Driving system, method, and program

Abstract

A driving system (2) comprises a processor (51b) and is configured to be capable of executing a dynamic driving task of a vehicle (1). The processor (51b) is configured to execute the following when the vehicle (1) is slated to pass through an intersection (IS) which is an area where the vehicle (1) can turn right or left: recognize an occulted area (OA) on the basis of sensor data from an external environment sensor (41) that is mounted on the vehicle (1) and monitors the surroundings of the vehicle (1); and plan the behavior of the vehicle (1) so as to change the mode of vehicle control pertaining to temporary stops in accordance with the recognition result for the occulted area (OA).

Description

Operating system, method and program CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based on Patent Application No. 2024-48791 filed in Japan on March 25, 2024, the contents of which are incorporated by reference in their entirety.

[0002] TECHNICAL FIELD This disclosure relates to techniques for performing dynamic driving tasks for a vehicle.

[0003] Patent Literature 1 discloses a system in which a vehicle is driven automatically when it is in a traffic jam. A decision is made to stop the automatic driving based on the results of image processing of a camera serving as a surroundings monitoring sensor.

[0004] Japanese Patent Application Laid-Open No. 2005-324661

[0005] Even if the autonomous driving does not stop, if an obstructed area is detected by the perimeter monitoring sensor, it may be difficult to execute the dynamic driving task, just as in the case where the obstructed area is not detected.

[0006] One of the purposes of the disclosure of this specification is to provide an operating system, method, and program that improves the appropriateness of dealing with occluded areas.

[0007] One aspect disclosed herein is a driving system having at least one processor and configured to be capable of executing a dynamic driving task for a vehicle, wherein the at least one processor is configured to: recognize an obstructed area based on sensor data from a surrounding monitoring sensor mounted on the vehicle that monitors the vehicle's surroundings when the vehicle is scheduled to pass through an area where right and left turns are possible; and plan the vehicle's behavior so as to change the vehicle control aspects regarding a temporary stop in accordance with the result of recognizing the obstructed area.

[0008] Another disclosed aspect is a method for performing a dynamic driving task of a vehicle, executed by at least one processor, which includes: recognizing an obstructed area based on sensor data from a surrounding monitoring sensor mounted on the vehicle that monitors the vehicle's surroundings when the vehicle is scheduled to pass through an area where a right or left turn is possible; and planning the vehicle's behavior so as to change the vehicle control mode regarding a temporary stop in accordance with the result of recognizing the obstructed area.

[0009] Another disclosed aspect is a program that executes processing to perform a dynamic driving task of a vehicle, and is configured to cause at least one processor to: recognize an obstructed area based on sensor data from a surrounding monitoring sensor that is mounted on the vehicle and monitors the vehicle's surroundings when the vehicle is scheduled to pass through an area where right and left turns are possible; and plan the vehicle's behavior so as to change the vehicle control mode regarding a temporary stop in accordance with the result of the recognition of the obstructed area.

[0010] According to these aspects, the dynamic driving task is planned to recognize an obstructed area, and the vehicle control mode for stopping temporarily is changed depending on the recognition result. That is, when passing through an area where a right or left turn is possible, the vehicle can make a more appropriate stop depending on the obstructed area, thereby increasing the appropriateness of dealing with the obstructed area.

[0011] Note that the symbols in parentheses included in the claims etc. are intended to exemplify the correspondence with the parts of the embodiments described below, and are not intended to limit the technical scope.

[0012] A diagram showing an example of the hardware configuration of a driving system, etc. A diagram showing the functional configuration of a driving system. A diagram showing an example of the configuration of a cockpit. A diagram showing an example of an intersection scenario in which a dynamic occlusion area has occurred. A diagram showing an example of an intersection scenario in which a static occlusion area has occurred. A flowchart illustrating processing in an intersection scenario. A flowchart illustrating processing in an intersection scenario. A configuration diagram explaining calculation of a sensor optimization position and an occupant optimization position. A flowchart illustrating processing in an intersection scenario. A configuration diagram explaining assumptions and plans using an acoustic sensor. A flowchart illustrating processing in an intersection scenario. A flowchart illustrating processing in an intersection scenario. A flowchart illustrating processing in an intersection scenario. A diagram showing an example of the hardware configuration of a processing system. A diagram showing an example of the hardware configuration of a processing system.

[0013] Hereinafter, several embodiments will be described with reference to the drawings. Note that corresponding components in each embodiment are given the same reference numerals, and redundant description may be omitted. When only a portion of the configuration is described in each embodiment, the configuration of another embodiment described previously can be applied to the remaining portion of the configuration. Furthermore, in addition to the combinations of configurations explicitly stated in the description of each embodiment, configurations of several embodiments can also be partially combined together even if not explicitly stated, as long as there is no particular problem with the combination.

[0014] (Explanation of Terms) Terms related to the disclosure of this specification are explained below. This explanation is included in the embodiments of the specification.

[0015] A road user may be a traffic participant on or adjacent to an active road for the purpose of traveling from one location to another.

[0016] A dynamic driving task (DDT) may be a real-time operational and tactical function for operating a vehicle in traffic, and a DDT may be all real-time operational and tactical functions for operating a vehicle on a roadway.

[0017] An ADS feature may be a design-specific functionality of an automated driving system within a particular operational design domain at a given automation level.

[0018] An automated driving system (ADS) may be a collection of hardware and software capable of performing the entire dynamic driving task on a continuous basis, whether or not it is limited to a specific operational design domain.

[0019] A DDT fallback may be a driver or automated system response to either perform the DDT or transition to a minimal-risk state after a failure or upon detection of a malfunction or potentially dangerous behavior. A DDT fallback may also be a method of transitioning from autonomy to driver or other system control using takeover / fallback conditions and associated use cases. A DDT fallback may also be a user response to perform the DDT or achieve a minimal-risk state after a system failure related to DDT performance or upon departure from the operational design domain, or a response by an automated driving system to achieve a minimal-risk state given the same circumstances.

[0020] A Minimal Risk Condition (MRC) may be a state of the vehicle to reduce risk if a given trip cannot be completed, or may be a stable, stopped state that a user or automated driving system places the vehicle in after DDT fallback is performed to reduce the risk of an accident if a given trip cannot or should not be continued.

[0021] An operational design domain (ODD) may be the specific conditions in which a given automated driving system is designed to function, and may include, but is not limited to, the operating conditions in which a given automated driving system or its features are specifically designed to function, including environmental, geographic, time-of-day restrictions, and / or the presence or absence of requirements for certain traffic and road characteristics.

[0022] Safety of the intended functionality (SOTIF) may be the absence of undue risk due to insufficient functionality of the intended functionality or its implementation.

[0023] A driving policy may be a strategy and rules that define control behavior at the vehicle level.

[0024] A scenario may be a description of the temporal relationships between several scenes in a sequence of scenes, including the goals and values ​​in a specific situation influenced by actions and events, and a description of a continuous time sequence of activities that integrates a subject vehicle, all its external environments, and their interactions in the process of performing a specific driving task.

[0025] A safety-relevant object may be any dynamic or static object that may be relevant to the safe performance of a dynamic driving task.

[0026] Reasonably foreseeable may be technically reliable and have a reliable or measurable rate of occurrence.

[0027] A triggering condition may be a specific condition of a scenario that acts as a catalyst for subsequent system responses that contribute to unsafe behavior, failure to prevent, detect, and mitigate reasonably foreseeable indirect misuse.

[0028] A Minimal Risk Maneuver (MRM) may be a vehicle movement commanded by the automated driving system during DDT fallback to achieve a minimal risk condition.

[0029] Risk acceptance criteria / criterion are standards that represent the absence of unreasonable levels of risk, and may be, for example, physical parameters that define when a particular behavior is considered undesirable, a maximum number of accidents per hour, as low as reasonably practicable, etc.

[0030] A proper response may be an action that is significant to avoid or ameliorate a dangerous situation in a reasonably foreseeable scenario in which other safety-related objects are operating within expected bounds.

[0031] A safety-related model may be a representation of safety-related aspects of driving behavior based on assumptions about the reasonably foreseeable behavior of other road users. A safety-related model may be an on-board or off-board safety verification or analysis device, a mathematical model, a more conceptual set of rules, a set of scenario-based behaviors, or a combination of these.

[0032] A formal model may be a model expressed in a formal notation that is used to verify system performance.

[0033] A safety envelope may be a set of limits and conditions within which an (automated) driving system is designed to operate, subject to constraints or controls, in order to maintain operation within an acceptable level of risk. A safety envelope may be a general concept that can be used to accommodate all principles to which a driving policy can adhere, according to which an ego-vehicle operated by an (automated) driving system may have one or more boundaries around it.

[0034] (First embodiment) <Driving system> The driving system 2 of the first embodiment shown in FIG. 1 realizes functions related to driving a vehicle 1. The driving system 2 may be a vehicle system itself, or may be a component that constitutes part of a vehicle system. Part or all of the driving system 2 is mounted on the vehicle 1. This vehicle 1 may be referred to as a subject vehicle EV, a host vehicle, or the like. The vehicle 1 may be configured to be able to communicate with other vehicles, etc., directly or indirectly via a communication infrastructure. The other vehicles may be referred to as target vehicles.

[0035] The vehicle 1 may be a road user capable of manual driving, such as a four-wheeled automobile or truck. The vehicle 1 may also be capable of automated driving. Autonomous driving may be a concept that includes autonomous driving by a driving system 2. Driving is classified into levels according to the extent to which a human driver performs all dynamic driving tasks (DDTs). Automation levels are specified, for example, in SAE J3016. At levels 0 to 2, the driver performs some or all of the DDTs. Levels 0 to 2 may be classified as so-called manual driving. Level 0 indicates that driving is not automated. Level 1 indicates that the driving system 2 assists the driver. Level 2 indicates that driving is partially automated. In other words, even at levels 1 and 2, autonomous driving by the driving system 2 is partially realized.

[0036] At levels 3 and above, while the ADS feature is activated, the driving system 2 performs all of the DDT. Levels 3 to 5 may be classified as so-called automated driving. A system capable of driving at level 3 or above may be called an automated driving system (ADS). A vehicle equipped with an automated driving system or a vehicle capable of driving at level 3 or above may be called an automated vehicle (AV).

[0037] Level 3 indicates conditional automation of driving. A level 3 automated driving system performs DDT but does not perform DDT fallback. That is, DDT fallback is performed by a driver who is ready for fallback. Level 4 indicates highly automated driving. A level 4 automated driving system performs DDT and DDT fallback. A level 4 automated driving system can hand over DDT to the driver after reaching a minimal risk condition (MRC) by performing DDT fallback, etc. Taking over DDT between the driving system 2 and a human driver is also called delegation of authority. Level 5 indicates fully automated driving.

[0038] The conditions for executing level 3 and level 4 autonomous driving may include some or all of the conditions indicated by the operational design domain (ODD). For example, the ADS function may be defined within the scope of the ODD. The driving system 2 described in this embodiment is a driving system capable of executing level 3 or higher autonomous driving. That is, the driving system 2 may be capable of executing autonomous driving up to level 3, up to level 4, or even level 5 autonomous driving.

[0039] The driving system 2 provides functions such as automated driving to a vehicle user of a vehicle 1 that can participate in public road traffic. For example, the vehicle user may be a driver riding in the vehicle 1. The vehicle user may be a passenger riding in the vehicle 1. For example, if the vehicle 1 is a POV (Personally Owned Vehicle), the vehicle user may be the owner of the vehicle 1. For example, if the vehicle 1 is used for MaaS (Mobility as a Service), the vehicle user may be an operator such as an operations manager that manages the operation of the vehicle 1.

[0040] The architecture of the driving system 2 is selected to enable an efficient safety of the intended functionality (SOTIF) process. For example, the architecture of the driving system 2 may be configured based on a sense-plan-act model. The sense-plan-act model includes a sense element, a plan element, and an act element as major system elements. The sense element, plan element, and act element interact with each other. Here, sense may be replaced with perception, plan with determine, and act with control, respectively.

[0041] At the technical level (i.e., from a technical perspective), the driving system 2 implements at least a plurality of sensors 40 corresponding to sensing functions, at least one processing system 50 corresponding to planning functions, and a plurality of motion actuators 60 corresponding to acting functions. At the functional level (i.e., from a functional perspective), the sensing, planning, and acting functions are implemented (see also FIG. 2 ).

[0042] In detail, a detection unit 10 serving as a processing unit for realizing a detection function may be constructed in the driving system 2, mainly consisting of a plurality of sensors 40, a processing system 50 for processing detection information from the plurality of sensors 40, and the processing system 50 for generating an environmental model based on information from the plurality of sensors 40. A planning unit 20 serving as a processing unit for realizing a planning function may be constructed in the driving system 2, mainly consisting of the processing system 50. A behavior unit 30 serving as a processing unit for realizing a behavior function may be constructed in the driving system 2, mainly consisting of a plurality of movement actuators 60 and at least one processing system 50 for outputting operation signals for the plurality of movement actuators 60.

[0043] Here, the detection unit 10 may be realized in the form of a detection system serving as a subsystem provided so as to be distinguishable from the planner 20 and the action unit 30. The planner 20 may be realized in the form of a planning system serving as a subsystem provided so as to be distinguishable from the detection unit 10 and the action unit 30. The planning system may include a risk confirmation function. The risk confirmation function may be mounted in the operation system 2 independently of the detection unit 10, the planner 20, and the action unit 30. The action unit 30 may be realized in the form of an action system serving as a subsystem provided so as to be distinguishable from the detection unit 10 and the planner 20. The detection system, the planning system, and the action system may constitute components independent of each other. The subsystem referred to here may be replaced with a module, a unit, a device, etc.

