Driver assistance systems and vehicles

Abstract

The present invention provides a driver assistance system and vehicle capable of predicting the likelihood of pedestrians or light vehicles crossing the road before a crosswalk in specific traffic conditions. [Solution] A driving assistance device according to one embodiment of the present disclosure is capable of predicting the time it will take for a target traffic participant to reach a crosswalk when, under predetermined conditions at a first time, the signal for pedestrians or light vehicles at a crosswalk begins to switch from indicating "proceed" to indicating "no proceed" at a second time. Furthermore, based on the predicted time, this driving assistance device can calculate the probability that the target traffic participant will cross the road on which the vehicle is traveling, and determine whether or not to provide driving assistance and the content of the driving assistance according to the calculated probability.

Description

[Technical Field]

[0001] This disclosure relates to a driver assistance system installed in a vehicle, and a vehicle equipped with a driver assistance system. [Background technology]

[0002] In recent years, various proposals have been made for driver assistance devices that perform various controls to support the driver's driving operations in vehicles such as automobiles, and these devices are generally being put into practical use. Technologies related to such driver assistance devices are disclosed, for example, in Patent Documents 1 to 4. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2011-138250 [Patent Document 2] Japanese Patent Publication No. 2012-234499 [Patent Document 3] Japanese Patent Publication No. 2015-49583 [Patent Document 4] Japanese Patent Publication No. 2021-157427 [Overview of the project]

[0004] The driver assistance device relating to the first aspect of this disclosure comprises an acquisition unit and a calculation unit. The acquisition unit is capable of acquiring road structure data and traffic participant data around the vehicle. Based on the road structure data and traffic participant data, the calculation unit calculates the probability that a predicted target traffic participant will cross a target section of the road on which the vehicle is traveling, which is before a pedestrian crossing as seen from the vehicle, and determines whether or not to provide driver assistance and the content of driver assistance according to the calculated probability of crossing. The control unit, if the following conditions (1) to (4) are met at a first time, calculates the time it will take for the predicted target traffic participant to reach the pedestrian crossing when the second traffic signal described below begins to switch from indicating "proceed" to indicating "no proceed" at a second time after the first time, calculates a first probability that the predicted target traffic participant will cross the target section based on the calculated time, and can set the calculated first probability as the above-mentioned probability of crossing. (1) In front of the vehicle, there is a first traffic light for vehicles, and a second traffic light for pedestrians or light vehicles, and a pedestrian crossing, which are installed in conjunction with the first traffic light. (2) The first traffic light is indicating that the vehicle cannot proceed. (3) The second traffic light indicates that the vehicle is permitted to proceed. (4) The predicted traffic participants include pedestrians or light vehicles moving towards a crosswalk.

[0005] The vehicle relating to the second aspect of this disclosure is equipped with a driver assistance system. The driver assistance system mounted on the vehicle comprises an acquisition unit and a calculation unit. The acquisition unit is capable of acquiring road structure data and traffic participant data around the vehicle. Based on the road structure data and traffic participant data, the calculation unit calculates the probability that a predicted target traffic participant will cross a target section of the road on which the vehicle is traveling, which is before a pedestrian crossing as seen from the vehicle, and can determine whether or not to provide driver assistance and what kind of driver assistance to provide according to the calculated probability of crossing. The control unit, if the following conditions (1) to (4) are met at a first time, predicts the time when the second traffic signal described below begins to switch from indicating "proceed" to indicating "no proceed" at a second time after the first time, and calculates a first probability that the predicted target traffic participant will cross the target section based on the predicted time, and can use the calculated first probability as the above-mentioned probability of crossing. (1) In front of the vehicle, there is a first traffic light for vehicles, and a second traffic light for pedestrians or light vehicles, and a pedestrian crossing, which are installed in conjunction with the first traffic light. (2) The first traffic light is indicating that the vehicle cannot proceed. (3) The second traffic light indicates that the vehicle is permitted to proceed. (4) The predicted traffic participants include pedestrians or light vehicles moving towards a crosswalk. [Brief explanation of the drawing]

[0006] The accompanying drawings are provided for further understanding of this disclosure and are incorporated herein and constitute part of this specification. The drawings illustrate one embodiment and, together with the specification, serve to illustrate the principles of this disclosure.

[0007] [Figure 1] Figure 1 is a diagram illustrating an example of traffic condition A. [Figure 2] Figure 2 shows an example of traffic condition B. [Figure 3] Figure 3 shows an example of traffic condition C. [Figure 4] FIG. 4 is a diagram showing a schematic configuration example of a vehicle according to an embodiment of the present disclosure. [Figure 5] FIG. 5 is a diagram showing an example of a driving support procedure in the vehicle of FIG. 4.

MODE FOR CARRYING OUT THE INVENTION

[0008] Hereinafter, some exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Note that the following description shows a specific example of the present disclosure and should not be construed as limiting the present disclosure. For example, each element including numerical values, shapes, materials, parts, the positions of each part, and the connection methods of each part is merely an example and should not be construed as limiting the present disclosure. Further, in the following exemplary embodiments, components not described in the independent claims based on the highest concept of the present disclosure are optional and may be provided as necessary. The drawings are schematic and are not intended to be drawn to actual scale. Throughout this specification and the drawings, components having substantially the same function and substantially the same configuration are denoted by the same reference numerals, and redundant descriptions are omitted. In addition, components not directly related to an embodiment of the present disclosure are not shown in the drawings.

[0009] <1. BACKGROUND> In recent years, in vehicles such as automobiles, various proposals have been made for driving support devices that perform various controls to assist a driver's driving operation, and they are generally being put into practical use. Technologies related to such driving support devices are disclosed in, for example, Patent Documents 1 to 4.

[0010] Patent Document 1 describes a technique for predicting whether a pedestrian is about to cross a roadway based on a planned movement route from the current position of the pedestrian to the destination and the acceleration of the pedestrian when walking, which are acquired from a portable terminal possessed by the pedestrian, and based on the acquired planned movement route and the preparatory action before crossing grasped by the change in the pitch interval of the acquired acceleration.

[0011] Patent Document 2 describes a technique for predicting the possibility that a pedestrian in front of the vehicle will cross the driving lane (own lane) in which the vehicle is traveling based on detecting a forward pedestrian walking on the roadside of the driving lane (own lane) of the vehicle and an oncoming pedestrian walking on the roadside of the oncoming lane, whether the detected oncoming pedestrian has started to cross the oncoming lane, whether the forward pedestrian has recognized the crossing of the oncoming lane by the oncoming pedestrian, and whether the forward pedestrian has recognized the presence of the vehicle itself.

[0012] Patent Document 3 describes a technique for predicting the possibility that a pedestrian will cross an intersection based on the lighting state of a pedestrian signal and the road width of the intersection at an intersection where the roads intersect in front of the vehicle itself.

[0013] Patent Document 4 describes a technique for predicting the possibility that a pedestrian will cross a crosswalk when there is a crosswalk in front of a time-difference intersection in the own lane of the vehicle itself, while the signal of the own lane indicates that it is possible to proceed and the signal of the oncoming lane indicates that it is not possible to proceed at the same time.

[0014] However, in the inventions described in Patent Documents 1 to 4, it is not possible to predict the possibility that a pedestrian will cross the road in front of the crosswalk in any of the following traffic situations A to C. Therefore, it is not possible to perform notification control or driving control considering the following risks.

