Method for controlling a vehicle

Abstract

A method for controlling a vehicle, the method comprising: Providing the vehicle with an actuator configured to control a vehicle steering system, a sensor configured to provide signals indicative of road geometry in the vicinity of the vehicle, and a controller connected to the actuator and the sensor; Controlling the actuator via the controller in an autonomous driving mode; Determining a distance to a merging point between a current lane of the vehicle and a target lane adjacent to the current lane via the controller based on a signal from the sensor; Calculating a first time parameter via the controller based on the distance to the merging point; Calculating a merge time via the controller to complete the merge between the current lane and the target lane; Determining, via the controller, whether a merge criterion is met based on a difference between the first time parameter and a second time parameter; and Interrupting the autonomous control of the actuator in response to the merging criterion being met; Calculating a tuning parameter based on signals from the sensor, wherein the merging criterion is met in response to the difference between the first time parameter and the second time parameter being less than the tuning parameter.

Description

The present description relates to vehicles controlled by automated driving systems, particularly those configured to automatically control vehicle steering, acceleration, and braking during a drive cycle without human intervention.The operation of modern vehicles is becoming more automated, i.e. it can take over driving control with less and less driver intervention. Vehicle automation has been classified into numerical levels ranging from zero, i.e., no automation with full human control, to five, i.e., full automation without human control. Various automated driver assistance systems such as cruise control, adaptive cruise control and parking assistance systems correspond to a lower degree of automation, while genuine "keyless" vehicles correspond to a higher degree of automation.US 2016 / 0 214 612 A1 describes an autonomous vehicle. In a case where it is determined that a merging control cannot be executed, a host vehicle is caused to stop in a lane toward a boundary line between the lane and a merging target lane by a stop control unit. For this reason, the possibility increases that the range in which the driver of the host vehicle can see the emerging target lane directly from the side window increases. Therefore, when the driver of the host vehicle restarts the host vehicle by manual driving, it is possible to facilitate the check of the status on the target lane.US 2018 / 0 240 345 A1 describes a navigation system with a traffic flow mechanism and the operation of such a system. A method of operating a navigation system includes: determining a buffer distance that satisfies or exceeds a size threshold between obstacle locations; determining a merging time based on a current location with respect to the buffer distance; determining a lane placement based on a travel time that satisfies or exceeds a time threshold; and executing a lane merging operation with a controller based on the merging time, the lane placement, or a combination thereof to guide a user's vehicle to merge into a lane different from the one currently being traveled.US 2018 / 0 148 060 A1 describes an autonomous driving system, comprising: an information acquisition device configured to acquire driving environment information indicating the driving environment for a vehicle; and a lane change control device configured to control the lane change of the vehicle based on the driving environment information. When it is determined that the lane change can be started at a standard time, the lane change control device performs delay processing that delays an actual start time of the lane change from the standard time. The lane change control device variably sets a delay setting from the standard time point to the actual start time point according to the driving environment.It may be considered an object to autonomously control a motor vehicle to join from one lane to another and return control to a human operator when human control is desired.At the outset, a motor vehicle is described which contains components with which the method according to the invention can be implemented.For example, a motor vehicle includes at least one actuator configured to control steering, shifting, accelerating, or braking of vehicles. The vehicle also includes at least one sensor configured to provide signals indicative of road geometry in the environment of the vehicle. The vehicle further includes a controller in communication with the at least one sensor and the at least one actuator. The controller is configured to selectively control the at least one actuator in an autonomous driving mode based on signals from the at least one sensor. The controller is configured to automatically determine a first time parameter based on a distance to a merging location between a current lane of the vehicle and a target lane adjacent to the current lane in response to signals from the at least one sensor, to automatically determine a second time parameter based on a calculated merging end time, and to automatically end autonomous control of the at least one actuator based on a difference between the first time parameter and the second time parameter.For example, the second time parameter is based on a speed limit of