[0044] The detection unit 10 is responsible for detection functions, including localization (e.g., location estimation) of road users such as the vehicle 1 and other vehicles. The detection unit 10 detects the external environment, internal environment, vehicle state, and the state of the driving system 2 of the vehicle 1. The detection unit 10 fuses the detected information to generate an environmental model. The environmental model may also be referred to as a world model. The planner 20 applies the objective and driving policy to the environmental model generated by the detection unit 10 to derive control actions. The behavior unit 30 executes the control actions derived by the planner 20.

[0045] <Physical Architecture> An example of the physical architecture of the driving system 2 will be described using Figure 1. The driving system 2 includes a plurality of sensors 40, a plurality of motion actuators 60, a plurality of HMI devices 70, and at least one processing system 50. These components can communicate with each other via one or both of wireless and wired connections. These components may also be able to communicate with each other through an in-vehicle network such as CAN (registered trademark).

[0046] The plurality of sensors 40 includes one or more external environment sensors 41. Furthermore, the plurality of sensors 40 may include at least one of one or more internal environment sensors 42, one or more communication systems 43, and a map database (DB) 44.

[0047] The external environment sensor 41 may detect targets present in the external environment of the vehicle 1. Target detection type external environment sensors 41 include, for example, cameras, LiDAR (Light Detection and Ranging / Laser Imaging Detection and Ranging), laser radar, millimeter-wave radar, ultrasonic sonar, acoustic sensors, etc. Typically, multiple types of external environment sensors 41 may be combined and implemented to monitor the front, sides, and rear directions of the vehicle 1. The external environment sensor 41 corresponds to a perimeter monitoring sensor that monitors the periphery of the vehicle.

[0048] Here, the external environment sensor 41 includes a spatial information sensor that handles light, electromagnetic waves, sound waves, etc. emitted or reflected by a target as spatial information, and a temporal information sensor that handles sound waves, etc. emitted or reflected by a target as temporal information. Spatial information sensors can also be said to be visual. For example, laser radar, millimeter wave radar, and ultrasonic sonar correspond to spatial information sensors. Temporal information sensors can also be said to be auditory. For example, an acoustic sensor can be said to be a temporal information sensor.

[0049] Furthermore, the external environment sensor 41 may detect atmospheric conditions and weather conditions in the environment outside the vehicle 1. The condition detection type external environment sensor 41 is, for example, an outside air temperature sensor, a temperature sensor, a raindrop sensor, or the like.

[0050] The internal environment sensor 42 may detect a specific physical quantity related to vehicle motion (hereinafter referred to as a motion physical quantity) in the internal environment of the vehicle 1. The motion physical quantity detection type internal environment sensor 42 is, for example, a speed sensor, an acceleration sensor, a gyro sensor, etc. The internal environment sensor 42 may detect the state of an occupant in the internal environment of the vehicle 1. The occupant detection type internal environment sensor 42 is, for example, an actuator sensor, a sensor and its system for monitoring a vehicle user (e.g., a driver) in the vehicle cabin (hereinafter referred to as an interior monitor), a biological sensor, a seating sensor, an in-vehicle equipment sensor, etc. Here, the actuator sensor in particular is, for example, an accelerator sensor, a brake sensor, a steering sensor, etc., which detect the state of an occupant's operation of a motion actuator 60 related to the motion control of the vehicle 1.

[0051] The communication system 43 obtains communication data usable in the driving system 2 via wireless communication. The communication system 43 may receive positioning signals from artificial satellites of a global navigation satellite system (GNSS) that exist in the external environment of the vehicle 1. The positioning type communication device in the communication system 43 is, for example, a GNSS receiver.

[0052] The communication system 43 may transmit and receive communication signals to and from an external system (e.g., a server 96) present in the external environment of the vehicle 1. Examples of V2X-type communication devices in the communication system 43 include dedicated short range communications (DSRC) communication devices, cellular V2X (C-V2X) communication devices, etc. Examples of communication with a V2X system present in the external environment of the vehicle 1 include communication with a communication system of another vehicle (V2V), communication with infrastructure equipment such as a communication device installed in a traffic light or a roadside device (V2I), communication with a mobile terminal of a pedestrian (V2P), and communication with a network such as a cloud server (V2N). The architecture of V2X communication, including V2I communication, may be an architecture defined in ISO 21217, ETSI TS 102 940-943, IEEE 1609, etc.

[0053] Furthermore, the communication system 43 may transmit and receive communication signals to and from a mobile terminal 91, such as a smartphone, present inside the vehicle 1. Examples of terminal communication type communication devices in the communication system 43 include Bluetooth (registered trademark) devices, Wi-Fi (registered trademark) devices, infrared communication devices, etc. Furthermore, if the vehicle user's mobile terminal 91 is associated with the vehicle 1 in advance, the communication system 43 may transmit and receive communication signals to and from the mobile terminal present in the external environment.

[0054] The map DB 44 is a database that stores map data available to the driving system 2. The map DB 44 includes at least one type of non-transitory tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium. The map DB 44 may include a database of a navigation unit that navigates the vehicle 1 along a route to a destination. The map DB 44 may include a database of probe data (PD) maps generated using probe data (PD) collected from each vehicle. The map DB 44 may include a database of high-precision maps with a high level of accuracy that are primarily used in automated driving systems. The map DB 44 may also include a database of parking lot maps that include detailed parking lot information, such as parking space information, that is used in automated parking or parking assistance applications.

[0055] The map DB 44 suitable for the driving system 2 acquires and stores the latest map data, for example, by communicating with a map server via a V2X communication system 43. The map data is data representing the external environment of the vehicle 1, and is converted into two-dimensional or three-dimensional data. The map data may include road data representing at least one of the position coordinates, shape, road surface condition, and standard running route of a road structure. The map data may also include marking data representing at least one of the position coordinates and shape of road signs, road markings, and lane markings attached to a road. The marking data included in the map data may represent landmarks such as traffic signs, arrow markings, lane markings, stop lines, directional signs, landmark beacons, business signs, and changes in road line patterns. The map data may also include structure data representing at least one of the position coordinates and shape of buildings and traffic lights facing the road. The marking data included in the map data may represent landmarks such as street lights, road edges, reflectors, and poles.

[0056] The motion actuator 60 can control vehicle motion based on an input control signal. The drive-type motion actuator 60 is, for example, a power train including at least one of an internal combustion engine, a drive motor, etc. The braking-type motion actuator 60 is, for example, a brake actuator. The steering-type motion actuator 60 is, for example, a steering.

[0057] As shown in FIG. 3 , a plurality of HMI (Human Machine Interface) devices 70 may be mounted on the vehicle 1. The HMI devices 70 realize human-machine interaction, which is an interaction between a user of the vehicle 1 and the driving system 2. Of the plurality of HMI devices 70, a portion that realizes an operation input function by an occupant may be part of the detection unit 10. Of the plurality of HMI devices 70, a portion that realizes an information presentation function may be part of the behavior unit 30. On the other hand, the function realized by the HMI device 70 may be positioned as a function independent of the detection function, the planning function, and the behavior function.

[0058] The HMI device 70 may be an operation input device 70a that can input user operations to transmit the will or intention of the user of the vehicle 1 to the driving system 2. Examples of the operation input type HMI device 70 include an accelerator pedal, a brake pedal, a shift lever, a steering wheel, a turn signal lever (a lever for operating a turn signal), a mechanical switch, and a touch panel of a navigation unit or the like. Of these, the accelerator pedal controls a powertrain as a motion actuator 60. The brake pedal controls a brake actuator as a motion actuator 60. The steering wheel controls a steering actuator as a motion actuator 60.

[0059] The HMI device 70 may be an information presentation device 70b that presents information such as visual information, auditory information, and cutaneous information to the user of the vehicle 1. Examples of the visual information presentation type HMI device 70 include a meter display 70b1, a navigation unit, a CID (center information display) 70b2, a HUD (head-up display) 70b3, and an illumination unit, as shown in FIG.

[0060] The meter display 70b1 is a display device that is arranged, for example, in a driver-facing portion of the instrument panel that faces the driver's seat. The meter display 70b1 displays to the driver information necessary for driving, focusing on the vehicle status including the speed of the vehicle 1. The meter display 70b1 may be a graphic meter that displays all information using images, or may be a combination meter that combines an image display with an analog display using a device.

[0061] The CID 70b2 is a display device disposed, for example, in the center of the instrument panel. The CID 70b2 has the largest display screen of all the in-vehicle display devices mounted on the instrument panel. The CID 70b2 is capable of displaying images not only to the driver but also to passengers. The CID 70b2 may include a touch panel that can be operated by the vehicle user. In this case, the CID 70b2 also corresponds to the operation input device 70a.

[0062] The HUD 70b3 is a display device arranged on the instrument panel on the opposite side of the driver's seat from the meter display 70b1, i.e., on the rear side of the area facing the driver's seat. The HUD 70b3 projects an image onto the front windshield of the vehicle 1, thereby displaying a virtual image VI that the driver can visually recognize as floating outside the vehicle.

[0063] Furthermore, instead of the CID 70b2 and the meter display 70b1, a pillar-to-pillar display arranged to cross the left and right A-pillars may be employed. Even in this case, the pillar-to-pillar display may be divided into several screens, each of which may be controlled in the same manner as the CID 70b2 and the meter display 70b1.

[0064] In addition, an information presentation device 70b (hereinafter referred to as a passenger display) of a visual information presentation type that mainly targets passengers other than the driver may be provided. For example, among pillar-to-pillar displays, a screen disposed opposite the passenger seat and a display installed in the rear seat correspond to passenger displays.

[0065] The auditory information presentation type HMI device 70 is, for example, a speaker, a buzzer, etc. The tactile information presentation type HMI device 70 is, for example, a steering wheel vibration unit, a driver's seat vibration unit, a steering wheel reaction force unit, an accelerator pedal reaction force unit, a brake pedal reaction force unit, an air conditioning unit, etc.

[0066] Furthermore, the HMI device 70 may realize an HMI function linked to a mobile terminal 91 such as a smartphone by mutually communicating with the terminal through the communication system 43. For example, as an alternative means for presenting information by the HMI device 70, information from the driving system 2 may be displayed on the screen of the vehicle user's smartphone through the communication system 43. On the other hand, the HMI device 70 may present information acquired from the smartphone to the vehicle user. Also, for example, an operation input to a smartphone may be an alternative means for inputting an operation to the HMI device 70.

[0067] Furthermore, the HMI device 70 may be an exterior information presentation device 70c that presents information such as visual information and audio information to other road users in the external environment of the vehicle 1. The exterior information presentation device 70c is, for example, a turn signal lamp (directional indicator), a hazard lamp, an exterior image display (including bus destination displays, etc.), a speaker, etc.

[0068] At least one processing system 50 is provided. For example, the processing system 50 may be an integrated processing system that integrally executes processing related to the detection function, processing related to the planning function, and processing related to the action function. In this case, the integrated processing system 50 may further execute processing related to the HMI device 70, or a processing system dedicated to the HMI may be provided separately. For example, the processing system dedicated to the HMI may be an integrated cockpit system that integrally executes processing related to each HMI device 70. The processing system 50 may be provided by an in-vehicle platform that can be used generally for AVs.

[0069] For example, the processing system 50 may be configured to have at least one processing unit corresponding to processing related to the detection function, at least one processing unit corresponding to processing related to the planning function, and at least one processing unit corresponding to processing related to the behavioral function.

[0070] The processing system 50 has a communication interface to the outside and is connected to at least one type of element related to processing by the processing system 50, such as each sensor 40, motion actuator 60, and HMI device 70, via at least one type of interface, such as a LAN (Local Area Network), a wire harness, an internal bus, or a wireless communication circuit.

[0071] The processing system 50 includes a main unit 51 mainly composed of at least one dedicated computer. The processing system 50 may realize functions such as a detection function, a planning function, and an action function by the main unit 51 which is a combination of multiple dedicated computers. The main unit 51 may be referred to as an operation control device.

[0072] For example, the dedicated computer constituting the main unit 51 may be an integrated ECU that integrates the driving functions of the vehicle 1. The dedicated computer constituting the main unit 51 may be a determination ECU that determines DDT. The dedicated computer constituting the main unit 51 may be a monitoring ECU that monitors the driving of the vehicle 1. The dedicated computer constituting the main unit 51 may be an evaluation ECU that evaluates the driving of the vehicle 1. The dedicated computer constituting the main unit 51 may be a navigation ECU that navigates the driving route of the vehicle 1.

[0073] Furthermore, the dedicated computer constituting the main unit 51 may be a locator ECU that estimates the position of the vehicle 1. The dedicated computer constituting the main unit 51 may be an image processing ECU that processes image data detected by the external environment sensor 41. The dedicated computer constituting the main unit 51 may be an actuator ECU that controls the motion actuator 60 of the vehicle 1. The dedicated computer constituting the main unit 51 may be an HCU (HMI Control Unit) that comprehensively controls the HMI device 70. The dedicated computer constituting the main unit 51 may include at least one external computer provided in an external center or mobile terminal 91 that can communicate via the communication system 43, for example.

[0074] The dedicated computer constituting the main unit 51 has at least one memory 51a and one processor 51b. The memory 51a may be at least one type of non-transient tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium, that non-temporarily stores computer programs and data that can be read by the processor 51b. Furthermore, the memory 51a may be provided with a rewritable volatile storage medium, such as a random access memory (RAM). The processor 51b includes at least one type of core, such as a central processing unit (CPU), a graphics processing unit (GPU), or a reduced instruction set computer (RISC)-CPU.

[0075] The dedicated computer constituting the main unit 51 may be a SoC (System on a Chip) that integrates the memory 51a, processor 51b, and interface into a single chip, or may have at least one SoC as a component of the dedicated computer.