[0015] Traffic situation A: · In front of the vehicle itself, there are a traffic signal for vehicles, a pedestrian signal provided corresponding to the traffic signal for vehicles, and a crosswalk. · The traffic signal for vehicles indicates red (not allowed to proceed). · The pedestrian signal at the crosswalk in front of the vehicle itself has started to switch from indicating blue (allowed to proceed) to indicating red (not allowed to proceed), and at this time, there is a pedestrian or a light vehicle moving towards the crosswalk. Risks in traffic situation A: · The possibility that a pedestrian or a light vehicle moving towards the crosswalk will cross the road in front of the crosswalk as seen from the vehicle itself on the road where the vehicle is traveling.

[0016] Traffic conditions B: • There is a traffic light for vehicles, as well as a pedestrian traffic light and crosswalk that are installed in conjunction with the traffic light for vehicles, in front of the vehicle. • The traffic light for vehicles is showing red (no proceedings). The pedestrian signal at the crosswalk ahead of the vehicle is beginning to change from green (proceeding permitted) to red (proceeding prohibited). At this time, there is a pedestrian or vehicle crossing the crosswalk, and a pedestrian or vehicle moving towards the crosswalk. Hazards in traffic condition B: - The possibility that a pedestrian or light vehicle moving towards a crosswalk may cross the road in front of the crosswalk from the perspective of the vehicle.

[0017] Traffic conditions C: • There is a traffic light for vehicles, as well as a pedestrian traffic light and crosswalk that are installed in conjunction with the traffic light for vehicles, in front of the vehicle. • The pedestrian signal is showing red (no entry). • When the traffic light for vehicles switches from red (no proceeding) to green (proceeding permitted), there are pedestrians or light vehicles moving towards the crosswalk alongside the line of vehicles that were stopped in a row while the traffic light was red (no proceeding). Hazards in traffic condition C: • A pedestrian or light vehicle moving alongside the above-mentioned line of vehicles towards a crosswalk may pass through the gaps in the line of vehicles and cross the road in front of the crosswalk from the perspective of the vehicle.

[0018] Figure 1 shows an example of traffic situation A. In traffic situation A, vehicle 100a (the vehicle itself) is attempting to make a right turn at intersection IS, and is flashing its right-turn signal while slowing down in the right-turn-only lane (lane La2). Vehicle 100a is traveling in lane La2 of road La, which is composed of a straight-ahead lane (lane La1), a right-turn-only lane (lane La2), and an oncoming lane (lane La3) near intersection IS. Road La intersects with road Lb at intersection IS. Intersection IS has multiple vehicle traffic lights and multiple pedestrian traffic lights. For example, intersection IS has a traffic light TLa for vehicles traveling in lanes La1 and La2, and a traffic light TLb for pedestrians or light vehicles crossing the pedestrian crossing CW on road La.

[0019] Traffic light TLa is showing red (no proceedings), and multiple vehicles are stopped in a line in lane La1. In lane La2, vehicle 100a is approaching intersection IS while slowing down and flashing its right turn signal. Traffic light TLb is about to switch from green (permitted) to red (no proceedings). At this time, there may or may not be pedestrians crossing the crosswalk CW. On the sidewalk adjacent to lane La1, pedestrian 100b is walking towards the crosswalk CW.

[0020] Pedestrian 100b sees the traffic light TLb switch from green (ready to go) to flashing green (caution) and begins to consider whether to cross the pedestrian crossing CW or cross the road La before reaching the pedestrian crossing CW. In this traffic situation, the likelihood of pedestrian 100b crossing the road La before reaching the pedestrian crossing CW may vary depending on the time it takes for pedestrian 100b to reach the pedestrian crossing CW.

[0021] Figure 2 shows an example of traffic situation B. In traffic situation B, vehicle 100a (the vehicle itself) is attempting to make a right turn at intersection IS, and is flashing its right-turn signal while slowing down in the right-turn-only lane (lane La2). Vehicle 100a is traveling in lane La2 of road La, which is composed of a straight-ahead lane (lane La1), a right-turn-only lane (lane La2), and an oncoming lane (lane La3) near intersection IS. Road La intersects with road Lb at intersection IS. Intersection IS has multiple vehicle traffic lights and multiple pedestrian traffic lights. For example, intersection IS has traffic light TLa for vehicles traveling in lanes La1 and La2, and traffic light TLb for pedestrians or light vehicles crossing the pedestrian crossing CW on road La.

[0022] Traffic light TLa is showing red (no proceedings), and multiple vehicles are stopped in a line in lane La1. In lane La2, vehicle 100a is approaching intersection IS while slowing down and flashing its right turn signal. Traffic light TLb is about to switch from green (permitted) to red (no proceedings). At this time, pedestrian 100b is walking on crosswalk CW, and it will take a considerable amount of time for pedestrian 100b to cross crosswalk CW completely. On the sidewalk or shoulder adjacent to lane La1, pedestrian 100b is walking towards crosswalk CW.

[0023] Pedestrian 100b sees the traffic light TLb switch from green (ready to go) to flashing green (caution) and begins to consider whether or not to cross the crosswalk CW. Seeing pedestrian 100c walking across the crosswalk CW, pedestrian 100b infers that the multiple vehicles stopped in lane La1 will not start moving until pedestrian 100c has finished crossing the crosswalk CW, and considers whether it is still possible to cross the crosswalk CW now, or to cross road La before reaching the crosswalk CW. In this traffic situation, the likelihood of pedestrian 100b crossing the crosswalk CW or crossing road La before reaching the crosswalk CW may change depending on the time it takes for pedestrian 100b to reach the crosswalk CW and the time it takes for pedestrian 100c to finish crossing the crosswalk CW.

[0024] Figure 3 shows an example of traffic situation C. In traffic situation C, vehicle 100a (the vehicle itself) is attempting to make a right turn at intersection IS, and is flashing its right-turn signal while slowing down in the right-turn-only lane (lane La2). Vehicle 100a is traveling in lane La2 of road La, which is composed of a straight-ahead lane (lane La1), a right-turn-only lane (lane La2), and an oncoming lane (lane La3) near intersection IS. Road La intersects with road Lb at intersection IS. Intersection IS has multiple vehicle traffic lights and multiple pedestrian traffic lights. For example, intersection IS has traffic light TLa for vehicles traveling in lanes La1 and La2, and traffic light TLb for pedestrians or light vehicles crossing the pedestrian crossing CW on road La.

[0025] Traffic light TLa switches from red (no proceeding) to green (proceeding permitted). In lane La1, several stopped vehicles are about to start moving. In lane La2, vehicle 100a is approaching intersection IS while slowing down and flashing its right turn signal. Traffic light TLb is showing red (no proceeding). On the sidewalk or shoulder adjacent to lane La1, pedestrian 100b is walking towards crosswalk CW.

[0026] Pedestrian 100b sees the traffic light TLa switch from red (no proceeding) to green (proceeding permitted) and infers that the multiple vehicles stopped in lane La1 will not depart immediately, and therefore considers that it may now be possible to cross road La before crosswalk CW. In this traffic situation, the likelihood of pedestrian 100b crossing road La before crosswalk CW may vary depending on the position and speed of one or more vehicles in lane La1 that are close to pedestrian 100b.