the target lane, a first road geometry parameter of the current lane, a second road geometry parameter of the target lane, a current speed of the vehicle, or a traffic density parameter of the target lane.For example, the controller is further configured to calculate a tuning parameter based on signals of the at least one sensor and automatically adjust the autonomous control of the at least one actuator when the difference between the first time parameter and the second time parameter is less than the tuning parameter. In such embodiments, the controller may be further configured to calculate a second tuning parameter based on signals from the at least one sensor, automatically abort the autonomous control of the at least one actuator in response to the difference between the first time parameter and the second time parameter being less than the tuning parameter when no merging maneuver has been initiated, and automatically abort the autonomous control of the at least one actuator in response to the difference between the first time parameter and the second time parameter being less than the second tuning parameter when the merging maneuver has not been completed.According to the invention, a method of controlling a vehicle includes providing a vehicle with an actuator configured to control a vehicle steering system, a sensor configured to provide signals indicative of road geometry in the environment of the vehicle, and a controller connected to the actuator and the sensor. The method additionally includes controlling, via the controller, the actuator in an autonomous driving mode. The method also includes determining, via the controller, a distance to a merging location between a current lane of the vehicle and a target lane adjacent to the current lane based on a signal from the sensor. The method further includes computing, via the controller, a first time parameter based on the distance to the merging location. The method additionally includes computing, via the controller, a merging time to complete the merging between the current lane and the target lane. The method also includes determining, via the controller, whether a merging criterion is met based on a difference between the first time parameter and a second time parameter. The method further includes aborting autonomous control of the actuator in response to satisfying the merging criterion. According to the invention, the method includes calculating a tuning parameter based on signals from the sensor, wherein the merging criterion is fulfilled in response to the difference between the first time parameter and the second time parameter being smaller than the tuning parameter.In an exemplary embodiment, the second time parameter is based on a speed limit of the target lane, a first road geometry parameter of the current lane, a second road geometry parameter of the target lane, a current speed of the vehicle, or a traffic density parameter of the target lane.According to the invention, the method additionally includes calculating a tuning parameter based on signals from the sensor. In this case, the merging criterion is fulfilled if the difference between the first time parameter and the second time parameter is smaller than the tuning parameter. In this context, the calculation of a second tuning parameter based on signals of the sensor may additionally be included. In such embodiments, the merging criterion is satisfied if the difference between the first time parameter and the second time parameter is less than the tuning parameter when no merging maneuver has been initiated, or if the difference between the first time parameter and the second time parameter is less than the second tuning parameter when the merging maneuver has not been completed.In an exemplary embodiment, the method additionally includes, in response to the merging criterion not being fulfilled, automatically controlling, via the controller, the actuator to merge with the target.Embodiments according to the present description provide a number of advantages. For example, the present description provides a system and method for controlling a motor vehicle to autonomously attempt to join from one lane to another and return control to a human operator when human control is desired. FIG. 1 is a schematic diagram of a communication system with an autonomously controlled vehicle; FIG. 2 is a schematic block diagram of an automated driving system (ADS) for a vehicle; FIG. 3 is an illustrative illustration of a vehicle; and FIG. 4 is a flowchart illustration of a method for controlling a vehicle according to an embodiment.FIG. 1 schematically illustrates an operating environment that includes a mobile vehicle communication and control system 10 for a motor vehicle 12. The motor vehicle 12 may be referred to as a host vehicle. The communication and control system 10 for the host vehicle 12 generally includes one or more wireless carrier systems 60, a land communication network 62, a computer 64, a mobile device 57 such as a smartphone, and a remote access center 78.The host vehicle 12 schematically illustrated in FIG. 1 is illustrated as a passenger vehicle in the illustrated embodiment, however, it should be appreciated that any other vehicle including motor bicycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), marine vessels, aircraft, etc., may also be used. The host vehicle 12 includes a propulsion system 13, which in various embodiments may include an internal combustion engine, an electric machine such as a