[0076] Furthermore, the processing system 50 may include at least one database for executing the DDT, which may include at least one type of non-transitory tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium, and an interface for accessing the storage medium.

[0077] The database may be a scenario database (hereinafter referred to as a scenario DB) 59. The database may be a rule database (hereinafter referred to as a rule DB) 58. At least one of the scenario DB 59 and the rule DB 58 may be configured integrally with the main unit 51. At least one of the scenario DB 59 and the rule DB 58 may not be provided in the processing system 50, but may be provided independently in the operation system 2. At least one of the scenario DB 59 and the rule DB 58 may be provided in an external system present in the external environment, and configured to be accessible from the processing system 50 via the communication system 43.

[0078] The scenario DB 59 has a scenario catalog in which multiple scenarios used for driving the vehicle 1 are stored. The driving system 2 can, for example, apply a situation in which the vehicle 1 is placed to one scenario selected from the multiple scenarios or a combination of multiple scenarios. The scenario DB 59 may store multiple scenarios including at least one of a functional scenario, a logical scenario, and a concrete scenario. A functional scenario defines a top-level qualitative scenario structure. A logical scenario is a scenario in which quantitative parameter ranges are assigned to a structured functional scenario. A concrete scenario defines a safety judgment boundary that distinguishes between a safe state and an unsafe state.

[0079] The rule DB 58 stores a rule set used for driving the vehicle 1. The rule set may include multiple rules. The rule set may further include a priority structure for the rules, which is set based on the relative importance of the multiple rules. The rule set may be an implementation of guidelines for strategic driving of the vehicle 1.

[0080] The plurality of rules may include rules based on laws, regulations, or a combination thereof. The plurality of rules may include rules based on preferences that are not influenced by laws, regulations, or the like. The plurality of rules may include rules based on exercise behavior based on past experience. The plurality of rules may include rules based on characterization of the exercise environment. The plurality of rules may include rules based on ethical concerns. The plurality of rules may include rules based on basic principles of a safety model (e.g., the five principles of the RSS model). The plurality of rules may include traffic rules. The traffic rules may be rules specified in the Road Traffic Act or may be rules based on national or local customs.

[0081] The rules such as traffic rules stored in the rule DB 58 may be positioned as information provided from the detection unit 10 to the planning unit 20 by the detection function, similar to the map information acquired from the map DB 44 .

[0082] The processing system 50 may also include at least one recording device 55 that records at least one of the detection information, planning information, and behavioral information of the driving system 2. The recording device 55 sequentially records event data related to the driving task of the vehicle 1. The event data is data that records events encountered by the vehicle 1. The event data may include at least one of various types of information related to the driving task, such as information about the operation of the motion actuators 60, information about the route or trajectory traversed or planned by the vehicle 1, information about a scenario encountered by the vehicle 1, information about the automation level or delegation of authority of the vehicle 1, and information about the execution of the DDT fallback or MRM of the vehicle 1.

[0083] The recording device 55 may include at least one large-capacity storage medium 55c. The storage medium 55c may be at least one type of non-transitory tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium. The storage medium 55c may be mounted on a board in a form that is not easily removable or replaceable, such as an embedded multimedia card (eMMC) using flash memory. At least one of the storage media 55c may be removable and replaceable from the recording device 55, such as an SD card.

[0084] At least one of the recording device 55 and the storage medium 55c may correspond to an EDR (Event Data Recorder) or a DSSAD (Data Storage System for Automated Driving). The recording device 55 may have a function for selecting information to be recorded from the event data. In this case, the recording device 55 may have a dedicated computer.

[0085] The dedicated computer provided in the recording device 55 has at least one memory 55a and one processor 55b. The memory 55a may be at least one type of non-transient tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium, that non-temporarily stores computer programs and data that can be read by the processor 55b. Furthermore, the memory 55a may be a rewritable volatile storage medium, such as a random access memory (RAM). The processor 55b includes at least one type of core, such as a central processing unit (CPU), a graphics processing unit (GPU), or a reduced instruction set computer (RISC)-CPU.

[0086] The dedicated computer may be a SoC (System on a Chip) in which the memory 55a, processor 55b, and interface are integrated into a single chip, or may have at least one SoC as a component of the dedicated computer.

[0087] The recording device 55 may access the storage medium 55c and perform recording in accordance with a data write command from each part of the driving system 2. The recording device 55 may determine information transmitted over the in-vehicle network, and, based on the judgment of the processor 55b provided in the recording device 55, access the storage medium 55c and perform recording.

[0088] Furthermore, the recording device 55 may not be provided in the processing system 50, but may be provided independently in the operation system 2. The recording device 55 may be provided in an external system present in the external environment, and configured to be accessible from the processing system 50 via the communication system 43.

[0089] Furthermore, the processing system 50 may include at least one risk confirmation unit 53. The risk confirmation unit 53 may be one aspect of an on-board implementation of RSS (Responsibility Sensitive Safety) as a safety model. The risk confirmation unit 53 may be an on-board checker for the planning function realized by a dedicated computer. In other words, the risk confirmation unit 53 may be a risk confirmation device. The risk confirmation unit 53 realizes the risk confirmation function by hardware independent of the planning unit 20.

[0090] The risk confirmation unit 53 may be primarily configured as a dedicated computer having at least one memory 53a and one processor 53b. The memory 53a may be at least one type of non-transient tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium, that non-temporarily stores computer programs and data readable by the processor 55b. Furthermore, the memory 55a may be provided with a rewritable volatile storage medium, such as a random access memory (RAM). The processor 55b includes at least one type of core, such as a central processing unit (CPU), a graphics processing unit (GPU), or a reduced instruction set computer (RISC)-CPU.

[0091] The dedicated computer may be a SoC (System on a Chip) in which the memory 53a, processor 53b, and interface are integrated into a single chip, or may have at least one SoC as a component of the dedicated computer.

[0092] As described above, the processing system 50 includes memories 51a, 53a, and 55a storing software. The processors 51b, 53b, and 55b are configured to operate the software to realize automated driving, allowing authority to be transferred between the system itself and the user. The software here may include the computer program itself used in the driving system 2. The software here may include an algorithm in the computer program used in the driving system 2. The software here may include parameters in the computer program used in the driving system 2. The software here may include a trained model, sometimes referred to as AI, implemented by, for example, a neural network, used in the driving system 2. Furthermore, the software may include data stored in a database referenced by the processing system 50, data stored in the map DB 44, and the like. One piece of software may correspond to one application or multiple applications, may be part of one application, or may be software commonly used by multiple applications.

[0093] Furthermore, the processing system 50 may include at least one software management unit 57. The software management unit 57 realizes a software management function. The software management unit 57 may also be referred to as a vehicle software management device. The software management unit 57 manages various software used in the processing system 50, such as the main unit 51, the risk confirmation unit 53, the recording device 55, the rule DB 58, and the scenario DB 59. The software management unit 57 may also manage software used in the driving system 2 outside the processing system 50. For example, the software management unit 57 may manage data stored in the map DB 44, software used for drawing processing by the information presentation device 70b, software used for communication processing by the communication system 43, etc.

[0094] Software management may include software version management, download and installation processes, uninstallation processes, etc. Software management may also include software testing using a shadow mode, etc.

[0095] The software management unit 57 may be configured primarily as a dedicated computer having at least one memory 57a and one processor 57b to realize the software management function. The memory 57a may be at least one type of non-transient tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium, that non-temporarily stores computer programs and data readable by the processor 57b. Furthermore, the memory 57a may be provided with a rewritable volatile storage medium, such as a random access memory (RAM). The processor 57b includes at least one type of core, such as a central processing unit (CPU), a graphics processing unit (GPU), or a reduced instruction set computer (RISC)-CPU.

[0096] The dedicated computer may be a SoC (System on a Chip) in which the memory 57a, processor 57b, and interface are integrated into a single chip, or may have at least one SoC as a component of the dedicated computer.

[0097] <Logical Architecture in Autonomous Driving> Next, an example of a logical architecture in the driving system 2 will be described using Figure 2. The description here will focus on processing by a computer program executed during autonomous driving at level 3 or higher. The detection unit 10 may include an environment recognition unit 11, a self-location recognition unit 12, and an internal recognition unit 13 as processing units for realizing sub-functions obtained by further classifying the detection function by the processor 51b executing a computer program.

[0098] The environment recognition unit 11 individually processes information (sometimes referred to as sensor data) related to the external environment acquired from each sensor 40, and realizes a function of recognizing the external environment including targets, other road users, etc. The environment recognition unit 11 individually processes the sensor data detected by each external environment sensor 41. The sensor data may be sensor data provided by, for example, millimeter-wave radar, sonar, LiDAR, etc. The environment recognition unit 11 may generate relative position data including the direction, size, and distance of an object relative to the vehicle 1 from the raw data detected by the external environment sensors 41.

[0099] The sensor data may be image data provided by, for example, a camera, LiDAR, or the like. The environment recognition unit 11 processes the image data and extracts objects reflected within the angle of view of the image. The object extraction may include estimating the direction, size, and distance of the object relative to the vehicle 1. The object extraction may also include classifying the object using, for example, semantic segmentation.

[0100] Furthermore, the environment recognition unit 11 processes information acquired through the V2X function of the communication system 43. The environment recognition unit 11 processes information acquired from the map DB 44.

[0101] The environment recognition unit 11 may be further divided into a plurality of sensor recognition units each optimized for one sensor group. When a sensor recognition unit is associated with recognizing information from one sensor group, the sensor recognition unit may fuse information from the one sensor group.

[0102] The self-location recognition unit 12 performs localization of the vehicle 1. The self-location recognition unit 12 acquires global position data of the vehicle 1 from the communication system 43 (e.g., a GNSS receiver). In addition, the self-location recognition unit 12 may acquire position information of targets extracted by the environment recognition unit 11. The self-location recognition unit 12 also acquires map information from the map DB 44. The self-location recognition unit 12 integrates this information to estimate the position of the vehicle 1 on the map.

[0103] The internal recognition unit 13 processes sensor data detected by each internal environment sensor 42 and realizes a function of recognizing the vehicle state. The vehicle state may include the state of the physical quantities of motion of the vehicle 1 detected by a speed sensor, an acceleration sensor, a gyro sensor, etc. The vehicle state may also include at least one of the user state, the user's operation state of the motion actuator 60, and the switch state of the HMI device 70.

[0104] The planning unit 20 may include a prediction unit 21, an operation planning unit 22, and a mode management unit 23 as processing units for realizing sub-functions that are further classified into planning functions by having processors 51b, 53b execute computer programs.

[0105] The prediction unit 21 acquires information on the external environment recognized by the environment recognition unit 11 and the self-position recognition unit 12, the vehicle state recognized by the internal recognition unit 13, etc. The prediction unit 21 may interpret the environment based on the acquired information and estimate the current situation of the vehicle 1. The situation here may be an operational situation or may include the operational situation.

[0106] The prediction unit 21 may interpret the environment and predict the behavior of an object, such as another road user. The object may be a safety-relevant object. The behavior prediction may include at least one of predicting the object's speed, predicting the object's acceleration, and predicting the object's trajectory. The behavior prediction may be performed based on reasonably foreseeable assumptions. Furthermore, the prediction unit 21 may infer the user's intention based on the predicted behavior, predicted potential hazards, and the acquired vehicle state.

[0107] The driving planning unit 22 plans autonomous driving of the vehicle 1 based on at least one of the estimated information of the vehicle 1's position on a map by the self-position recognition unit 12, the prediction information and user intention estimation information by the prediction unit 21, and the function constraint information by the mode management unit 23.

[0108] The driving planner 22 realizes a route planning function, a behavior planning function, and a trajectory planning function. The route planning function is a function of planning at least one of a route to a destination and a mid-range lane plan based on estimated information about the position of the vehicle 1 on a map. The route planning function may further include a function of determining at least one of a lane change request and a deceleration request based on the mid-range lane plan. Here, the route planning function may be a mission / route planning function in a strategic function, and may be a function of outputting a mission plan and a route plan.

[0109] The behavior planning function is a function that plans the behavior of the vehicle 1 based on at least one of the route to the destination planned by the route planning function, a mid-distance lane plan, a lane change request and a deceleration request, prediction information and user intention estimation information by the prediction unit 21, and function constraint information by the mode management unit 23. The behavior planning function may include a function that generates conditions related to state transitions of the vehicle 1. The conditions related to state transitions of the vehicle 1 may correspond to triggering conditions. The conditions related to state transitions may include fallback conditions for executing DDT fallbacks.

[0110] The behavior planning function may include a function for determining state transitions of an application that realizes the DDT and further state transitions of driving actions based on the conditions. As a result, the driving planner 22 plans the execution of a DDT fallback. If this does not involve authority delegation, the driving planner 22 may further execute a Minimal Risk Maneuver (MRM) together with the motion control unit 31 to transition the vehicle 1 to a minimal risk state. The MRM plan may be realized by the behavior planning function or the trajectory planning function.

[0111] The behavior planning function may also include a function for determining, based on the information on these state transitions, longitudinal constraints on the path of the vehicle 1 and lateral constraints on the path of the vehicle 1. The behavior planning function may be a tactical behavior plan in the DDT function, and may output tactical behavior.

[0112] The trajectory planning function is a function that plans a driving trajectory of the vehicle 1 based on the judgment information by the prediction unit 21, longitudinal constraints on the path of the vehicle 1, and lateral constraints on the path of the vehicle 1. The trajectory planning function may include a function that generates a path plan. The path plan may include a speed plan, or the speed plan may be generated as a plan independent of the path plan. The trajectory planning function may include a function that generates multiple path plans and selects an optimal path plan from the multiple path plans, or a function that switches between path plans. The trajectory planning function may further include a function that generates backup data of the generated path plan. The trajectory planning function may be a trajectory planning function in the DDT function, and may output a trajectory plan.