[0027] In addition, in traffic situations A to C described above, a light vehicle (e.g., a bicycle) may travel on the sidewalk or shoulder instead of pedestrian 100b. Also, in traffic situation B described above, a light vehicle (e.g., a bicycle) may travel across the crosswalk CW instead of pedestrian 100c.

[0028] In the above traffic conditions A to C, if it is not possible to predict the possibility of pedestrian 100b or a light vehicle crossing road La before pedestrian crossing CW, vehicle 100a may collide with pedestrian 100b or a light vehicle crossing road La before pedestrian crossing CW. Therefore, the inventor of the present invention has conceived of a prediction technology that can predict the possibility of pedestrian 100b or a light vehicle crossing road La before pedestrian crossing CW in the above traffic conditions A to C. By realizing such a technology, it will be possible to reduce traffic accidents in which vehicle 100a comes into contact with pedestrian 100b or a light vehicle in the above traffic conditions A to C. A vehicle equipped with the above prediction technology will be described in detail below.

[0029] Hereinafter, several exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. The following description is intended to illustrate specific examples of the present disclosure and should not be construed as limiting the disclosure. For example, elements such as numerical values, shapes, materials, parts, the location of each part, and the method of connecting each part are merely examples and should not be construed as limiting the disclosure. Furthermore, in the following exemplary embodiments, components not described in separate sections based on the highest-level concepts of the present disclosure are optional and may be provided as needed. The drawings are schematic and are not intended to be to scale. Throughout this specification and the drawings, components having substantially the same function and substantially the same configuration are denoted by the same reference numerals, and redundant descriptions are omitted. Furthermore, components not directly related to an embodiment of the present disclosure are not shown in the drawings.

[0030] <2. Embodiments> [Example Configuration] Figure 4 shows a schematic configuration example of vehicle 1 according to one embodiment of the present disclosure. Vehicle 1 corresponds to vehicle 100a described above and is a specific example of "vehicle" according to one embodiment of the present disclosure. Vehicle 1 includes, for example, a sensor unit 10, a communication unit 20, a control unit 30, a storage unit 40, a notification unit 50, a prime mover 60, a brake 70, and an ESP motor 80, as shown in Figure 4. The control unit 30 is a specific example of "driving support device" according to one embodiment of the present disclosure.

[0031] The sensor unit 10 is comprised of various sensors mounted on the vehicle 1. For example, the sensor unit 10 comprises a vehicle speed sensor, an acceleration sensor, an angular velocity sensor, a steering angular velocity sensor, a steering torque sensor, and a braking torque sensor. The sensor unit 10 may also include sensors other than those listed above.

[0032] The vehicle speed sensor is capable of detecting the speed of vehicle 1. The vehicle speed sensor can output time-series data of the detected vehicle speed to the control unit 30. The acceleration sensor is capable of detecting the acceleration applied to vehicle 1. The acceleration sensor can output time-series data of the detected acceleration in three directions to the control unit 30. The angular velocity sensor is capable of detecting the angular velocity of vehicle 1. The angular velocity sensor can output time-series data of the detected three angular velocities (yaw angular velocity, roll angular velocity, and pitch angular velocity) to the control unit 30.

[0033] The steering angular velocity sensor is capable of detecting the rotational speed of the steering angle (steering angle) of the steering wheel of vehicle 1. The steering angular velocity sensor is capable of outputting time-series data of the detected steering angular velocity to the control unit 30. The steering torque sensor is capable of detecting the steering torque generated by the driver's steering wheel operation. The steering torque sensor is capable of outputting time-series data of the detected steering torque to the control unit 30. The braking torque sensor is capable of detecting the braking torque generated by the driver's brake operation. The braking torque sensor is capable of outputting time-series data of the detected braking torque to the control unit 30.

[0034] The sensor unit 10 further comprises a stereo camera mounted on the vehicle 1 and a driving environment detection unit. The stereo camera is an autonomous sensor that senses the real space around the vehicle 1. The stereo camera is positioned, for example, symmetrically on either side of the central part of the vehicle 1 in the width direction, enabling stereo imaging of the area in front of the vehicle 1 from different viewpoints. The stereo camera is capable of outputting image data Ia (a pair of stereo image data) obtained by imaging to the control unit 30.

[0035] The stereo camera is capable of generating distance image data Ib, which is determined from the amount of displacement of the corresponding object's position based on image data Ia obtained by imaging. The driving environment detection unit can, for example, determine the lane markings that demarcate the road around the vehicle 1 based on the distance image data Ib. The driving environment detection unit can further determine the road curvature of the markings that demarcate the left and right sides of the road (driving lane) on which the vehicle 1 travels, and the width between the left and right markings (vehicle width). The driving environment detection unit can further perform predetermined pattern matching on the distance image data Db to detect lanes and three-dimensional objects such as structures present around the vehicle 1. The driving environment detection unit is composed of, for example, an MPU (Micro Processing Unit).

[0036] In the driving environment detection unit, the detection of three-dimensional objects includes, for example, the type of object, the distance to the object, the speed of the object, and the relative speed between the object and the vehicle (the vehicle itself). Examples of objects to be detected include traffic lights, intersections, road signs, stop lines, other vehicles, pedestrians, bicycles, and buildings. Examples of buildings include detached houses, apartment buildings, commercial facilities, factories, and signs. The driving environment detection unit can output driving environment data TE, which includes the data of three-dimensional objects acquired in this way, to the control unit 30.

[0037] The communication unit 20 can acquire data to supplement data that cannot be obtained from image data Ia and distance image data Ib, for example, through vehicle-to-vehicle communication, vehicle-to-infrastructure communication, and satellite communication. The communication unit 20 can output the acquired data to the control unit 30.

[0038] The communication unit 20 can acquire data obtained from other vehicles (e.g., vehicle position, vehicle speed) through vehicle-to-vehicle communication, for example. The communication unit 20 can also receive positioning signals transmitted from multiple positioning satellites through satellite communication, for example.

[0039] The communication unit 20 is capable of acquiring road map data around vehicle 1, for example, through vehicle-to-infrastructure communication. The road map data consists of, for example, high-precision road map information (dynamic map) and mainly comprises static and quasi-static information that constitutes road information, and quasi-dynamic and dynamic information that mainly constitutes traffic information.

[0040] The static information that constitutes road information consists of information that requires updates at a frequency of no more than one month, such as roads and structures on roads, structures surrounding roads, lane information, road surface information, and permanent regulatory information. "Roads" include, for example, the location and shape of roads, intersections, and road attributes (e.g., national roads, prefectural roads, municipal roads, private roads, priority roads, non-priority roads, general roads, expressways). "Structures on roads" include, for example, traffic signs, traffic lights, convex mirrors, pedestrian overpasses, bus stops, and garbage collection points. "Structures surrounding roads" include, for example, various buildings and parks.

[0041] The quasi-static information that makes up road information consists of information that needs to be updated within an hour, such as traffic restriction information due to road construction or events, wide-area weather information, and congestion forecasts.

[0042] The semi-dynamic information that makes up traffic information consists of information that needs to be updated within one minute, such as actual congestion conditions and driving restrictions at the time of observation, temporary driving obstructions such as fallen objects and obstacles, actual accident conditions, and local weather information.