traction motor, and / or a fuel cell propulsion system.The host vehicle 12 also includes a transmission 14 configured to transmit power from the propulsion system 13 to a plurality of vehicle wheels 15 according to selectable speed ratios. According to various embodiments, the transmission 14 may include a stepped automatic transmission, a continuously variable transmission, or another suitable transmission. The host vehicle 12 additionally includes wheel brakes 17 configured to provide the braking torque to the vehicle wheels 15. The wheel brakes 17 may include friction brakes, a regenerative braking system such as an electric machine, and / or other suitable braking systems, in various embodiments.The host vehicle 12 additionally includes a steering system 16. Although shown as a steering wheel for illustrative purposes, the steering system 16 may not include a steering wheel in some embodiments contemplated within the scope of the present description.The host vehicle 12 includes a wireless communication system 28 configured to wirelessly communicate with other vehicles ("V2V") and / or the infrastructure ("V2I"). In an exemplary embodiment, the wireless communication system 28 is configured to operate over a dedicated DSRC (Dedicated Short Range Communication) channel. Dedicated Short Range Communications Channel, DSRC channel). DSRC channels refer to short to medium range, uni- or bi-directional wireless communication channels that have been specially developed for use in automobiles, as well as a corresponding set of protocols and standards. However, wireless communication systems configured for communication via additional or alternative wireless communication standards such as IEEE 802.11 and cellular data communication are also contemplated within the scope of the present description.The propulsion system 13, transmission 14, steering system 16, and wheel brakes 17 are in communication with or under the control of at least one controller 22, while controller 22 is illustratively shown as a single unit, it may additionally include one or more other controllers, collectively referred to as a "controller.". The controller 22 may include a microprocessor or central processing unit (CPU) in communication with various types of computer readable storage devices or media. Computer readable storage devices or media may include, for example, volatile and nonvolatile memories in read-only memory (ROM), random access memory (RAM), and keep alive memory (KAM). KAM is a persistent or non-volatile memory that can be used to store various operating variables while the CPU is off. Computer readable storage devices or media may be implemented using any number of known storage devices, such as programmable read-only memory (PROMs), electrically EPROMs (PROM), EEPROMs (electrically erasable PROM), flash memory, or other electrical, magnetic, optical, or combined storage devices for storing data, some of which represent executable instructions, used by the controller 22 to control the vehicle.The controller 22 includes an automated driving system (ADS) 24 for automatically controlling various actuators in the vehicle. In an exemplary embodiment, the ADS 24 is a so-called Level 3 automation system. A level 3 system refers to "conditional automation", which relates to driving mode-specific performance of an automated driving system of all aspects of the dynamic driving task, with the expectation that the human operator will respond appropriately to a prompt for intervention.Other embodiments may be implemented in connection with so-called Level 1 or Level 2 automation systems. A level 1 system refers to "driver assistance" that relates to driving mode-related execution of steering or acceleration operations by a driver assistance system using information about the driving environment and expect the human operator to meet all other aspects of the dynamic driving task. A level 2 system is indicative of "sub-automation" and relates to driving mode-related execution of steering and acceleration by one or more driver assistance systems using information about the driving environment and with the expectation that the human operator will meet all other aspects of the dynamic driving task.Still further embodiments may also be realized in connection with so-called level 4 or level 5 automation systems. A level 4 system means "high automation" and refers to driving mode-related performance of an automated driving system in all aspects of the dynamic driving task, even if a human operator does not respond appropriately to a request to intervene. A level 5 system refers to "full automation", i.e., the permanent performance of an automated driving system with respect to all aspects of the dynamic driving task under all roadway and environmental conditions that can be controlled by a human operator.In an exemplary embodiment, the ADS 24 is configured to control the propulsion system 13, transmission 14, steering system 16, and wheel brakes 17 to control vehicle acceleration, steering, and braking without human intervention via a plurality of actuators 30 in response to inputs from a plurality of sensors 26, which may include GPS, RADAR, LIDAR, optical cameras, thermal cameras, ultrasonic sensors, and / or additional sensors, as appropriate.FIG. 1 illustrates a plurality of networked devices capable of communicating with the wireless communication system 28 of the host vehicle 12. One of the networked devices that may communicate with the host vehicle 12 via the wireless