[0113] The mode management unit 23 monitors the driving system 2 and sets constraints on driving-related functions. The mode management unit 23 may manage the autonomous driving mode, for example, the state of the automation level. The management of the automation level may include management of switching between manual driving and autonomous driving, i.e., management of the transfer of authority between the user and the driving system 2, in other words, management of the takeover of driving. The mode management unit 23 may monitor the state of the subsystem related to the driving system 2 and determine a system malfunction (e.g., an error, an unstable operation state, a system failure, or a malfunction). The mode management unit 23 may determine a mode based on the user's intention based on the user's intention estimation information generated by the internal recognition unit 13. The mode management unit 23 may set constraints on driving-related functions based on at least one of the system malfunction determination result, the mode determination result, the vehicle state determined by the internal recognition unit 13, the sensor abnormality (or sensor failure) signal output from the sensor 40, the application state transition information and the trajectory plan determined by the driving planner 22, etc.

[0114] Furthermore, the mode management unit 23 may have a comprehensive function of determining, in addition to constraints on driving functions, longitudinal constraints on the path of the vehicle 1 and lateral constraints on the path of the vehicle 1. In this case, the operation planning unit 22 plans behavior and trajectories in accordance with the constraints determined by the mode management unit 23.

[0115] When the automation level is switched to level 2 or lower, the mode management unit 23 may control the enablement state of the driving assistance application according to the automation level.

[0116] When the risk confirmation function is implemented as part of the planner 20, the risk confirmation function may be implemented as part of the functions realized by the predictor 21, the operation planner 22, and the mode manager 23. On the other hand, the risk confirmation function may be implemented as a function independent of the planner 20 (see also FIG. 3 ).

[0117] The risk confirmation function is a function that acquires an environmental model, sensor data, etc. from the detection unit 10, evaluates a risk based on this information, and outputs a response based on the risk to the behavior unit 30 or the operation planning unit 22. This series of functions or processes may be referred to as risk confirmation or risk monitoring.

[0118] More specifically, the risk confirmation function outputs a situation based on information acquired from the detection unit 10. The risk confirmation function confirms whether the situation is safe or dangerous. This confirmation may include confirmation of an estimated result of a collision risk between the vehicle 1 and a surrounding object. In this confirmation, an index such as a collision probability may be used to take uncertainty into account. The risk confirmation function may compare an acceptable collision risk threshold with the estimated collision risk value to determine whether the situation is dangerous. The acceptable collision risk threshold may be set in advance based on risk acceptance criteria / criterion.

[0119] The risk tolerance criteria may be set based on a positive risk balance. The positive risk balance can be said to be the main measure of an ethically acceptable risk level. A quantitative criterion for the risk tolerance criteria is, for example, that the probability of harm occurring is below a threshold. The risk tolerance criteria may be set by combining a statistical approach, such as traffic statistics, with a scenario-based approach.

[0120] The risk confirmation function derives a proper response based on the result of this confirmation. The proper response may be provided to the behavior unit 30 or the driving plan unit 22 only if the situation is determined to be a dangerous situation. The proper response may be a restriction on the control command of the motion actuator 60. The proper response may be a response to return the vehicle 1 to a safe state.

[0121] The risk confirmation function is realized by implementing a safety model. The safety model may be referred to as a safety-related model. The safety model may be a formal model. For example, an RSS model may be adopted as the safety model, but other models such as an SFF model, a more generalized model, or a composite model combining multiple models may also be adopted. SFF stands for Safety Force Field. The safety model monitors the risk of the vehicle 1 based on a driving policy. In other words, risk monitoring can also be said to be monitoring the driving policy.

[0122] In the RSS model, for example, the longitudinal and lateral safety distances from other road users are used as indicators for determining collision risk. The safety distances are an example of a geometric approach, such as a safety envelope.

[0123] The behavior unit 30 may include a motion control unit 31 and an HMI output unit 71 as processing units for realizing sub-functions obtained by further classifying the behavior functions by the processor 51b executing a computer program. The motion control unit 31 controls the motion of the vehicle 1 based on the trajectory plan (e.g., a path plan and a speed plan) acquired from the driving plan unit 22. Specifically, the motion control unit 31 generates accelerator request information, shift request information, brake request information, and steering request information according to the trajectory plan, and outputs them to the motion actuator 60.

[0124] Here, the motion control unit 31 can directly obtain the vehicle state recognized by the detection unit 10 (particularly the internal recognition unit 13), such as at least one of the current speed, acceleration, and yaw rate of the vehicle 1, from the detection unit 10 and reflect this in the motion control of the vehicle 1.

[0125] The HMI output unit 71 outputs information related to the HMI based on at least one of prediction information and user intention estimation information from the prediction unit 21, application state transition information and trajectory planning from the operation planning unit 22, and function constraint information from the mode management unit 23. The HMI output unit 71 may manage vehicle interactions. The HMI output unit 71 may generate an information presentation request based on the management state of the vehicle interactions and control the information presentation function of the HMI device 70. Furthermore, the HMI output unit 71 may generate control requests for wipers, a sensor washing device, headlights, and an air conditioning device based on the management state of the vehicle interactions and control these devices.

[0126] <Intersection Scenario with Other Blocked Road Users> Here, we will explain the response of vehicle 1 in a scenario in which vehicle 1 passes through an intersection IS, as shown in Figures 4 and 5. The intersection IS is a type of area where a right or left turn is possible. Here, the area where a right or left turn is possible is any area where at least one of a right turn or a left turn is possible, and may be, for example, a crossroads, a T-junction, or a five-way intersection. Passing through the intersection IS here may involve going straight through, or turning right or left.

[0127] In the scenarios of Figures 4 and 5, vehicle 1 is approaching an intersection IS. Based on traffic rules such as the Road Traffic Act, vehicle 1 has the right of way at the intersection IS. At the intersection IS, a traffic light TL may be present, as shown in Figures 4 and 5, and a stop line may also be present. Just before the intersection IS, there may be a crosswalk CW for pedestrians to cross the road, as shown in Figure 5.

[0128] In such a scenario, there is a possibility that other road users are present in an obstructed area OA obstructed by a dynamic object DO or a static object SO within or around the intersection IS, in an area that may affect passage through the intersection IS. Hereinafter, the obstructed area OA obstructed by a dynamic object DO such as another vehicle shown in Figure 4 will be referred to as a dynamic obstructed area DOA. The obstructed area OA obstructed by a static object SO such as a thicket of plants shown in Figure 5 will be referred to as a static obstructed area SOA. The obstructed area OA may also be referred to as a blind spot.

[0129] In the driving system 2 of the vehicle 1, the prediction unit 21 identifies a scenario in which the vehicle 1 is about to travel through an intersection IS, i.e., an intersection scenario, based on the sensor data from the environment recognition unit 11, the global position data from the self-position recognition unit 12, and the vehicle state acquired from the internal recognition unit 13. Furthermore, the prediction unit 21 identifies whether or not there is an obstructed area OA within the detection area of ​​the external environment sensor 41 (particularly the spatial information sensor) that is obstructed by an object and cannot be detected. If an obstructed area OA exists, the prediction unit 21 identifies its extent. The identified obstructed area OA is reflected in the environment model. Furthermore, the prediction unit 21 reflects a traffic signal TL and a pedestrian crossing CW in the environment model.

[0130] The driving planner 22 plans autonomous driving in an intersection scenario. The driving planner 22 plans the behavior of the vehicle 1 so as to change the mode of vehicle control, for example, regarding a stop, depending on the recognition result of the occluded area OA. When the driving planner 22 does not recognize the occluded area OA where other road users may appear, the driving planner 22 determines to pass through the intersection IS based on the right-of-way generated by traffic rules.

[0131] On the other hand, when the driving planner 22 recognizes an obstructed area OA where other road users may appear, the driving planner 22 further changes the mode of vehicle control depending on whether or not there is a crosswalk CW before the intersection IS. If there is no crosswalk CW, the driving planner 22 makes a temporary stop before the intersection IS (or before the stop line if there is one), and plans the subsequent fine movement control.

[0132] When there is a crosswalk CW, the driving planning unit 22 plans to make a temporary stop before the crosswalk CW and to issue a warning to the occupants of the vehicle 1. Furthermore, the driving planning unit 22 plans subsequent fine movement control in the same way as when there is no crosswalk CW.

[0133] The notification here is a notification that prompts the occupant of the vehicle 1 to monitor the surroundings. The notification may be provided by at least one of the meter display 70b1, the CID 70b2, and the HUD 70b3 through the HMI output unit 71, or may be provided in combination with a sound notification using a speaker. The occupant monitoring the surroundings can request the driving system 2 to take over driving or can request an emergency stop of the vehicle 1, depending on the situation.

[0134] Furthermore, when the vehicle 1 stops temporarily before an intersection IS or a crosswalk CW, the driving planner 22 may plan a positioning of the vehicle 1 that is offset laterally from the center of the lane so as to improve the extent of the blocked area OA rather than when the vehicle 1 is positioned at the center of the lane. Control for implementing this positioning may be referred to as offset control. This can increase the possibility of improving the blocked area OA when fine movement control, which will be described later, is implemented.

[0135] The fine movement control is a vehicle control that alternately repeats temporary stops and fine movements. The fine movement of the vehicle 1 may change the range of the shielded area OA to a range that is favorable for passing through the intersection IS, or may eliminate the shielded area OA itself. The fine movement here is mainly a slight forward movement, but may also include at least one of backing up and changing the direction of the vehicle 1 if it is expected that at least one of backing up and changing the direction of the vehicle 1 will improve the shielded area OA.

[0136] The driving planning unit 22 determines whether the shaded area OA has improved to a level where the vehicle 1 can pass through the intersection IS with little risk after the vehicle 1 performs the fine movement control for a preset time or a preset number of times. If the shaded area OA has not improved, the driving planning unit 22 determines to issue a notification to prompt the occupants of the vehicle 1 to monitor the surroundings. Then, the driving planning unit 22 determines to pass through the intersection IS in a state where the presence of the vehicle 1 is conspicuous.

[0137] The state in which the presence of the vehicle 1 is made conspicuous may be a state in which the presence of the vehicle 1 is made conspicuous by special information presentation (display color, brightness, flashing pattern, horn sound, siren sound, etc.) by the exterior information presentation device 70c. For example, the illumination of a turn signal lamp, a hazard lamp, etc. may be used.

[0138] An example of a processing method for dealing with an intersection scenario in the vehicle 1 will now be described using the flowchart in Fig. 6. The series of processes in S101 to S112 may be realized, for example, by the processor 51b of the main unit 51 executing a computer program stored in the memory 51a.

[0139] In S101, the main unit 51 (particularly the prediction unit 21) identifies that the scenario that the vehicle 1 is encountering is an intersection scenario. In S102 after S101, the main unit 51 (particularly the prediction unit 21) identifies an occlusion area OA. After processing S102, the process proceeds to S103.

[0140] In S103, the main unit 51 (particularly the driving plan unit 22) determines whether the blocked area OA identified in S102 is a blocked area where other road users may appear. If the determination is Yes, the process proceeds to S104. If the determination is No, the process proceeds to S112.

[0141] In S104, the main unit 51 (particularly the operation planning unit 22) determines whether or not a crosswalk CW is present before the intersection IS. If the determination is Yes, the process proceeds to S105. If the determination is No, the process proceeds to S107.

[0142] In S105, the main unit 51 (particularly the driving planner 22) determines to make a temporary stop before the crosswalk CW. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 stops temporarily. In S106 after S105, the main unit 51 (particularly the driving planner 22) determines to issue a notification urging the occupants to monitor their surroundings. Based on this plan, the main unit 51 (particularly the HMI output unit 71) outputs an information presentation request to the information presentation device 70b, and the notification is executed. After processing S106, the process proceeds to S108.

[0143] In S107, if there is no pedestrian crossing CW, the main unit 51 (particularly the driving planner 22) determines to make a temporary stop before the intersection IS. After the process of S107, the process proceeds to S108.

[0144] In S108, the main unit 51 (particularly the driving planner 22) decides to execute fine movement control. Based on this plan, the main unit 51 (particularly the motion controller 31) outputs a control request to the motion actuator 60, and the vehicle 1 executes fine movement control. In S109 after S108, the main unit 51 (particularly the driving planner 22) determines whether the occluded area OA has improved as a result of the fine movement control. If the answer is Yes, proceed to S112. If the answer is No, proceed to S110.

[0145] In S110, the main unit 51 (particularly the driving plan unit 22) determines to issue a notification to urge the occupant to monitor the surroundings. Based on this plan, the main unit 51 (particularly the HMI output unit 71) outputs an information presentation request to the information presentation device 70b, and the notification is executed. After processing S110, the process proceeds to S111.

[0146] In S111, the main unit 51 (particularly the driving plan unit 22) determines, based on the right of way, that the vehicle 1 will pass through the intersection IS in a conspicuous state. Based on this plan, the main unit 51 (particularly the motion control unit 31 and the HMI output unit 71) outputs a control request to the motion actuator 60 and the exterior information presentation device 70c, and the vehicle 1 passes through the intersection IS in a conspicuous state. The series of processes ends with S111.

[0147] In S112, when the blocked area OA where other road users may appear does not exist or has been resolved, the main unit 51 (particularly the driving plan unit 22) determines, based on the right of way, to pass through the intersection IS without making the vehicle 1 particularly conspicuous. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 passes through the intersection IS. The series of processes ends with S112.