[0043] The dynamic information that constitutes traffic information consists of information that requires updates every second, such as information transmitted and exchanged between moving objects, information on currently displayed traffic signals, information on pedestrians and cyclists at intersections, and information on vehicles traveling on the roads. This road map information is maintained and updated in cycles until the next information is received from each vehicle, and the updated road map information is transmitted to each vehicle as appropriate through the communication unit 20.

[0044] The storage unit 40 is composed of, for example, non-volatile memory, such as EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, or resistive random-access memory. The storage unit 40 stores, for example, a road map DB (database) 41 and a threshold value 42, as shown in Figure 5.

[0045] The road map DB41 contains high-precision road map information (dynamic map). This high-precision road map information, similar to road map information acquired externally via vehicle-to-infrastructure communication, mainly consists of static and quasi-static information that constitutes road information, and quasi-dynamic and dynamic information that mainly constitute traffic information.

[0046] Threshold 42 includes various thresholds used to predict the likelihood of a pedestrian crossing the road before a crosswalk in any of the traffic conditions A to C described above. Threshold 42 includes, for example, thresholds tpc1, tpc2, and tpc3 described below. Threshold tpc1 is used to predict the likelihood of a pedestrian crossing the road before a crosswalk in traffic condition A described above. Threshold tpc2 is used to predict the likelihood of a pedestrian crossing the road before a crosswalk in traffic condition B described above. Threshold tpc3 is used to predict the likelihood of a pedestrian crossing the road before a crosswalk in traffic condition C described above.

[0047] The control unit 30 is capable of controlling the entire vehicle 1. The control unit 30 is, for example, a so-called ECU (Electronic Control Unit) and is composed of, for example, one or more processors and one or more memories. The control unit 30 may also be composed of, for example, a CPU (Central Processing Unit). In this case, the control unit 30 is capable of controlling the entire vehicle 1 by, for example, executing a program stored in a memory unit.

[0048] The control unit 30 includes, for example, a locator unit. The locator unit is capable of acquiring the position coordinates of vehicle 1 based on the positioning signal received through the communication unit 20. The locator unit is capable of estimating the vehicle's position on the road map by map matching the acquired position coordinates onto route map information. Based on the acquired position coordinates of vehicle 1, the locator unit acquires map information for a predetermined range including vehicle 1 from the map information stored in the road map DB 41, which will be described later.

[0049] The locator unit can switch to autonomous navigation, which estimates the vehicle's position on a road map based on vehicle speed, angular velocity, and longitudinal acceleration detected by the sensor unit 10, in environments where it is not possible to receive effective positioning signals from positioning satellites due to reduced sensitivity, such as when driving in a tunnel.

[0050] As described above, the locator unit estimates the position of vehicle 1 on a road map (vehicle position) based on the positioning signal received through the communication unit 20 or the information detected by the sensor unit 10. Based on the estimated vehicle position on the road map, it is possible to determine the type of road on which vehicle 1 is traveling.

[0051] The locator unit can update the road map information stored in the road map DB 41 to the latest state using road map information acquired through external communication (vehicle-to-infrastructure communication and vehicle-to-vehicle communication) via the communication unit 20. This information update is performed not only on static information but also on quasi-static, quasi-dynamic, and dynamic information. As a result, the road map information is composed of road information and traffic information acquired through communication with the outside of the vehicle, and information on moving objects such as vehicles traveling on the road is updated in near real time.

[0052] The locator unit verifies the road map information based on the driving environment information recognized as described above, and updates the road map information stored in the road map DB41 to the latest state. This information update is performed not only on static information, but also on quasi-static, quasi-dynamic, and dynamic information. As a result, information on moving objects such as vehicles traveling on the road, as recognized as described above, is updated in real time.

[0053] The control unit 30 further includes a driving control unit 31, as shown in Figure 4, for example. The driving control unit 31 is capable of controlling the driving of the vehicle 1 (for example, the torque of the prime mover 60, the amount of brake depression, and the steering angle of the steering wheel) and providing notifications related to the driving of the vehicle 1. The driving control unit 31 includes, for example, a data acquisition unit 32, a crossing determination unit 33, a support decision unit 34, a notification control unit 35, an avoidance control unit 36, an accelerator control unit 37, a brake control unit 38, and a steering control unit 39, as shown in Figure 4. The data acquisition unit 32 corresponds to one specific example of the "acquisition unit" according to one embodiment of the present disclosure. The crossing determination unit 33 and the support decision unit 34 correspond to one specific example of the "calculation unit" according to one embodiment of the present disclosure.

[0054] The data acquisition unit 32 is capable of periodically acquiring data about the status or condition of the vehicle 1 through monitoring. Specifically, the data acquisition unit 32 is capable of periodically acquiring various data obtained from the sensor unit 10, various data obtained from external sources via the communication unit 20, and various control signals for various devices of the vehicle 1 (for example, control signals for the turn signals). Hereinafter, the various data obtained from the sensor unit 10, various data obtained from external sources via the communication unit 20, and various control signals for various devices of the vehicle 1 will be referred to as "data obtained from the sensor unit 10, etc."

[0055] The data acquisition unit 32 is capable of acquiring road structure data Da and traffic participant data Db based on data obtained from the sensor unit 10, etc. Road structure data Da corresponds to one specific example of "road structure data" according to one embodiment of the present disclosure. Traffic participant data Db corresponds to one specific example of "traffic participant data" according to one embodiment of the present disclosure. Road structure data Da includes, for example, information about the road and structures on the road surrounding vehicle 1, and structures around the road.

[0056] The traffic participant data database (Db) includes information about the position and speed of vehicle 1, and information about the position and speed of each traffic participant around vehicle 1. A traffic participant is a concept that includes, for example, vehicles, light vehicles (e.g., bicycles), and pedestrians. The traffic participant data database (Db) includes, for example, information about the position and speed of vehicle 1, information about the position and speed of each vehicle traveling on the road around vehicle 1, information about the position and speed of pedestrians and cyclists on sidewalks or shoulders adjacent to the road around vehicle 1, and information about the position and speed of pedestrians and cyclists at crosswalks on the road around vehicle 1.

[0057] The crossing determination unit 33 is capable of identifying the traffic conditions around vehicle 1 based on road structure data Da and traffic participant data Db. For example, when the traffic conditions around vehicle 1 satisfy the following conditions (1) to (4), the crossing determination unit 33 determines the time T A It is possible to temporarily store this. Time T A This corresponds to a specific example of the "first time" according to one embodiment of the present disclosure. The cross-sectional determination unit 33 determines, for example, time T A After the time has elapsed, when the traffic light TLb begins to switch from displaying green (go) to red (do not go), the time T at that time B It is possible to temporarily store this. Time T B This corresponds to a specific example of the "second time" according to one embodiment of the present disclosure. Time T Bis, for example, the time when the traffic signal TLb switches from a flashing blue (proceed with caution) indication to a red (no entry) indication. Time T B may be, for example, the time when the traffic signal TLb switches from a blue (go-ahead) indication to a flashing blue (proceed with caution) indication. The crossing determination unit 33 can, for example, identify the traffic situation around the vehicle 1 as traffic situation A when the following conditions (1) to (4) of the traffic situation around the vehicle 1 are satisfied and the traffic signal TLb starts to switch from a blue (go-ahead) indication to a red (no entry) indication.