communication system 28 is the mobile device 57. the mobile device 57 may include computer processing capability, a transceiver that may transmit signals 58 using a short-range wireless protocol, and a visual smartphone display 59. The computer processing capability includes a microprocessor in the form of a programmable device including one or more instructions stored in an internal memory structure and used to receive binary inputs to generate binary outputs. In some embodiments, the mobile device 57 includes a GPS module capable of receiving signals from GPS satellites 68 and generating GPS coordinates based on these signals. In further embodiments, mobile device 57 includes cellular communication functionality such that mobile device 57 performs voice and / or data communication over wireless carrier system 60 using one or more cellular communication protocols, as discussed herein. The smartphone visual display 59 may also include a touch screen graphical user interface.The wireless carrier system 60 is preferably a cellular system that includes a plurality of cell towers 70 (only one shown), one or more mobile switching centers (MSCs) 72, as well as any other networking components required to connect the wireless carrier system 60 to the land communications network 62. Each cell tower 70 includes transmitting and receiving antennas and a base station, the base stations of different cell towers being connected to the MSC 72 either directly or via intermediary devices such as a base station controller. The wireless carrier system 60 may implement any suitable communication technology, including, for example, analog technologies such as AMPS or digital technologies such as CDMA (e.g., CDMA2000) or GSM / GPRS. Other cell towers / base stations / MSC arrangements are possible and may be used with the wireless carrier system 60. For example, the base station and cell tower could be co-located or spaced apart, each base station could be responsible for a single cell tower, or a single base station could serve multiple cell towers, or different base stations could be coupled to a single MSC, to name just a few of the possible arrangements.In addition to using the wireless carrier system 60, a second wireless carrier system in the form of satellite communication may be used to enable unidirectional or bidirectional communication with the host vehicle 12. This may be done with one or more communication satellites 66 and an uplink transmitting station 67. Unidirectional communication may include satellite radio services, for example, where program content (news, music, etc.) is received from the broadcasting station 67, packaged for uploading, and then sent to the satellite 66, which broadcasts the program to the subscribers. Bidirectional communication may include, for example, satellite telephony services that utilize satellite 66 to relay telephone communication between host vehicle 12 and station 67. Satellite telephony may be used either in addition to or in place of the wireless carrier system 60.Land network (or land network) 62 may be a conventional land based telecommunications network that is connected to one or more land telephone sets and connects wireless carrier system 60 to remote access center 78. For example, land network 62 may include a public switched telephone network (PSTN) as used for providing land telephony, packet switched data communication, and the Internet infrastructure. One or more segments of land network 62 could be realized through the use of a standard wired network, a fiber or other optical network, a cable network, power lines, other wireless networks such as wireless local area networks (WLANs), or networks providing broadband wireless access (BWA), or any combination thereof. Moreover, the remote access center 78 need not be connected via the land network 62, but could also include wireless telephony devices so that it can communicate directly with a wireless network, such as the wireless carrier system 60.Although shown as a single device in FIG. 1, the computer 64 may include a number of computers accessible via a private or public network such as the Internet. Each computer 64 may be used for one or more purposes. In an exemplary embodiment, the computer 64 may be configured as a web server accessible by the host vehicle 12 via the wireless communication system 28 and the wireless carrier 60. Other computers 64 may include, for example, a service center computer in which diagnostic information and other vehicle data may be uploaded from the vehicle via the wireless communication system 28, or a third party repository into or from which vehicle data or other information is provided, whether by communication with the host vehicle 12, the remote access center 78, the mobile device 57, or a combination thereof. The computer 64 may maintain a searchable database and database management system that enables input, removal, and modification of data as well as receipt of requests for data search in the database. The computer 64 may also be used to provide Internet connections such as DNS services or as a network address server that uses DHCP or other suitable protocol to assign an IP address to the host vehicle 12. The computer 64 may be in communication with at least one additional vehicle in addition to the host vehicle 12. The host vehicle 12 and all additional vehicles may collectively be referred to as fleets.As shown in FIG. 2, the ADS 24 includes a plurality of different systems, including at least one perception