[0148] According to the first embodiment described above, the occlusion area OA is recognized by the dynamic driving task plan, and the vehicle control mode for stopping temporarily is changed depending on the recognition result. That is, when passing through an intersection IS where a right or left turn is permitted, the vehicle 1 can make a more appropriate stopping motion depending on the occlusion area OA, thereby improving the appropriateness of the response to the occlusion area OA.

[0149] Furthermore, according to the first embodiment, when a blocked area OA where other road users may appear is recognized, vehicle control is executed in which the vehicle alternately stops and moves slightly in front of the intersection IS. That is, the blocked area OA may be improved during the slight movement control, and other road users in the blocked area OA may be made aware of the presence of the vehicle 1 during the slight movement control. Therefore, the appropriateness of the response to the blocked area OA is increased.

[0150] Furthermore, according to the first embodiment, when the vehicle 1 repeatedly stops and moves slightly, and the condition of the occupant of the vehicle 1 does not improve, a notification is issued to urge the occupant of the vehicle 1 to monitor the surroundings. By utilizing the occupant's monitoring of the surroundings, the appropriateness of responding to the occupant of the vehicle 1 is further improved.

[0151] Furthermore, according to the first embodiment, when a crosswalk CW exists between the current position of the vehicle 1 and the intersection IS, the vehicle 1 makes a temporary stop in front of the crosswalk CW, and accompanying the temporary stop, a notification is issued to encourage the occupant of the vehicle 1 to monitor the surroundings. By utilizing the occupant's monitoring of the surroundings, the appropriateness of responding to the blocked area OA is further improved, making it easier to avoid trouble with pedestrians crossing the crosswalk CW.

[0152] Furthermore, according to the first embodiment, the vehicle 1 is planned to be positioned laterally off-center with respect to the center of the lane so as to improve the extent of the blocked area OA rather than being positioned in the center of the lane. By setting a position with better visibility, it is possible to reduce the risk when passing through the intersection IS.

[0153] Furthermore, according to the first embodiment, when the vehicle 1 travels in an area where other road users may emerge from the shaded area OA, the exterior information presentation device 70c makes the presence of the vehicle 1 conspicuous. This makes it easier for other road users in the shaded area OA to notice the vehicle 1, further increasing the appropriateness of responding to the shaded area OA.

[0154] Second Embodiment As shown in Fig. 7, the second embodiment is a modification of the first embodiment. The second embodiment will be described, focusing on the differences from the first embodiment.

[0155] In the second embodiment, the prediction unit 21 distinguishes whether the object causing the occlusion area OA is a dynamic object DO or a static object SO. In other words, the prediction unit 21 recognizes the occlusion area OA by distinguishing between a dynamic occlusion area DOA and a static occlusion area SOA. The driving planner 22 plans the behavior of the vehicle 1 so as to change the mode of vehicle control, for example, regarding a temporary stop, depending on whether the occlusion area OA is a dynamic occlusion area DOA or a static occlusion area SOA.

[0156] Specifically, when the occlusion area OA is the dynamic occlusion area DOA, the driving plan unit 22 plans to temporarily stop and wait the vehicle 1 in front of the intersection IS. This waiting is performed in the hope that the dynamic object DO will move and the dynamic occlusion area DOA will disappear.

[0157] Then, the driving planner 22 determines whether the dynamic occlusion area DOA has improved after a preset time has elapsed. If the driving planner 22 determines that the dynamic occlusion area DOA has been maintained or worsened, the driving planner 22 plans to move forward at a slower speed for the vehicle 1. Conversely, if the driving planner 22 determines that the dynamic occlusion area DOA has improved, the driving planner 22 passes through the intersection IS at a normal speed.

[0158] On the other hand, when the shielded area OA is the static shielded area SOA, the operation planner 22 plans the fine movement control described in the first embodiment.

[0159] An example of a processing method for dealing with an intersection scenario in the vehicle 1 will now be described using the flowchart in Figure 7. The series of processes in S201 to S212 may be realized, for example, by the processor 51b of the main unit 51 executing a computer program stored in the memory 51a.

[0160] Steps S201 to S202 are the same as steps S101 to S102 in the first embodiment. However, in step S202, the dynamic shielding area DOA and the static shielding area SOA are recognized separately. In step S203 after step S202, the main unit 51 (particularly the operation planning unit 22) determines whether the shielding area OA is the dynamic shielding area DOA. If the answer is Yes, the process proceeds to step S204. If the answer is No, the process proceeds to step S208.

[0161] In S204, the main unit 51 (particularly the driving planner 22) plans to have the vehicle 1 wait by temporarily stopping just before the intersection IS. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 temporarily stops. In S205 after processing S204, the main unit 51 (particularly the driving planner 22) determines whether the dynamic occlusion area DOA has improved within a preset time period. If the answer is Yes in S205, the process proceeds to S206. If the answer is No, the process proceeds to S207. Note that if the dynamic occlusion area DOA has not improved and the preset time period has not elapsed, the main unit 51 continues waiting and executes the determination in S205 again.

[0162] In S206, the main unit 51 (particularly the driving planner 22) plans to pass through the intersection IS at a normal speed based on the right of way. The passing speed here may be set to a speed faster than the slow speed set in S207. Based on this plan, the main unit 51 (particularly the motion controller 31) outputs a control request to the motion actuator 60, and the vehicle 1 passes through the intersection IS. The series of processes ends with S206.

[0163] In S207, the main unit 51 (particularly the driving plan unit 22) plans to pass through the intersection IS at a slow speed based on the right-of-way. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 passes through the intersection IS. The series of processes ends with S207.

[0164] On the other hand, when the shielded area OA is the static shielded area SOA, steps S208 to S212 are the same as steps S108 to S112 in the first embodiment. The series of processes ends with step S211 or S212.

[0165] According to the second embodiment described above, the occlusion area OA is recognized as being distinguished between a dynamic occlusion area DOA formed by a dynamic object DO and a static occlusion area SOA formed by a static object SO. Then, the mode of vehicle control regarding the temporary stop is changed depending on whether the occlusion area OA is a dynamic occlusion area DOA or a static occlusion area SOA. Since the mode is changed depending on the ease of improving the occlusion area OA, the appropriateness of the response to the occlusion area OA is increased.

[0166] According to the second embodiment, the vehicle 1 temporarily stops in front of the intersection IS so that the dynamic occlusion area DOA improves as the dynamic object DO moves. If the dynamic occlusion area DOA does not improve for a predetermined time or longer, the vehicle 1 moves forward slowly. In a scenario where the occlusion area OA remains, the vehicle 1 moves slowly, thereby reducing the risk of passing through the intersection IS.

[0167] Furthermore, according to the second embodiment, when the shielded area OA is a dynamic shielded area DOA, the vehicle 1 waits by temporarily stopping in front of the intersection IS. When the shielded area OA is a static shielded area SOA, vehicle control is executed in which the vehicle alternately stops and moves slightly in front of the intersection IS. When the shielded area OA is of a nature that is easy to improve, waiting is selected, and when the shielded area OA is of a nature that is difficult to improve, slight movement is used to overcome the situation, thereby increasing the appropriateness of the response to the shielded area OA.

[0168] 8 and 9, the third embodiment is a modification of the first embodiment. The third embodiment will be described, focusing on the differences from the first embodiment.

[0169] In the third embodiment, the prediction unit 21 generates an environmental model 21a shown in Fig. 8. The environmental model 21a may include a three-dimensional model that represents, in a virtual three-dimensional space, the environment in which the vehicle 1 is currently located. The environmental model 21a includes the road on which the vehicle 1 is traveling, objects DO and SO present around the vehicle 1, as well as a sensor detection range M1 and an eye point M2.

[0170] The sensor detection range M1 can be determined by acquiring the mounting position of the external environment sensor 41 on the vehicle 1 and the specifications or status of the external environment sensor 41. The sensor detection range M1 is determined relative to the position and orientation of the vehicle 1. The sensor detection range M1 is preferably expressed as a three-dimensional range taking into account the longitudinal, lateral, and height directions of the vehicle 1, but may also be expressed as a two-dimensional range taking into account the longitudinal and lateral directions for faster calculation processing, etc. The eye point M2 is the position of the occupant's eyes as captured by a camera provided on the interior monitor 42a of the internal environment sensor 42. The occupant may be, for example, the driver.

[0171] The driving planner 22 calculates a sensor optimization position P1 and an occupant optimization position P2 with reference to the environmental model 21a. The sensor optimization position P1 is a position to which the vehicle 1 can move before passing through the intersection IS, and is a position where the range of the occupant area OA recognized by the perimeter monitoring sensor can be optimized compared to the current position of the vehicle 1. The optimization here may mean moving the vehicle 1 to a position less affected by the occupant area OA so that the vehicle 1 can pass through the intersection IS with less risk. The position less affected by the occupant area OA may be a position where the occupant area OA is reduced to a size where other road users are less likely to appear. The position less affected by the occupant area OA may be a position where the occupant area OA is formed farther away from the expected trajectory of the vehicle 1 when passing through the intersection IS, thereby reducing the risk of passing through. The sensor optimization position P1 is calculated with reference to the sensor detection range M1 and the positions of objects around the vehicle 1 placed in the environmental model 21a. The sensor optimization position P1 may be calculated, for example, by simulating the change in the range of the shielded area OA of the external environment recognized by the peripheral monitoring sensor when the position of the vehicle 1 is virtually moved in at least one of the vertical and horizontal directions.

[0172] The occupant optimization position P2 is a position to which the vehicle 1 can be moved before passing through the intersection IS, and is a position where the range of the occupant's ...

[0173] Then, the driving planner 22 determines the manner of movement to the sensor optimization position P1 and the occupant optimization position P2 according to the current automation level of the vehicle 1 managed by the mode manager 23. For example, when planning the behavior of the vehicle 1 in a mode corresponding to automation level 2, the driving planner 22 plans to move the vehicle 1 from its current position to the sensor optimization position P1 and temporarily stop there, and then move it to the occupant optimization position P2 and temporarily stop there. In other words, the difficulty in reducing the risk caused by the blocked area OA by the perimeter monitoring sensor is compensated for by the occupant monitoring the perimeter.

[0174] Here, if the shaded area OA is improved by moving to the sensor optimization position P1, the driving plan unit 22 may cancel the plan to move the vehicle 1 to the occupant optimization position P2. This is because the sensor data from the perimeter monitoring sensor at the sensor optimization position P1 ensures that there is little risk in the vehicle 1 passing through the intersection IS.

[0175] On the other hand, if the shaded area OA is not improved by moving to the sensor optimization position P1 and the vehicle 1 moves to the occupant optimization position P2, the driving planner 22 may plan to issue a notification to encourage the occupant of the vehicle 1 to monitor the surroundings. This notification may be similar to that in the first embodiment.

[0176] Furthermore, for example, when planning the behavior of the vehicle 1 in a mode corresponding to automation level 3 or higher, it is assumed that the occupants have no obligation to monitor the surroundings. For this reason, the driving planner 22 plans to move the vehicle 1 from its current position to the sensor optimization position P1 and temporarily stop it, but does not plan movement to the occupant optimization position P2 from the beginning, or omits the calculation of the occupant optimization position P2 altogether.

[0177] An example of a processing method for dealing with an intersection scenario in the vehicle 1 will now be described with reference to the flowchart in Fig. 9. The series of processes in S301 to S315 may be realized, for example, by the processor 51b of the main unit 51 executing a computer program stored in the memory 51a.

[0178] S301 is the same as S101 in the first embodiment. However, the environmental model 21a for identifying the intersection scenario includes the sensor detection range M1 and the eyepoint M2. In S302 after processing S301, the main unit 51 (particularly the driving planner 22) determines whether the current automation level of the vehicle 1 is 2. If the answer is Yes, proceed to S303. If the answer is No, proceed to S311. Note that, since it is difficult for the vehicle 1 to pass through the intersection IS based on the plan of the driving system 2 at automation level 1 or lower, if the answer is No in S301, the automation level is necessarily 3 or higher.

[0179] In S303, the main unit 51 (particularly the driving planner 22) calculates a sensor optimization position P1. In S304 after S303, the main unit 51 (particularly the driving planner 22) plans to move the vehicle 1 to the sensor optimization position P1 and temporarily stop the vehicle 1. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 temporarily stops at the sensor optimization position P1.

[0180] In S305 after the processing of S304, the main unit 51 (particularly the operation plan unit 22) determines whether the shielded area OA has been improved by moving to the sensor optimization position P1. If the result is Yes, proceed to S306. If the result is No, proceed to S307.

[0181] In S306, the main unit 51 (particularly the driving plan unit 22) omits moving the vehicle 1 to the occupant optimization position P2. After the processing of S306, the process proceeds to S310.

[0182] In S307, the main unit 51 (particularly the driving planner 22) calculates an occupant optimization position P2. In S308 after S307, the main unit 51 (particularly the driving planner 22) plans to move the vehicle 1 to the occupant optimization position P2 and temporarily stop the vehicle 1. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 temporarily stops at the occupant optimization position P2. Furthermore, in S309 after S308, the main unit 51 (particularly the motion control unit 31) determines to issue a notification to prompt the occupant to monitor the surroundings. Based on this plan, the main unit 51 (particularly the HMI output unit 71) outputs an information presentation request to the information presentation device 70b, and the notification is executed. After processing S309, the process proceeds to S310.

[0183] In S310, the main unit 51 (particularly the driving planner 22) plans to pass through the intersection IS at a slow speed based on the right-of-way. Based on this plan, the main unit 51 (particularly the motion controller 31) outputs a control request to the motion actuator 60, and the vehicle 1 passes through the intersection IS. The series of processes ends with S310.

[0184] When the automation level is 3 or higher, steps S311 to S313 are the same as steps S303 to S304 and S310. The series of processes ends with step S313.