[0058] (1) In front of the vehicle 1 (vehicle 100a), there are a traffic signal TLa for the vehicle 1 (vehicle 100a), a traffic signal TLb for pedestrians or light vehicles provided corresponding to the traffic signal TLa, and a crosswalk CW. (2) The traffic signal TLa shows a red (no entry) indication. (3) The traffic signal TLb shows a blue (go-ahead) indication. (4) As a predicted traffic participant, there is a pedestrian 100b or a light vehicle moving towards the crosswalk CW.

[0059] The crossing determination unit 33, for example, at time T B when there is a pedestrian or a light vehicle crossing the crosswalk CW, can identify the traffic situation around the vehicle 1 as traffic situation B when the traffic signal TLb starts to switch from a blue (go-ahead) indication to a red (no entry) indication. The crossing determination unit 33, for example, at time T B after time T has elapsed, when the traffic signal TLa switches from a red (no entry) indication to a blue (go-ahead) indication, can temporarily store the time T C at that time. Time T C corresponds to a specific example of the "third time" according to an embodiment of the present disclosure. The crossing determination unit 33, for example, after time T B has elapsed, when the traffic signal TLa switches from a red (no entry) indication to a blue (go-ahead) indication, can identify the traffic situation around the vehicle 1 as traffic situation C.

[0060] The crossing determination unit 33 is capable of calculating the probability (hereinafter referred to as "crossing probability P") that a predicted target traffic participant will cross the road in front of a pedestrian crossing on the road on which vehicle 1 is traveling, as seen from vehicle 1, in the identified traffic conditions, based on the road structure data Da and traffic participant data Db. Hereinafter, "the area in front of a pedestrian crossing on the road on which vehicle 1 is traveling, as seen from vehicle 1" will be referred to as the target section. Crossing probability P corresponds to one specific example of "crossing probability" according to one embodiment of the present disclosure. The target section corresponds to one specific example of "target section" according to one embodiment of the present disclosure.

[0061] The crossing determination unit 33 can, for example, when it identifies the traffic conditions around vehicle 1 as traffic condition A, predict the time T1 at which the target traffic participant (pedestrian 100b or light vehicle) will reach the pedestrian crossing CW in traffic condition A. The crossing determination unit 33 can predict time T1 based, for example, the speed at which pedestrian 100b moves in traffic condition A and the distance from pedestrian 100b to the pedestrian crossing CW in traffic condition A. The crossing determination unit 33 can, for example, calculate the probability Pa at which the target traffic participant will cross the road (road La) on which vehicle 1 (vehicle 100a) is traveling, in front of the pedestrian crossing CW on the road (road La) as seen from vehicle 1 (vehicle 100a), based on the calculated time T1 and threshold tpc1.

[0062] Hereinafter, "the section of road La on which vehicle 1 (vehicle 100a) is traveling, up to the pedestrian crossing CW on the road La as seen from vehicle 1 (vehicle 100a)" will be referred to as the target section TS. The predicted target traffic participant (pedestrian 100b or light vehicle) corresponds to one specific example of the "predicted target traffic participant" in one embodiment of this disclosure. The target section TS corresponds to one specific example of the "target section" in one embodiment of this disclosure. Time T1 corresponds to one specific example of the "first time" in one embodiment of this disclosure. Probability Pa corresponds to one specific example of the "first possibility" in one embodiment of this disclosure.

[0063] The crossing determination unit 33 can determine, for example, that a predicted traffic participant may cross the target section TS when time T1 is longer than threshold tpc1. At this time, the crossing determination unit 33 can calculate the probability Pa using, for example, the following formula. α1 and β1 are correction coefficients, and γ1 is a correction term. Pa=α1×[exp((T1-tpc1) / β1)-1]+γ1

[0064] The crossing determination unit 33 can determine, for example, that there is no possibility of the predicted traffic participant crossing the target section TS when time T1 is less than or equal to threshold tpc1. In this case, the crossing determination unit 33 can set the probability Pa to 0, for example. The crossing determination unit 33 can set the probability Pa in traffic condition A to the possibility of crossing P, for example.

[0065] The crossing determination unit 33 can, for example, when it identifies the traffic conditions around vehicle 1 as traffic conditions B, calculate time T1 and time T2 until pedestrian 100c completes crossing the pedestrian crossing CW in traffic conditions B. The crossing determination unit 33 can calculate time T2 based on, for example, the speed of movement of pedestrian 100c in traffic conditions B and the distance from the position of pedestrian 100c in traffic conditions B to the position reached when pedestrian 100c completes crossing the pedestrian crossing CW. The crossing determination unit 33 can, for example, calculate the probability Pb ​​that the predicted target traffic participant will cross the target section TS in traffic conditions B based on the calculated time T2 and threshold tpc2. The crossing determination unit 33 can, for example, calculate probability Pc based on the calculated probabilities Pa and Pb, and set the calculated probability Pc as the crossing probability P. Time T2 corresponds to one specific example of the "second time" according to one embodiment of this disclosure. Possibility Pb ​​corresponds to a specific example of the "second possibility" according to one embodiment of the present disclosure. Possibility Pc corresponds to a specific example of the "third possibility" according to one embodiment of the present disclosure.

[0066] The crossing determination unit 33 can determine, for example, that a predicted traffic participant may cross the target section TS when time T2 is shorter than threshold tpc2. In this case, the crossing determination unit 33 can calculate the probability Pb ​​using, for example, the following formula. α2 and β2 are correction coefficients, and γ2 is a correction term. Pb=α2×[exp((T2-tpc2) / β2)-1]+γ2

[0067] The crossing determination unit 33 can determine, for example, that there is no possibility of the predicted traffic participant crossing the target section TS when time T2 is greater than or equal to threshold tpc2. In this case, the crossing determination unit 33 can determine, for example, that the probability Pb ​​is 0. The crossing determination unit 33 can calculate the probability Pc (= Pa + Pb) by adding the probability Pa and probability Pb ​​together. The crossing determination unit 33 can determine, for example, that the probability Pc in traffic conditions A and B is the crossing probability P.

[0068] For example, when the crossing determination unit 33 identifies the traffic conditions around vehicle 1 as traffic condition C, it is possible to calculate the probability Pd that the predicted traffic participant will cross the target section TS based on the positions and speeds of multiple vehicles heading towards intersection IS that are close to the predicted traffic participant in traffic condition C. The probability Pd corresponds to one specific example of the "fourth possibility" according to one embodiment of this disclosure.

[0069] The crossing determination unit 33 can, for example, identify the vehicle that is closest to the predicted traffic participant and further from the intersection IS than the predicted traffic participant (hereinafter referred to as the "nearest vehicle") in traffic condition C. The crossing determination unit 33 can, for example, identify multiple vehicles (hereinafter referred to as "vehicles ahead") that are on the same lane La1 as the nearest vehicle and are located between the nearest vehicle and the intersection IS in traffic condition C. The crossing determination unit 33 can, for example, calculate the travel speed and inter-vehicle distance of the nearest vehicle and the multiple vehicles ahead in traffic condition C. Inter-vehicle distance refers to the distance between the target vehicle and the vehicle ahead that is closest to the target vehicle.

[0070] The crossing determination unit 33 can, for example, set the distance between vehicles when there is a vehicle ahead whose speed exceeds a predetermined amount (e.g., 1.0 m / s) in the calculated speed of each vehicle ahead as the threshold for the distance between nearest vehicles. Based on the calculated position and speed of each vehicle ahead, the crossing determination unit 33 determines, for example, the time T in traffic condition C when the distance between nearest vehicles (the distance between the nearest vehicle and the vehicle closest to it) exceeds the aforementioned threshold. D It is possible to estimate the cross-sectional determination unit 33, for example, time T D and time T C By calculating the difference (time T3) and the threshold tpc3, it is possible to calculate the probability Pd that the predicted traffic participant will cross the target section TS.