system 32 for determining the presence, position, classification, and path of detected features or objects in the environment of the vehicle. The perception system 32 is configured to receive inputs from a plurality of sensors, such as the sensors 26 shown in FIG. 1, and synthesize and process the sensor inputs to generate parameters that are used as inputs to other control algorithms of the ADS 24.The perception system 32 includes a sensor fusion and preprocessing module 34 that processes and synthesizes sensor data 27 from the plurality of sensors 26. The sensor fusion and preprocessing module 34 performs the calibration of the sensor data 27 including, but not limited to, LIDAR-to-LIDAR calibration, camera-to-LIDAR calibration, LIDAR-to-chassis calibration, and LIDAR beam intensity calibration. The sensor fusion and preprocessing module 34 outputs the preprocessed sensor output 35.A classification and segmentation module 36 receives the preprocessed sensor output 35 and performs object classification, image classification, traffic light classification, object segmentation, ground segmentation, and object tracking processes. Object classification includes, but is not limited to, identification and classification of objects in the environment, including identification and classification of traffic lights and signs, RADAR fusion and tracking to account for the position and field of view (FOV) of the sensor, and false positive rejection by LIDAR fusion to eliminate the many false positive false alarms present in an urban environment, such as channel caps, bridges, overhead trees or light towers, and other obstacles with a high RADAR cross-section, but which do not affect the ability of the vehicle to move along its path. Additional object classification and tracking processes performed by the classification and segmentation model 36 include, but are not limited to, free space detection and high level tracking that merges data from RADAR tracks, LIDAR segmentation, LIDAR classification, image classification, object shape matching models, semantic information, motion prediction, raster maps, static obstacle maps, and other sources to generate high-quality object tracks. The classification and segmentation module 36 additionally performs the classification of traffic control devices and the fusion of traffic control devices with lane assignment and behavior models of traffic control devices. The classification and segmentation module 36 generates an object classification and segmentation output 37 containing information about object identification.A localization and mapping module 40 uses the object classification and segmentation output 37 to calculate parameters including, but not limited to, estimates of the position and orientation of the host vehicle 12 in typical and demanding driving situations. These demanding driving situations include, but are not limited to, dynamic environments with many cars (e.g., dense traffic), environments with large area obstacles (e.g., road construction or construction sites), hills, multi-lane roads, single lane roads, a variety of road markings and buildings or their absence (e.g., residential quarters versus business quarters), as well as bridges and overpass vehicles (both above and below a current road section of the vehicle).The localization and mapping module 40 also includes new data collected by extended map areas obtained by onboard mapping functions performed by the host vehicle 12 during operation and map data "pushed" to the host vehicle 12 via the wireless communication system 28. The localization and mapping module 40 updates previous map data with the new information (e.g., new lane markings, new building structures, addition or removal of construction zones, etc.) and leaves unaffected map areas unchanged. Examples of map data that can be generated or updated include categorization of broken lines, generation of lane boundaries, lane connection, classification of sub- and main roads, classification of left and right turns, and generation of intersection driving lanes. The localization and mapping module 40 generates a localization and mapping output 41 that includes the position and orientation of the host vehicle 12 with respect to detected obstacles and road features.A vehicle odometry module 46 receives data 27 from the vehicle sensors 26 and generates a vehicle odometry output 47, including, for example, heading and speed information. An absolute positioning module 42 receives the localization and mapping output 41 and the vehicle odometry information 47 and generates a vehicle localization output 43 that is used in separate computations as discussed below.An object prediction module 38 uses the object classification and segmentation output 37 to generate parameters including, but not limited to, a position of a detected obstacle with respect to the vehicle, a predicted path of the detected obstacle with respect to the vehicle, and a position and orientation of the lanes with respect to the vehicle. Data about the predicted path of objects (including pedestrians, surrounding vehicles, and other moving objects) is output as object prediction output 39 and used in separate computations, as discussed below.The ADS 24 also includes an observation module 44 and an interpretation module 48. the observation module 44 generates an observation output 45 that is received by the interpretation module 48. The observation module 44 and the interpretation module 48 enable access by the remote access center 