[0185] According to the third embodiment described above, in a mode corresponding to automation level 2, the vehicle 1 moves to one of the following positions: a sensor optimization position P1 where the range of the shielded area OA recognized by the perimeter monitoring sensor can be optimized; and an occupant optimization position P2 where the range of the shielded area OA recognized by the occupant of the vehicle 1 can be optimized. After temporarily stopping at that position, the vehicle 1 moves to the other position and temporarily stops there again. By temporarily stopping at both positions, the risk to the shielded area OA can be minimized, thereby increasing the appropriateness of responding to the shielded area OA.

[0186] Furthermore, according to the third embodiment, in a mode corresponding to automation level 2, the vehicle 1 is planned to move to the sensor optimization position P1 and temporarily stop there, and then move to the occupant optimization position P2 and temporarily stop there. In this case, if the occupant optimization position P2 improves the occupant optimization area OA at the sensor optimization position P1, the movement to the occupant optimization position P2 is omitted. By omitting unnecessary behavior during risk reduction, the appropriateness of the response to the occupant optimization area OA is further improved.

[0187] Furthermore, according to the third embodiment, in a mode corresponding to automation level 3 or higher, the vehicle 1 moves to and temporarily stops at the sensor optimization position P1, which is the position of the vehicle 1. At level 3 or higher, where the occupant is not required to monitor the surroundings, not requiring the occupant to monitor the surroundings further enhances the appropriateness of responding to the blocked area OA.

[0188] Fourth Embodiment As shown in Fig. 10, the fourth embodiment is a modification of the first embodiment. The fourth embodiment will be described, focusing on the differences from the first embodiment.

[0189] In the fourth embodiment, the prediction unit 21 acquires acoustic data as sensor data detected by an acoustic sensor 41a, which serves as a temporal information sensor among the external environment sensors 41. The acoustic sensor 41a includes a microphone that detects sound or air vibrations (hereinafter collectively referred to as "sound") and converts them into an electrical signal, and an AD conversion circuit that generates a sound signal as digitalized acoustic data from the electrical signal (analog signal). The microphone may be a condenser microphone, particularly a MEMS microphone. MEMS stands for Micro Electro Mechanical Systems. The sound signal may correspond to the acoustic data.

[0190] The prediction unit 21 identifies the shaded area OA using sensor data from the spatial information sensor, and then uses acoustic data to execute a shaded area prediction F1, which predicts the possibility of another road user being present within the shaded area OA and their behavior. It is usually difficult to accurately identify the location where the sound originates using only acoustic data as temporal information. Therefore, the prediction unit 21 estimates the possibility of another road user being present within the shaded area OA by combining the sensor data from the spatial information sensor.

[0191] The prediction unit 21 analyzes the sound data using a learning model that uses, for example, a neural network, etc. This allows the sound to be classified into siren sounds emitted by emergency vehicles (e.g., ambulances, fire engines, and police vehicles), horn sounds, engine sounds, driving sounds, etc. emitted by other vehicles.

[0192] For example, when the prediction unit 21 recognizes the siren sound of an ambulance, it determines whether or not the ambulance, which is the source of the siren sound, is present in an area that can be recognized by the spatial information sensor other than the blocked area OA. If the presence of an ambulance is recognized in an area that can be recognized by the spatial information sensor, the prediction unit 21 determines that there is a low possibility that the ambulance is present within the blocked area OA. If the presence of an ambulance is not recognized in an area that can be recognized by the spatial information sensor, the prediction unit 21 determines that there is a high possibility that the ambulance is present within the blocked area OA.

[0193] If the prediction unit 21 does not recognize any sound that may be emitted by another road user, it reserves the right to decide whether or not another road user is present in the shielded area OA. This is because there remain the following possibilities: there is no other road user in the shielded area OA; there is a possibility that another road user is present in the shielded area OA but is not emitting any recognizable sound; or the sound is not being detected correctly due to a malfunction of the acoustic sensor 41 a.

[0194] The prediction unit 21 predicts the behavior of other road users who may be present within the shielded area OA. This behavior may be predicted within a reasonably foreseeable range. The behavior of other road users who may be present within the shielded area OA may be predicted on the assumption that they will abide by traffic rules. On the other hand, the behavior of other road users who may be present within the shielded area OA may be predicted taking into consideration that they may violate traffic rules. For example, the prediction unit 21 may refer to the legal speed limit applied to the shielded area OA and predict that other road users may travel at a predetermined speed (e.g., approximately 10 km / h) above the legal speed limit. A speed that exceeds the legal speed limit by a predetermined speed is hereinafter referred to as the upper speed limit. The upper speed limit may correspond to a reasonably foreseeable maximum assumed longitudinal velocity other road users could exhibit.

[0195] The driving planner 22 executes the plan F2 based on the assumption F1 within the shielded area. For example, on the assumption that another road user who may be present within the shielded area OA will emerge from the shielded area OA at the upper limit speed predicted by the prediction unit 21, the driving planner 22 may plan to drive the vehicle 1 at a speed that will not cause a collision with the other road user, or may plan to temporarily stop the vehicle 1 before the intersection IS to avoid a collision with the other road user.

[0196] According to the fourth embodiment described above, the perimeter monitoring sensor includes a spatial information sensor capable of monitoring using spatial information and an acoustic sensor 41a as a temporal information sensor capable of monitoring using temporal information. The possibility that another road user is present in the blocked area OA recognized based on the spatial information sensor is determined based on the temporal information sensor. The behavior of the other road user in the blocked area OA is predicted within a reasonably foreseeable range. By using a prediction within a reasonably foreseeable range within the blocked area OA, the appropriateness of the dynamic driving task's response to the blocked area OA is further enhanced.

[0197] Fifth Embodiment As shown in Fig. 11, the fifth embodiment is a modification of the first embodiment. The fifth embodiment will be described, focusing on the differences from the first embodiment.

[0198] In the fifth embodiment, the recording device 55 sequentially stores the driving route of the vehicle 1 as event data related to the driving task of the vehicle 1 in the storage medium 55c. Furthermore, the recording device 55 sequentially stores information about the obstructed area OA recognized by the prediction unit 21 along the route in the storage medium 55c. The information about the obstructed area OA may include at least one of the position and range of the obstructed area OA. The information about the obstructed area OA may include information distinguishing whether the obstructed area OA is a dynamic obstructed area (DOA) or a static obstructed area (SOA). The information about the obstructed area OA may include information distinguishing whether the obstructed area OA is likely to be accessed by other road users.

[0199] In the fifth embodiment, the driving planner 22 refers to the past driving route stored in the storage medium 55c and information related to the blocked area OA on the route, and plans the behavior of the vehicle 1. Specifically, the driving planner 22 selects whether to plan vehicle control in a cautious manner or in a non-cautious manner.

[0200] As a premise, the driving planner 22 selects the cautious mode if it recognizes an obstructed area OA where other road users may appear during the current driving. However, even if it does not recognize an obstructed area OA where other road users may appear during the current driving, the driving planner 22 selects the cautious mode if the current driving route is a route that has been driven in the past and an obstructed area OA where other road users may appear has been recognized in the past on that route.

[0201] An example of a processing method for dealing with an intersection scenario in the vehicle 1 will now be described with reference to the flowchart in Fig. 11. The series of processes in S401 to S410 may be realized, for example, by the processor 51b of the main unit 51 executing a computer program stored in the memory 51a.

[0202] Steps S401 to S402 are the same as steps S101 to S102 in the first embodiment. In step S403 after step S402, the driving planner 22 acquires information on the past driving route and the shaded area OA from the storage medium 55c. In step S404 after step S403, the driving planner 22 determines whether there is a shaded area OA in which another road user may appear during the current driving. If the answer is Yes, the process proceeds to step S407. If the answer is No, the process proceeds to step S405.

[0203] In S405, the driving plan unit 22 refers to the data acquired in S403 and determines whether the current driving route is a route that the driver has traveled in the past. If the answer is Yes, the process proceeds to S406. If the answer is No, the process proceeds to S409.

[0204] In S406, the driving plan unit 22 determines whether or not an obstructed area OA where other road users may appear was recognized during the driving on the previous route identified in S405. If the answer is Yes, the process proceeds to S407. If the answer is No, the process proceeds to S409.

[0205] S407 to S408 are processes performed when the driving planner 22 selects the cautious mode. In S407, the driving planner 22 plans to have the vehicle 1 make multiple temporary stops before the intersection IS. These multiple temporary stops may be the fine movement control of the first embodiment. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 makes multiple temporary stops before the intersection IS. S408 after S407 is the same as S207 in the second embodiment. The series of processes ends with S408.

[0206] S409 to S410 are processes performed when the driving planner 22 selects an uncautious mode. In S409, the driving planner 22 plans to have the vehicle 1 make a single temporary stop before the intersection IS. Based on this plan, the main unit 51 (particularly the motion control unit 31) outputs a control request to the motion actuator 60, and the vehicle 1 makes a single temporary stop before the intersection IS. S410 after S409 is the same as S206 in the second embodiment. The series of processes ends with S410.

[0207] According to the fifth embodiment described above, the storage medium 55c stores information about routes traveled by the vehicle 1 in the past and about the shaded areas OA on those routes. Even if the shaded areas OA where other road users may appear are not recognized during the current travel, if the current travel route is a route traveled in the past and shaded areas OA where other road users may appear have been recognized on the route in the past, vehicle control regarding stopping times will be more cautious than when the shaded areas OA are not recognized. By using vehicle control that reflects past data, the appropriateness of responses to the shaded areas OA is further improved.

[0208] Sixth Embodiment As shown in Fig. 12, the sixth embodiment is a modification of the first embodiment. The sixth embodiment will be described, focusing on the differences from the first embodiment.

[0209] In the sixth embodiment, the map DB 44 includes information on road structures. The information on road structures may be aggregated in the form of road structure data, or may be stored in a dispersed manner in road data, signage data, etc. The information on road structures may include the gradient of the road, the shape of the curve, etc. The information on road structures may include the shape of the median strip of the road, the presence and shape of roadside trees in the median strip or roadside strip, the presence and shape of buildings adjacent to the road, etc. The road structure here may correspond to a static object SO.

[0210] The prediction unit 21 of the sixth embodiment acquires information on the road structure of the road ahead of the vehicle 1 from the map DB 44. Based on the information on the road structure, the prediction unit 21 estimates the possibility of the occurrence of a static occlusion area SOA formed by a static object SO on the road ahead of the vehicle 1.

[0211] For example, the prediction unit 21 may estimate that a static occlusion area SOA may occur ahead of the vehicle 1 at a point where the gradient of the road changes from ascending to descending (i.e., the top of a slope). The prediction unit 21 may also estimate that a static occlusion area SOA may occur due to a building adjacent to an intersection IS ahead of the vehicle 1.

[0212] The operation planning unit 22 determines whether or not preparation for the static shielding area SOA is necessary, depending on the occurrence possibility of the static shielding area SOA estimated by the prediction unit 21 and the estimated range or estimated scale of the static shielding area SOA. If preparation is necessary, the operation planning unit 22 plans preparation for the static shielding area SOA.

[0213] The preparation here may be, for example, stopping acceleration of the vehicle 1. The preparation may be, for example, setting an upper limit on the set speed of the vehicle 1. The preparation may be one aspect of a restriction on a driving function.

[0214] Then, based on the plan including the preparation, the motion control unit 31 outputs a control request to the motion actuator 60, and the vehicle 1 travels to a position where the static occlusion area SOA is estimated to occur.

[0215] At this time, the operation planner 22 may plan to issue a notification regarding preparation. The notification regarding preparation may be issued by at least one of the meter display 70b1, the CID 70b2, and the HUD 70b3 via the HMI output unit 71, or may be issued in combination with an audio notification using a speaker. The notification regarding preparation may be a notification indicating a possibility of occurrence of a static occlusion area SOA ahead of the vehicle 1, or may be a notification indicating that the vehicle 1 is in a state of preparation for the possibility of occurrence.

[0216] When it is confirmed that the estimated static occlusion area SOA has actually occurred, the operation planning unit 22 plans careful control of the vehicle 1. In the careful control plan, the thresholds are changed so that deceleration and temporary stop are more likely to occur compared to the deceleration thresholds or temporary stop thresholds in normal control when no occlusion area OA has occurred.

[0217] The thresholds for switching between the careful control and the normal control may be collision risk thresholds used in the risk confirmation function. For example, the deceleration threshold or the stop threshold may be a safety distance in the RSS model. In this case, deceleration and stop as actions given as a result of determining the threshold may correspond to appropriate responses.

[0218] Furthermore, when a dynamic occlusion area DOA occurs in addition to a static occlusion area SOA, the operation planner 22 may plan even more cautious control than the cautious control. That is, in the plan for the even more cautious control, the thresholds are changed so that deceleration and temporary stop are more likely to occur compared to the deceleration thresholds or temporary stop thresholds in the cautious control. Note that the above-mentioned controls may be referred to as a normal control mode, a cautious control mode, and an even more cautious control mode.

[0219] Furthermore, when a dynamic obstruction area DOA occurs in addition to a static obstruction area SOA, the driving planner 22 plans to issue a notification to the occupants of the vehicle 1. The notification here may be a notification that prompts the occupants of the vehicle 1 to monitor their surroundings.

[0220] 12, an example of a processing method in the vehicle 1 will be described. The series of processes in S501 to S509 may be realized, for example, by the processor 51b of the main unit 51 executing a computer program stored in the memory 51a, and simultaneously by the processor 53b of the risk confirmation unit 53 executing a computer program stored in the memory 53a.

[0221] In S501, the driving planning unit 22 identifies an intersection IS ahead of the vehicle 1. In S502 after S501, the driving planning unit 22 acquires information on the road structure around the intersection IS identified in S501 from the map DB 44. In S503 after S502, the driving planning unit 22 estimates the possibility of occurrence of a static obstruction area SOA based on the information on the road structure.