[0071] The crossing determination unit 33 can determine, for example, that a predicted traffic participant may cross the target section TS when time T3 is longer than threshold tpc3. In this case, the crossing determination unit 33 can calculate the probability Pd using, for example, the following formula, where α3 and β3 are correction coefficients and γ3 is a correction term. Pd=α3×[exp((T3-tpc3) / β3)-1]+γ3

[0072] The crossing determination unit 33 can determine, for example, that there is no possibility of the predicted traffic participant crossing the target section TS when time T3 is less than or equal to the threshold tpc3. In this case, the crossing determination unit 33 can set the probability Pd to 0. The crossing determination unit 33 can calculate the probability Pe (= Pa + Pc + Pd) by adding the probabilities Pa, Pc, and Pd together. The probability Pe corresponds to a specific example of the "fifth possibility" according to one embodiment of this disclosure. The crossing determination unit 33 can set the probability Pe in traffic conditions A, B, and C as the crossing possibility P. Here, the correction coefficients α1, α2, α3, β1, β2, and β3 are set to values ​​such that the probability Pe is between 0 and 1.

[0073] The support decision unit 34 can determine whether or not to provide driving assistance and what kind of driving assistance to provide, according to the possibility of crossing P calculated by the crossing determination unit 33. If the possibility of crossing P is less than, for example, 0.25, the support decision unit 34 can decide not to provide driving assistance.

[0074] If the probability of crossing P is, for example, 0.25 or greater and less than 0.50, the support decision unit 34 can decide to issue a warning to the driver of vehicle 1 (vehicle 100a). At this time, the support decision unit 34 can output the necessary notification control information to the notification control unit 35 for issuing a warning to the driver of vehicle 1 (vehicle 100a). The support decision unit 34 can output the notification control unit 35, for example, notification control information that includes information about the location of the predicted target traffic participant that may jump into the target section TS.

[0075] If the probability of crossing P is, for example, 0.50 or greater and less than 0.75, the support decision unit 34 can decide to issue a warning to the driver of vehicle 1 (vehicle 100a). At this time, the support decision unit 34 can output the necessary notification control information to the notification control unit 35 for issuing a warning to the driver of vehicle 1 (vehicle 100a). The support decision unit 34 can output the notification control unit 35, for example, notification control information including information about the location of the predicted target traffic participant that may jump into the target section TS, and information instructing the output of a warning sound.

[0076] If the crossing probability P is, for example, 0.75 or higher, the support decision unit 34 can decide to perform avoidance control to prevent vehicle 1 (vehicle 100a) from making contact with the predicted traffic participant. At this time, the support decision unit 34 can output the avoidance control information necessary for vehicle 1 (vehicle 100a) to make contact with the predicted traffic participant to the avoidance control unit 36.

[0077] The notification control unit 35 is capable of performing notification control based on notification control information obtained from the support decision unit 34. For example, the notification control unit 35 can generate an audio signal of an audio message informing that a traffic participant may suddenly jump out from the side of the road in front of the vehicle, based on the notification control information obtained from the support decision unit 34, and output it to the notification unit 50. The notification unit 50 is configured, for example, to include a microphone, and is capable of outputting an audio message informing that a traffic participant may suddenly jump out from the side of the road in front of the vehicle, based on the audio signal input from the notification control unit 35. For example, the notification control unit 35 is capable of generating an audio signal of a warning sound informing that a traffic participant may suddenly jump out from the side of the road in front of the vehicle, based on the notification control information obtained from the support decision unit 34, and outputting it to the notification unit 50. The notification unit 50 is capable of outputting a warning sound based on the audio signal input from the notification control unit 35.

[0078] The notification control unit 35 can, for example, generate a video signal to display an image showing that a traffic participant may suddenly jump out from the side of the road in front of the vehicle, based on the notification control information obtained from the support decision unit 34, and output it to the notification unit 50. The notification unit 50 is configured, for example, to include a liquid crystal panel or an organic EL panel, and can display an image showing that a traffic participant may suddenly jump out from the side of the road in front of the vehicle, based on the video signal input from the notification control unit 35. The notification unit 50 can, for example, display an image showing the location of a predicted target traffic participant who may suddenly jump out into the target section TS.

[0079] The avoidance control unit 36 ​​is capable of performing driving control in accordance with the avoidance control information obtained from the support decision unit 34.

[0080] The accelerator control unit 37 is capable of controlling the torque of the prime mover 60 based on the requested torque corresponding to the amount the driver of the vehicle 1 depresses the accelerator pedal. Furthermore, the accelerator control unit 37 is capable of deriving a target torque by adding an additional torque obtained based on avoidance control information to the requested torque, and controlling the torque of the prime mover 60 based on the derived target torque. The prime mover 60 is configured to drive the steering wheels of the vehicle 1 and is capable of driving the steering wheels of the vehicle 1 according to the requested torque or target torque input from the accelerator control unit 37.

[0081] The brake control unit 38 is capable of controlling the torque of the brake 70 based on the requested torque corresponding to the amount the driver of the vehicle 1 presses the brake pedal. Furthermore, the brake control unit 38 is capable of deriving a target torque by adding an additional torque obtained based on avoidance control information to the requested torque, and controlling the torque of the brake 70 based on the derived target torque. The brake 70 is configured to brake the steering wheels of the vehicle 1, and is capable of braking the steering wheels of the vehicle 1 according to the requested torque or target torque input from the brake control unit 38.

[0082] The steering control unit 39 can derive a steering assist torque to assist the steering torque generated by the driver's steering wheel operation, and set an EPS torque corresponding to the derived steering assist torque. Furthermore, the steering control unit 39 can derive a target torque by adding an additional torque obtained based on avoidance control information to the steering assist torque, and set an EPS torque corresponding to the derived target torque. The steering control unit 39 can output a control signal to the EPS motor 80 so that the output torque of the EPS motor 80 becomes the set EPS torque. The EPS motor 80 generates an output torque based on the input control signal and can control the steering angle of the steering wheel.

[0083] Next, we will explain the driving assistance procedure for vehicle 1.

[0084] Figure 5 shows an example of the driving assistance procedure in vehicle 1. The driving control unit 31 acquires various data, including road structure data Da and traffic participant data Db (step S101). The driving control unit 31 also acquires various control signals as needed. Subsequently, the driving control unit 31 identifies the traffic conditions around vehicle 1 based on the acquired road structure data Da and traffic participant data Db, etc. (step S102).

[0085] Next, the driving control unit 31 calculates the probability (crossing probability P) that a predicted target traffic participant will cross the target section TS in the identified traffic conditions. If the crossing probability P is greater than a predetermined value, that is, if there is a possibility that a predicted target traffic participant will cross the target section TS (step S103;Y), the crossing probability P is notified to the driver of vehicle 1 (step S104). Furthermore, if the crossing probability P is greater than a predetermined value, that is, if there is a high risk that a predicted target traffic participant will cross the target section TS (step S103;Y), avoidance control is performed (step S105). In this way, driving assistance for vehicle 1 is performed.

[0086] [effect] Next, the effects of Vehicle 1 according to one embodiment of the present disclosure will be described.

[0087] In this embodiment, time T A If the predetermined conditions are met at time T A Time T later than B In this embodiment, when the traffic signal TLb for pedestrians or light vehicles at the crosswalk CW begins to switch from green (proceed) to red (no proceed), the time T1 at which the predicted target traffic participant will reach the crosswalk CW is calculated. Based on the calculated time T1, the probability P that the predicted target traffic participant will cross the target section TS in traffic condition A is calculated, and the presence or absence of driver assistance and the content of driver assistance are determined according to the calculated probability P. Thus, in this embodiment, the probability that the predicted target traffic participant will cross the target section TS is predicted using the predicted value of the time T1 at which the predicted target traffic participant will reach the crosswalk CW. As a result, even if vehicle 1 does not have prior knowledge of the planned actions of pedestrians or light vehicles present around the crosswalk CW, it is possible to, for example, identify the presence of pedestrians or light vehicles that may cross the target section TS, and to inform the driver of vehicle 1 of the presence of such pedestrians or light vehicles, or to perform driving control to avoid contact with pedestrians or light vehicles that may cross the target section TS. As a result, it is possible to reduce the number of traffic accidents in which vehicle 1 comes into contact with pedestrians or light vehicles crossing the target section TS.

[0088] In this embodiment, time T BIn this embodiment, when a pedestrian or light vehicle is crossing the crosswalk CW, and the traffic signal TLb begins to switch from green (proceed) to red (no proceed), the time T2 until pedestrian 100c completes crossing the crosswalk CW is calculated. Based on the calculated time T2, the probability Pb ​​that the predicted target traffic participant will cross the target section TS in traffic condition B is calculated, and based on probabilities Pa and Pb, the probability P of crossing in traffic conditions A and B is calculated, and the presence or absence and content of driver assistance are determined according to the calculated probability P of crossing. Thus, in this embodiment, the probability that the predicted target traffic participant will cross the target section TS is predicted using the predicted value of the time T2 until pedestrian 100c completes crossing the crosswalk CW. As a result, even if vehicle 1 does not have prior knowledge of the planned movements of pedestrians or light vehicles around the crosswalk CW, it can, for example, identify the presence of pedestrians or light vehicles that may cross the target section TS. This allows the driver of vehicle 1 to be notified of the presence of such pedestrians or light vehicles, or to perform driving control to avoid contact with pedestrians or light vehicles that may cross the target section TS. Consequently, the number of traffic accidents in which vehicle 1 comes into contact with pedestrians or light vehicles crossing the target section TS can be reduced.

[0089] In this embodiment, time T CIn this embodiment, when the traffic light TLa switches from red (no proceeding) to green (proceeding permitted), the probability Pd of a predicted target traffic participant crossing the target section TS in traffic condition C is calculated based on the positions and speeds of multiple vehicles approaching intersection IS that are close to the predicted target traffic participant. Based on probabilities Pa, Pc, and Pd, the probability P of crossing in traffic conditions A, B, and C is calculated, and the presence and content of driver assistance are determined according to the calculated probability P of crossing. Thus, in this embodiment, the probability of a predicted target traffic participant crossing the target section TS is predicted using the positions and speeds of multiple vehicles approaching intersection IS. As a result, even if vehicle 1 does not have prior knowledge of the planned actions of pedestrians or light vehicles present around the crosswalk CW, it can, for example, identify the presence of pedestrians or light vehicles that may cross the target section TS, and the presence of such pedestrians or light vehicles can be notified to the driver of vehicle 1, or driving control can be performed to avoid contact with pedestrians or light vehicles that may cross the target section TS. As a result, the number of traffic accidents in which vehicle 1 comes into contact with pedestrians or light vehicles crossing the target section TS can be reduced.

[0090] Thus, in this embodiment, notification control and driving control are performed based on the predicted possibility P of crossing the target section TS by the target traffic participant, which changes in accordance with the moment-to-moment changing traffic conditions. This makes it possible to reduce traffic accidents in which vehicle 1 comes into contact with pedestrians or light vehicles crossing the target section TS.

[0091] The effects described herein are illustrative only. The effects of this disclosure are not limited to those described herein. This disclosure may have effects other than those described herein.

[0092] The above embodiment assumed that the country or region had traffic regulations in which vehicle 1 travels in the left lane. However, if the country or region has traffic regulations in which vehicle 1 travels in the right lane, the above embodiment should be modified to reflect the traffic regulations of that country or region, such as replacing expressions that assume a left lane with expressions that assume a right lane, or changing "turn right" to "turn left".

[0093] Furthermore, for example, this disclosure can take the following configuration. <1> An acquisition unit capable of acquiring road structure data and traffic participant data around the first vehicle, A calculation unit capable of determining whether or not to provide driving assistance and what kind of driving assistance to provide, based on the road structure data and the traffic participant data, calculates the probability that a predicted traffic participant will cross a target section of the road on which the first vehicle is traveling, which is before a pedestrian crossing as seen from the first vehicle, and determines the probability of providing driving assistance and what kind of driving assistance to provide, based on the calculated probability of crossing. Equipped with, The aforementioned arithmetic unit, At the first time, if the following conditions (1) to (4) are met, and at the second time, which is later than the first time, the second traffic light described below begins to switch from indicating "proceed" to indicating "no proceed," the first time when the predicted target traffic participant reaches the pedestrian crossing is predicted. Based on the predicted first time, the probability that the predicted traffic participant will cross the target section is calculated, and the calculated first probability is defined as the crossing possibility. This becomes possible Driving assistance system. (1) In front of the first vehicle, there is a first traffic light for the first vehicle, and a second traffic light for pedestrians or light vehicles and a pedestrian crossing, which are provided in correspondence with the first traffic light. (2) The first traffic light is indicating that the vehicle cannot proceed. (3) The second traffic light indicates that the vehicle is permitted to proceed. (4) The predicted traffic participants include pedestrians or light vehicles moving towards the crosswalk. <2> The aforementioned arithmetic unit, At the second time, if there is a pedestrian crossing the crosswalk, and the second traffic light begins to switch from indicating "proceed" to indicating "no proceeding," the second time until the pedestrian completes crossing the crosswalk is predicted. Based on the predicted second time, the probability of the predicted traffic participant crossing the target section is calculated, and a third probability is calculated based on the calculated first and second probabilities, and the calculated third probability is defined as the crossing possibility. This becomes possible <1> The driving assistance device described above. <3> The calculation unit, at a third time after the second time, when the first traffic light switches from indicating no proceedings to indicating proceedings, calculates a fourth possibility that the predicted target traffic participant will cross the target section based on the positions and speeds of multiple second vehicles approaching the intersection that are close to the predicted target traffic participant. Based on the calculated first, second, and third possibilities, it calculates a fifth possibility, and the calculated fifth possibility is set as the crossing possibility. <2> The driving assistance device described above. <4> A vehicle equipped with a driver assistance system, The aforementioned driving support device, An acquisition unit capable of acquiring road structure data and traffic participant data around the first vehicle, A calculation unit capable of determining whether or not to provide driving assistance and what kind of driving assistance to provide, based on the road structure data and the traffic participant data, calculates the probability that a predicted traffic participant will cross a target section of the road on which the first vehicle is traveling, which is before a pedestrian crossing as seen from the first vehicle, and determines the probability of providing driving assistance and what kind of driving assistance to provide, based on the calculated probability of crossing. It has, The aforementioned arithmetic unit, At the first time, if the following conditions (1) to (4) are met, and at the second time, which is later than the first time, the second traffic light described below begins to switch from indicating "proceed" to indicating "no proceed," the first time when the predicted target traffic participant reaches the pedestrian crossing is predicted. Based on the predicted first time, the probability that the predicted traffic participant will cross the target section is calculated, and the calculated first probability is defined as the crossing possibility. This becomes possible vehicle. (1) In front of the first vehicle, there is a first traffic light for the first vehicle, and a second traffic light for pedestrians or light vehicles and a pedestrian crossing, which are provided in correspondence with the first traffic light. (2) The first traffic light is indicating that the vehicle cannot proceed. (3) The second traffic light indicates that the vehicle is permitted to proceed. (4) The predicted traffic participants include the pedestrian or light vehicle moving toward the crosswalk.