[0222] In S504 after the process of S503, the operation planner 22 determines whether the occurrence possibility of the static shielding area SOA is equal to or higher than a level that requires preparation for the static shielding area SOA. If the determination is Yes, the process proceeds to S505. If the determination is No, the process proceeds to S509.

[0223] In S505, the driving planner 22 plans preparations for the static obstruction area SOA estimated in S503. In S506 after the vehicle 1 approaches the intersection IS according to the plan, the driving planner 22 determines whether the static obstruction area SOA estimated in S503 has actually occurred. If the determination is Yes, the process proceeds to S507. If the determination is No, the process proceeds to S509.

[0224] In S507, the operation planning unit 22 plans careful control. Based on this plan, the motion control unit 31 outputs a control request to the motion actuator 60. In S508 after S507, the operation planning unit 22 plans a notification to the occupants. Based on this plan, the HMI output unit 71 outputs an information presentation request to the information presentation device 70b, and the notification is executed.

[0225] On the other hand, in S509, preparation and careful control for the static occlusion area SOA are not planned, and the operation planner 22 continues planning in the normal control mode. A series of processes ends with S508 and S509.

[0226] According to the first embodiment described above, the probability of occurrence of a static occlusion area SOA formed by a static object SO on a road ahead of the vehicle 1 is estimated based on road structure information included in map information. Then, preparations for the static occlusion area SOA are planned based on the occurrence probability. Since preparations can be made based on the occurrence probability before the occlusion area OA is actually discovered, the appropriateness of responses to the occlusion area OA is increased.

[0227] Seventh Embodiment As shown in Fig. 13, the seventh embodiment is a modification of the first embodiment. The seventh embodiment will be described, focusing on the differences from the first embodiment.

[0228] The environment recognition unit 11 of the seventh embodiment is capable of identifying the source of the horn sound detected by the acoustic sensor 41a serving as the external environment sensor 41. Specifically, the environment recognition unit 11 can identify the source of the horn sound by combining sensor data from the acoustic sensor 41a with sensor data from other external environment sensors 41, such as a camera. The source of the horn sound is usually another vehicle.

[0229] In the seventh embodiment, when a horn sound is detected while the vehicle 1 is entering an intersection IS, the driving planner 22 plans to temporarily stop the vehicle 1 and temporarily stops the vehicle 1. Then, the driving planner 22 checks the separation behavior of the other vehicle that emitted the horn sound with respect to the vehicle 1. Here, the separation behavior may be that the other vehicle that emitted the horn sound passed through the intersection IS before the vehicle 1 and moved out of the intersection IS.

[0230] After confirming that the other vehicle has moved away, the driving planner 22 plans to resume driving the vehicle 1. This makes it possible to avoid conflict with the other vehicle that has honked its horn.

[0231] 12, an example of a processing method in the vehicle 1 will be described. The series of processes in S601 to S608 may be realized, for example, by the processor 51b of the main unit 51 executing a computer program stored in the memory 51a.

[0232] Steps S601 and S602 are the same as steps S101 and S102 in the first embodiment. In step S603, the environment recognition unit 11 determines whether a horn sound has been generated. If the determination is Yes, the process proceeds to step S604. If the determination is No, the process proceeds to step S608.

[0233] In S604, the environment recognition unit 11 identifies the source of the horn sound. If the source of the horn sound cannot be identified and an obstructed area OA exists at the intersection IS, the environment recognition unit 11 may estimate that there is a possibility that another vehicle, which is the source of the horn sound, is present in the obstructed area OA, and the process may proceed to S608.

[0234] In S605 after S604, the driving planner 22 plans a temporary stop of the vehicle 1. Based on this plan, the motion controller 31 outputs a control request to the motion actuator 60.

[0235] In S606 after S605, the driving planner 22 determines whether the other vehicle that emitted the horn has passed the intersection IS and moved away from the vehicle 1. If the determination is Yes, the process proceeds to S607. If the determination is No, the process returns to S605, the temporary stop continues, and the determination in S606 is executed again after a predetermined time.

[0236] In S607, the driving planner 22 plans the resumption of driving of the vehicle 1. Based on this plan, the motion controller 31 outputs a control request to the motion actuator 60. With S607, the processing for one point ends.

[0237] In addition, in S608 where the generation of the horn sound is not confirmed, a response to the blocked area OA is executed. Specifically, the processes of S103 to S112 may be executed.

[0238] According to the seventh embodiment described above, the external environment sensor 41 serving as a perimeter monitoring sensor includes an acoustic sensor 41a that detects sound. When a horn sound is detected based on the acoustic sensor 41a, the behavior of the vehicle 1 is planned to be temporarily stopped, and after checking that the other vehicle that emitted the horn has moved away from the vehicle 1 while the vehicle 1 is temporarily stopped, the vehicle 1 is planned to resume traveling. By avoiding a conflict with the other vehicle that emitted the horn, the vehicle 1 is prevented from getting into trouble.

[0239] (Other Embodiments) Although multiple embodiments have been described above, the present disclosure should not be construed as being limited to those embodiments, and can be applied to various embodiments and combinations within the scope that does not deviate from the gist of the present disclosure.

[0240] In another embodiment, the area where a right or left turn is permitted may be other than an intersection IS. For example, the area where a right or left turn is permitted may be a connecting portion to a road at the entrance of a facility such as a roadside store.

[0241] In another embodiment, the size of the obscured area OA in which other road users may appear may be defined differently depending on the type of other road users that are assumed, for example, the minimum size of the obscured area OA may be defined to be smaller if the other road users are pedestrians than if the other road users are vehicles.

[0242] As another embodiment related to the third embodiment, the driving planner 22 may plan to move the vehicle 1 from the current position to the occupant optimization position P2, temporarily stop the vehicle 1, and then move the vehicle 1 to the sensor optimization position P1, temporarily stop the vehicle 1. The position to which the vehicle 1 moves first, either the sensor optimization position P1 or the occupant optimization position P2, may be closer to the current position.

[0243] As another embodiment related to the third embodiment, when the automation level is 3 or higher, the driving planner 22 may move the vehicle 1 to the occupant optimization position P2 in addition to the sensor optimization position P1. When there is a risk in passing through the intersection IS, the appropriateness of the response to the blocked area OA can be further improved by encouraging the occupant to monitor the surroundings.

[0244] As another embodiment related to the third embodiment, if the shielded area OA disappears after the vehicle 1 has moved to the sensor optimization position P1 through the offset control, the driving planner 22 may plan for the vehicle 1 to pass through the intersection IS while continuing the offset control. Passing here includes making the vehicle 1 turn right or left at the intersection IS. If the shielded area OA does not disappear after the vehicle 1 has moved to the sensor optimization position P1 through the offset control, the driving planner 22 may plan for the vehicle 1 to pass through the intersection IS after ending the offset control.

[0245] In another embodiment, when the vehicle 1 is traveling in a quiet environment (e.g., a residential area), information indicating non-detection of sound, i.e., no sound was detected, among the detected sound information of the acoustic sensor 41a may be used to plan the behavior of the vehicle 1. For example, when no information indicating non-detection of sound is acquired, the prediction unit 21 may predict that no dynamic object DO is present in the obstructed area OA, and this prediction may be used by the driving planner 22.

[0246] In other embodiments, the processing system 50 may have a configuration as shown in Figures 14 and 15. For example, Figure 14 shows a configuration including multiple domain controllers 451 to 454. Each of the domain controllers 451 to 454 may have a hardware configuration including a processor and a memory, similar to the processing system 50 or ECU of the first embodiment.

[0247] The ADAS domain controller 451 aggregates functions related to ADAS (Advanced Driver-Assistance Systems). The ADAS domain controller 451 may comprehensively realize a portion of the recognition function, a portion of the judgment function, and a portion of the control function. The portion of the recognition function realized by the ADAS domain controller 451 may be, for example, a function corresponding to the fusion of information detected by the multiple sensors 40 in the detection unit 10 of the first embodiment, or a simplified function thereof. The portion of the judgment function realized by the ADAS domain controller 451 may be, for example, a function corresponding to the prediction unit 21 and the driving planner 22 of the first embodiment, or a simplified function thereof. The portion of the control function realized by the ADAS domain controller 451 may be, for example, a function corresponding to the motion control unit 31 of the first embodiment, that generates request information for the motion actuator 60.

[0248] The powertrain domain controller 452 aggregates functions related to the control of the powertrain. The powertrain domain controller 452 may compositely realize at least a part of the recognition function and at least a part of the control function. A part of the recognition function realized by the powertrain domain controller 452 may be, for example, a function corresponding to the internal recognition unit 13 in the first embodiment, which recognizes the driver's operation state with respect to the motion actuator 60. A part of the control function realized by the powertrain domain controller 452 may be, for example, a function corresponding to the motion control unit 31 in the first embodiment, which controls the motion actuator 60.

[0249] The cockpit domain controller 453 aggregates functions related to the cockpit. The cockpit domain controller 453 may compositely realize at least a part of the recognition function and at least a part of the control function. A part of the recognition function realized by the cockpit domain controller 453 may be, for example, a function of recognizing the switch state of the HMI device 70, which is included in the internal recognition unit 13 of the first embodiment. A part of the control function realized by the cockpit domain controller 453 may be, for example, a function corresponding to the HMI output unit 71 of the first embodiment.

[0250] The connectivity domain controller 454 aggregates connectivity-related functions. The connectivity domain controller 454 may comprehensively realize at least a part of the recognition function. Part of the recognition function realized by the connectivity domain controller 454 may be a function to organize and convert the global position data of the vehicle, V2X information, etc. acquired from the communication system 43 into a format usable by the ADAS domain controller 451 and the cockpit domain controller 453, for example.

[0251] 15 employs a configuration including an integrated ECU 551 and multiple zone ECUs 551a-d. In this configuration, the multiple zone ECUs 551a-d control devices, modules, units, equipment, etc. that are located in specific assigned zones of the vehicle 1. The multiple zone ECUs 551a-d may be hardware configurations that include a processor and a memory, similar to the processing system 50 or ECU of the first embodiment.

[0252] For example, an external environment sensor 41 such as a camera arranged in the front of the vehicle 1, and an information presentation device 70b such as a CID arranged in the cockpit, are controlled by a zone ECU 551a or 551b arranged in the front of the vehicle 1. For example, an external environment sensor 41 such as a millimeter wave radar arranged in the rear of the vehicle 1 is controlled by a zone ECU 551c or 551d arranged in the rear of the vehicle 1.

[0253] The integrated ECU 551 collects detection information and the like from each of the zone ECUs 551a to 551d, and controls each of the zone ECUs 551a to 551d in an integrated manner the driving system 2. The integrated ECU 551 may implement almost all of the planning function and risk confirmation function.

[0254] In another embodiment, the vehicle 1 equipped with the driving system 2 may be a right-hand drive vehicle or a left-hand drive vehicle. Furthermore, the traffic environment in which the vehicle 1 travels may be a traffic environment where traffic is assumed to be on the left side of the road, or a traffic environment where traffic is assumed to be on the right side of the road. The driving system 2 according to the present disclosure may be optimized as appropriate, taking into consideration the road traffic laws, data protection laws, customs, and legal systems and practices of police investigations, prosecutions, criminal proceedings, and civil proceedings in each country and region.

[0255] The controller and methods described herein may be implemented by a special-purpose computer comprising a processor programmed to perform one or more functions embodied in a computer program. Alternatively, the apparatus and methods described herein may be implemented by special-purpose hardware logic circuitry. Alternatively, the apparatus and methods described herein may be implemented by one or more special-purpose computers comprising a processor executing a computer program in combination with one or more hardware logic circuits. Furthermore, the computer program may be stored as instructions executed by a computer on a computer-readable non-transitory storage medium.

[0256] (Disclosure of Technical Ideas) This specification discloses multiple technical ideas described in the following multiple clauses. Some clauses may be described in a multiple dependent form, where the subsequent clause alternatively cites the preceding clause. These multiple dependent clauses define multiple technical ideas.

[0257] <Technical Idea 1> A driving system comprising at least one processor (51b) and configured to be capable of executing a dynamic driving task for a vehicle (1), wherein the at least one processor is configured to: recognize an obstructed area (OA) based on sensor data from a surrounding monitoring sensor (41) mounted on the vehicle and monitoring the periphery of the vehicle when the vehicle is scheduled to pass through an area (IS) where a right or left turn is possible; and plan the behavior of the vehicle so as to change the mode of vehicle control regarding a temporary stop in accordance with the result of the recognition of the obstructed area.

[0258] <Technical Idea 2> The driving system according to Technical Idea 1, wherein the at least one processor, in planning the behavior of the vehicle, plans to execute the vehicle control that alternately repeats the temporary stop and slight movement in front of the area where a right or left turn is possible when the blocked area where another road user may appear is recognized.

[0259] <Technical Idea 3> The driving system according to Technical Idea 2, wherein the at least one processor further plans to issue a notification to occupants of the vehicle to urge them to monitor their surroundings when the occupant of the vehicle repeatedly stops and moves slightly, and the occupant of the vehicle does not improve the occupant of the occupant of the vehicle as a result of the occupant of the vehicle alternating between stopping and moving slightly.

[0260] <Technical Idea 4> A driving system according to any one of Technical Ideas 1 to 3, wherein, when a crosswalk (CW) exists between the current position of the vehicle and the area where a right or left turn is possible, the at least one processor, in planning the behavior of the vehicle, further plans to make the vehicle temporarily stop in front of the crosswalk and to issue a notification in conjunction with the temporary stop that encourages the occupants of the vehicle to monitor their surroundings.