[0094] In the driver assistance system relating to the first aspect of this disclosure and the vehicle relating to the second aspect of this disclosure, if predetermined conditions are met at a first time, at a second time later than the first time, when the second traffic signal for pedestrians or light vehicles at a crosswalk begins to switch from indicating "proceed" to indicating "no proceed," the time it will take for the predicted traffic participant to reach the crosswalk is calculated. Based on the calculated time, the probability that the predicted traffic participant will cross the road on which the vehicle is traveling is calculated, and the presence or absence of driver assistance and the content of the driver assistance are determined according to the calculated probability. This makes it possible, for example, to inform the vehicle driver of the presence of pedestrians or light vehicles that may cross before the crosswalk, or to perform driving control to avoid contact with pedestrians or light vehicles that may cross before the crosswalk. As a result, it is possible to reduce traffic accidents in which a vehicle comes into contact with pedestrians or light vehicles that are crossing before the crosswalk.

[0095] The control unit 30 shown in Figure 4 can be implemented by a circuit including at least one semiconductor integrated circuit, such as at least one processor (e.g., a central processing unit (CPU)), at least one application-specific integrated circuit (ASIC) and / or at least one field-programmable gate array (FPGA). The at least one processor can be configured to perform all or some of the functions of the control unit 30 shown in Figure 4 by reading instructions from at least one non-temporary, tangible computer-readable medium. Such a medium can take various forms, including, but is not limited to, various magnetic media such as hard disks, various optical media such as CDs or DVDs, and various semiconductor memories (i.e., semiconductor circuits) such as volatile or non-volatile memory. Volatile memory may include DRAM and SRAM. Non-volatile memory may include ROM and NVRAM. An ASIC is an integrated circuit (IC) specialized to perform all or some of the functions of the control unit 30 shown in Figure 4. An FPGA is an integrated circuit designed to be configurable after manufacturing to perform all or some of the functions of the control unit 30 shown in Figure 4.

[0096] 1...Vehicle, 10...Sensor unit, 20...Communication unit, 30...Control unit, 31...Driving control unit, 32...Data acquisition unit, 33...Crossing determination unit, 34...Support decision unit, 35...Notification control unit, 36...Avoidance control unit, 37...Accelerator control unit, 38...Brake control unit, 39...Steering control unit, 40...Storage unit, 41...Road map DB, 42...Threshold, 50...Notification unit, 60...Motor, 70...Brake, 80...EPS motor, 100a...Vehicle, 100b,100c...Pedestrian, ...CW...Crosswalk, IS...Intersection, La,Lb...Road, La1,La2,La3...Lane, TLa,TLb...Traffic light, TS...Target section.

Claims

1. An acquisition unit capable of acquiring road structure data and traffic participant data around the first vehicle, A calculation unit capable of determining whether or not to provide driving assistance and what kind of driving assistance to provide, based on the road structure data and the traffic participant data, calculates the probability that a predicted traffic participant will cross a target section of the road on which the first vehicle is traveling, which is before a pedestrian crossing as seen from the first vehicle, and determines the probability of providing driving assistance and what kind of driving assistance to provide, based on the calculated probability of crossing. Equipped with, The aforementioned arithmetic unit, At the first time, if the following conditions (1) to (4) are met, and at the second time, which is later than the first time, the second traffic light described below begins to switch from indicating "proceed" to indicating "no proceed," the first time when the predicted target traffic participant reaches the pedestrian crossing is predicted. Based on the predicted first time, the probability that the predicted traffic participant will cross the target section is calculated, and the calculated first probability is defined as the crossing possibility. This becomes possible Driving assistance system. (1) In front of the first vehicle, there is a first traffic light for the first vehicle, and a second traffic light for pedestrians or light vehicles and a pedestrian crossing, which are provided in correspondence with the first traffic light. (2) The first traffic light is indicating that the vehicle is not allowed to proceed. (3) The second traffic light is indicating that the vehicle can proceed. (4) The predicted traffic participants include pedestrians or light vehicles moving towards the crosswalk.

2. The aforementioned arithmetic unit, At the second time, if there is a pedestrian crossing the crosswalk, and the second traffic light begins to switch from indicating "proceed" to indicating "no proceeding," the second time until the pedestrian completes crossing the crosswalk is predicted. Based on the predicted second time, the probability of the predicted traffic participant crossing the target section is calculated, and a third probability is calculated based on the calculated first and second probabilities, and the calculated third probability is defined as the crossing possibility. This becomes possible The driving support device according to claim 1.

3. The calculation unit, at a third time after the second time, when the first traffic light switches from indicating no proceedings to indicating proceedings, calculates a fourth possibility that the predicted target traffic participant will cross the target section based on the positions and speeds of multiple second vehicles approaching the intersection that are close to the predicted target traffic participant. Based on the calculated first, second, and third possibilities, it calculates a fifth possibility, and the calculated fifth possibility is set as the crossing possibility. The driving support device according to claim 2.

4. A vehicle equipped with a driver assistance system, The aforementioned driving support device, An acquisition unit capable of acquiring road structure data and traffic participant data around the first vehicle, A calculation unit capable of determining whether or not to provide driving assistance and what kind of driving assistance to provide, based on the road structure data and the traffic participant data, calculates the probability that a predicted traffic participant will cross a target section of the road on which the first vehicle is traveling, which is before a pedestrian crossing as seen from the first vehicle, and determines the probability of providing driving assistance and what kind of driving assistance to provide, based on the calculated probability of crossing. It has, The aforementioned arithmetic unit, At the first time, if the following conditions (1) to (4) are met, and at the second time, which is later than the first time, the second traffic light described below begins to switch from indicating "proceed" to indicating "no proceed," the first time when the predicted target traffic participant reaches the pedestrian crossing is predicted. Based on the predicted first time, the probability that the predicted traffic participant will cross the target section is calculated, and the calculated first probability is defined as the crossing possibility. This becomes possible vehicle. (1) In front of the first vehicle, there is a first traffic light for the first vehicle, and a second traffic light for pedestrians or light vehicles and a pedestrian crossing, which are provided in correspondence with the first traffic light. (2) The first traffic light is indicating that the vehicle is not allowed to proceed. (3) The second traffic light is indicating that the vehicle can proceed. (4) The predicted traffic participants include the pedestrian or light vehicle moving toward the crosswalk.

Images