[0261] <Technical Idea 5> The driving system described in any one of Technical Ideas 1 to 4, wherein the at least one processor, in recognizing the occluded area, distinguishes between a dynamic occluded area (DOA) formed by a dynamic object (DO) and a static occluded area (SOA) formed by a static object (SO), and, in planning the behavior of the vehicle, plans the behavior of the vehicle so as to change the mode of vehicle control regarding a temporary stop depending on whether the occluded area is the dynamic occluded area or the static occluded area.

[0262] <Technical Idea 6> The driving system according to Technical Idea 5, wherein the at least one processor, in planning the behavior of the vehicle, plans to have the vehicle wait by temporarily stopping in front of the area where a right or left turn is possible so that the dynamic occlusion area improves as the dynamic object moves, and if the dynamic occlusion area does not improve for a preset time or more, plans to have the vehicle move forward at a slower speed.

[0263] <Technical Idea 7> The driving system according to Technical Idea 5 or 6, wherein the at least one processor, in planning the behavior of the vehicle, plans to have the vehicle wait by temporarily stopping in front of the area where a right or left turn is possible when the blocked area is the dynamic blocked area, and plans to execute the vehicle control that alternately repeats the temporary stop and slight movement in front of the area where a right or left turn is possible when the blocked area is the static blocked area.

[0264] <Technical Idea 8> The driving system described in Technical Idea 1, wherein the at least one processor, in planning the behavior of the vehicle, estimates the possibility of a static occlusion area (SOA) formed by a static object (SO) occurring on the road ahead of the vehicle based on road structure information included in map information, and plans preparations for the static occlusion area based on the possibility of occurrence.

[0265] <Technical Idea 9> A driving system described in any one of Technical Ideas 1 to 8, wherein the at least one processor, in planning the behavior of the vehicle, plans a positioning of the vehicle that is laterally eccentric relative to the center of the lane so as to improve the coverage of the occlusion area rather than the vehicle being located in the center of the lane.

[0266] <Technical Idea 10> A driving system according to Technical Idea 1, configured to be able to execute the dynamic driving task in a mode corresponding to automation level 2, wherein the at least one processor, when planning the behavior of the vehicle in the mode corresponding to automation level 2, plans to move the vehicle to one of a sensor optimization position (P1) where the range of the occupant area recognized by the surrounding monitoring sensor can be optimized, and an occupant optimization position (P2) where the range of the occupant area recognized by the vehicle can be optimized, temporarily stop the vehicle, and then move the vehicle to the other position and temporarily stop the vehicle.

[0267] <Technical Idea 11> The at least one processor, when planning the behavior of the vehicle in a mode corresponding to automation level 2, decides to omit moving to the occupant optimization position if the occupancy optimization position improves and the occupant optimization position moves to the sensor optimization position and stops temporarily, in the driving system described in Technical Idea 10.

[0268] <Technical Idea 12> A driving system described in any one of Technical Ideas 1, 10 and 11, configured to be able to execute the dynamic driving task in a mode corresponding to automation level 3 or higher, wherein the at least one processor, when planning the behavior of the vehicle in the mode corresponding to automation level 3 or higher, plans to move the vehicle to a sensor optimization position where the position of the vehicle can be optimized to optimize the range of the occluded area recognized through the surrounding monitoring sensor, and to stop the vehicle.

[0269] <Technical Idea 13> The driving system described in any one of Technical Ideas 1 to 12, wherein the periphery monitoring sensor includes a spatial information sensor capable of monitoring using spatial information and a temporal information sensor (41 a) capable of monitoring using temporal information, and the at least one processor is further configured to, in recognizing the obstructed area, determine, based on the temporal information sensor, the possibility that other road users are present in the obstructed area recognized based on the spatial information sensor, and predict the behavior of the other road users in the obstructed area within a reasonably foreseeable range.

[0270] <Technical Idea 14> The driving system according to any one of Technical Ideas 1 to 13, further comprising a storage medium (55c) that stores information about a route that the vehicle has previously traveled and about the obstructed area on the route, wherein the at least one processor plans vehicle control regarding the temporary stop in a more cautious manner when planning the behavior of the vehicle, even if the obstructed area where other road users may appear has not been recognized in the current driving, if the current driving route is the route that has been previously traveled and the obstructed area where other road users may appear has been recognized in the past on the route, than if the obstructed area had not been recognized.

[0271] <Technical Idea 15> The driving system described in any one of Technical Ideas 1 to 14, wherein the at least one processor, in planning the behavior of the vehicle, plans to make the presence of the vehicle conspicuous using an external information presentation device (70c) when traveling in an area where other road users may emerge from the obstructed area.

[0272] <Technical Idea 16> The driving system described in any one of Technical Ideas 1 to 15, wherein the perimeter monitoring sensor includes an acoustic sensor (41 a) that detects sound, and the at least one processor, in planning the behavior of the vehicle, plans to temporarily stop the vehicle when a horn sound is detected based on the acoustic sensor, and to resume driving of the vehicle after confirming, while the vehicle is temporarily stopped, that the other vehicle that emitted the horn sound is moving away from the vehicle.

[0273] <Technical Idea 17> A driving system comprising at least one processor (51b) and configured to be capable of executing a dynamic driving task for a vehicle (1), wherein the at least one processor is configured to: recognize an obstructed area (OA) based on sensor data from a surrounding monitoring sensor (41) mounted on the vehicle and monitoring the periphery of the vehicle when the vehicle is scheduled to pass through an area (IS) where a right or left turn is possible; and plan a notification in the vehicle according to the recognition result of the obstructed area.

[0274] According to Technical Idea 17, by providing an appropriate notification in accordance with the recognition result of the occluded area, the appropriateness of the response to the occluded area is increased.

[0275] <Technical Idea 18> A driving system including at least one processor (51b) and configured to be capable of executing a dynamic driving task for a vehicle (1), wherein the at least one processor is configured to: recognize an occluded area (OA) by distinguishing between a dynamic occluded area (DOA) formed by a dynamic object (DO) and a static occluded area (SOA) formed by a static object (SO) based on sensor data from a surrounding monitoring sensor (41) mounted on the vehicle and monitoring the surroundings of the vehicle; and plan the behavior of the vehicle so as to change the mode of vehicle control according to the recognition result of the occluded area.

[0276] According to Technical Concept 18, by implementing vehicle control according to the distinction between shaded areas, the appropriateness of dealing with shaded areas is increased.

[0277] <Technical Idea 19> A driving system comprising at least one processor (51b) and configured to be capable of executing a dynamic driving task of a vehicle (1), wherein the at least one processor is configured to: recognize an occluded area (OA) based on sensor data from a periphery monitoring sensor (41) mounted on the vehicle and monitoring the periphery of the vehicle; calculate a sensor optimization position (P1) of the vehicle that can optimize the range of the occluded area recognized through the periphery monitoring sensor, and an occupant optimization position (P2) that can optimize the range of the occupant of the vehicle; and plan movement of the vehicle to one of the sensor optimization position and the occupant optimization position.

[0278] According to Technical Idea 19, the appropriateness of response to occupant obstruction areas is improved by calculating the sensor optimum position and the occupant optimum position and appropriately using them to execute the dynamic driving task.

Claims

1. A driving system having at least one processor (51b) and configured to be capable of executing a dynamic driving task for a vehicle (1), wherein the at least one processor is configured to: recognize an obstructed area (OA) based on sensor data from a surrounding monitoring sensor (41) mounted on the vehicle and monitoring the vehicle's surroundings when the vehicle is scheduled to pass through an area (IS) where a right or left turn is possible; and plan the vehicle's behavior so as to change the vehicle control mode regarding a temporary stop in accordance with the result of the obstructed area recognition.

2. The driving system of claim 1, wherein the at least one processor, in planning the vehicle behavior, plans to execute the vehicle control that alternates between stopping temporarily and moving slightly in front of the area where a right or left turn is possible when the blocked area where another road user may appear is recognized.

3. The driving system of claim 2, wherein the at least one processor further plans to issue a notification to an occupant of the vehicle urging them to monitor their surroundings if the occupant of the vehicle does not improve as a result of the vehicle repeatedly performing the alternating temporary stops and slight movements.

4. The driving system of claim 1, wherein, when a crosswalk (CW) exists between the current position of the vehicle and the area where a right or left turn is permitted, the at least one processor, in planning the behavior of the vehicle, further plans to execute the temporary stop in front of the crosswalk and to issue an alert to encourage the occupants of the vehicle to monitor their surroundings in conjunction with the temporary stop.

5. The driving system of claim 1, wherein the at least one processor, in recognizing the occluded area, distinguishes between a dynamic occluded area (DOA) formed by a dynamic object (DO) and a static occluded area (SOA) formed by a static object (SO), and, in planning the vehicle behavior, plans the vehicle behavior so as to change the manner of vehicle control regarding a temporary stop depending on whether the occluded area is the dynamic occluded area or the static occluded area.

6. The driving system described in claim 5, wherein the at least one processor, in planning the behavior of the vehicle, plans to have the vehicle wait by temporarily stopping in front of the area where a right or left turn is possible so that the dynamic occlusion area improves as the dynamic object moves, and plans to have the vehicle move forward at a slower pace if the dynamic occlusion area does not improve for a predetermined time or more.

7. The driving system of claim 5, wherein the at least one processor, in planning the vehicle behavior, plans to have the vehicle wait by temporarily stopping in front of the area where a right or left turn is possible when the blocked area is the dynamic blocked area, and plans to execute the vehicle control that alternates between temporarily stopping and slowly moving in front of the area where a right or left turn is possible when the blocked area is the static blocked area.

8. The driving system of claim 1, wherein the at least one processor, in planning the vehicle's behavior, estimates the possibility of a static occlusion area (SOA) formed by a static object (SO) occurring on the road ahead of the vehicle based on road structure information contained in map information, and plans preparations for the static occlusion area based on the possibility of occurrence.

9. The driving system of claim 1, wherein the at least one processor, in planning the vehicle's behavior, plans a positioning of the vehicle laterally off-center relative to the center of the lane to improve coverage of the occlusion area rather than the vehicle being in the center of the lane.

10. A driving system as described in claim 1, configured to be able to execute the dynamic driving task in a mode corresponding to automation level 2, wherein the at least one processor, when planning the behavior of the vehicle in the mode corresponding to automation level 2, plans to move the vehicle to one of the following positions, a sensor optimization position (P1) that can optimize the range of the occluded area recognized by the surrounding monitoring sensor, and an occupant optimization position (P2) that can optimize the range of the occluded area recognized by the occupant of the vehicle, to temporarily stop, and then move the vehicle to the other position and temporarily stop.

11. The driving system described in claim 10, wherein, when planning the behavior of the vehicle in a mode corresponding to automation level 2, the at least one processor decides to omit moving to the occupant optimization position if the occupancy optimization position improves after moving to the sensor optimization position and temporarily stopping, and then moving to the occupant optimization position and temporarily stopping.

12. A driving system as described in any one of claims 1, 10 and 11, configured to be able to execute the dynamic driving task in a mode corresponding to automation level 3 or higher, wherein the at least one processor, when planning the behavior of the vehicle in the mode corresponding to automation level 3 or higher, plans to move the vehicle to a sensor optimization position where the position of the vehicle can optimize the extent of the occluded area recognized through the surrounding monitoring sensor and to stop the vehicle.

13. The driving system of claim 1, wherein the periphery monitoring sensor includes a spatial information sensor capable of monitoring using spatial information and a temporal information sensor (41a) capable of monitoring using temporal information, and wherein the at least one processor is further configured to, in recognizing the obstructed area, determine, based on the temporal information sensor, the possibility that other road users are present in the obstructed area recognized based on the spatial information sensor, and predict the behavior of the other road users in the obstructed area within a reasonably foreseeable range.

14. The driving system of claim 1, further comprising a storage medium (55c) for storing information about a route traveled by the vehicle in the past and about the obstructed area on the route, wherein the at least one processor, even if the obstructed area where other road users may appear is not recognized in the current driving, plans vehicle control regarding the temporary stop in a more cautious manner when planning the behavior of the vehicle, if the current driving route is the route traveled in the past and the obstructed area where other road users may appear has been recognized in the past on the route, than if the obstructed area was not recognized.

15. The driving system of claim 1, wherein the at least one processor, in planning the vehicle's behavior, plans to make the presence of the vehicle conspicuous using an exterior information presentation device (70c) when traveling in an area where other road users may emerge from the occluded area.

16. The driving system of claim 1, wherein the surroundings monitoring sensor includes an acoustic sensor (41a) that detects sound, and the at least one processor, in planning the vehicle's behavior, plans to temporarily stop the vehicle when a horn sound is detected based on the acoustic sensor, and to resume driving the vehicle after confirming, while the vehicle is temporarily stopped, that the other vehicle that emitted the horn sound is moving away from the vehicle.

17. A method for executing a dynamic driving task for a vehicle (1), executed by at least one processor (51b), comprising: recognizing an obstructed area (OA) based on sensor data from a surrounding monitoring sensor (41) mounted on the vehicle and monitoring the surroundings of the vehicle when the vehicle is scheduled to pass through an area (IS) where a right or left turn is permitted; and planning the behavior of the vehicle so as to change the manner of vehicle control regarding a stop according to the result of the recognition of the obstructed area.

18. A program for executing processing to execute a dynamic driving task of a vehicle (1), the program being configured to cause at least one processor (51b) to: recognize an obstructed area (OA) based on sensor data from a surrounding monitoring sensor (41) mounted on the vehicle and monitoring the vehicle's surroundings when the vehicle is scheduled to pass through an area (IS) where a right or left turn is possible; and plan the behavior of the vehicle so as to change the vehicle control mode regarding a temporary stop in accordance with the result of the recognition of the obstructed area.

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