78. the interpretation module 48 generates an interpreted output 49 that includes additional inputs provided by the remote access center 78, if any.A path planning module 50 processes and synthesizes the object prediction output 39, the interpreted output 49, and additional routing information 79 received from an online database or remote access center 78 to determine a vehicle path to follow to maintain the vehicle on the desired route while maintaining the traffic rules and avoiding detected obstacles. The path planning module 50 uses algorithms configured to avoid detected obstacles in the environment of the vehicle, maintain the vehicle in a current lane, and maintain the vehicle on the desired route. The path planning module 50 outputs the vehicle path information as the path planning output 51. The path planning output 51 includes a commanded vehicle path based on the vehicle route, the vehicle position with respect to the route, the position and orientation of the lanes, and the presence and path of detected obstacles.A first control module 52 processes and synthesizes the path planning output 51 and the vehicle localization output 43 to generate a first control output 53. The first control module 52 also includes the routing information 79 provided by the remote access center 78 in the event of a remote take-over of the vehicle.A vehicle control module 54 receives the first control output 53 and speed and heading information 47 received from the vehicle odometry 46, and generates a vehicle control output 55. The vehicle control output 55 includes a set of actuator commands to achieve the path commanded by the vehicle control module 54, including, but not limited to, a steering command, a shift command, a throttle command, and a brake command.The vehicle control output 55 is passed to the actuators 30. In an exemplary embodiment, the actuators 30 include a steering controller, a shift controller, a throttle controller, and a brake controller. The steering controller may control, for example, a steering system 16 as shown in FIG. 1. The shift controller may control, for example, a transmission 14, as shown in FIG. 1. The throttle control may control, for example, a drive system 13 as shown in FIG. 1. The brake controller may control the wheel brakes 17, for example, as shown in FIG. 1.As discussed above, in embodiments where the ADS 24 is a Level 1 to Level 3 ADS, it is expected that the human operator will regain control of the vehicle 12 under certain operating conditions. It is therefore desirable to define methods by which the ADS 24 may determine whether and when to transmit control of the vehicle 12 to the human operator.Referring now to FIG. 3, a method of controlling a vehicle is illustrated in flow chart form. While the method will be described in connection with the vehicle 12 illustrated in FIGS. 1 and 2 for exemplary purposes, in other embodiments, the method may be employed in vehicles having other configurations. The method begins at block 100, where the ADS 24 controls the vehicle 12, which may be referred to as a host vehicle later, in an autonomous driving mode while initiating a merging maneuver. As used herein, a merging maneuver refers to a vehicle maneuver performed when a current lane of the host vehicle 12 merges or merges with an adjacent lane, which may be referred to as a target lane. Such maneuvers may be required when the host vehicle 12 is on an approach that merges with a highway when a roadway narrows or in another merging situation.An available merge time parameter T en a is calculated as illustrated at block 102. The available merging time refers to a maximum available time within which the host vehicle 12 can perform the merging maneuver while complying with the traffic rules and standards. In an exemplary embodiment, the available merging time parameter T end is calculated based on a distance to a merging location D end and a current vehicle speed V c e.g., as the distance to the merging location refers to a distance between the current location of the host vehicle 12 and the location at which the current lane of the host vehicle 12 merges with the target lane measured along the current lane. The distance to the merging location may be determined based on active sensor data, e.g., signals from one or more of the sensors 26, mapping data stored in a non-transitory computer readable memory, other data, or any suitable combination thereof. The current vehicle speed may be determined based on signals from one or more of the sensors 26 or another suitable source.A reserved time parameter for return to manual control T hb is calculated as illustrated at block 104. The reserved time parameter for return to manual control refers to an amount of time reserved to return control of the host vehicle 12 to a human operator and to the human operator to perform the merging maneuver. In an exemplary embodiment, the reserved manual control return time parameter T hb may be retrieved from a look-up table or otherwise calculated based on speed limit, road geometry, current speed, and traffic density. In other embodiments, the reserved time parameter for return to manual control T hb may be based on additional or other parameters including, but not limited to, driving practice of the human operator, size or maneuverability of the host vehicle 12, current visibility or weather conditions, or other suitable factors.An autonomous lane change allowed time parameter (autonomous lane change time parameter) T lc is calculated as illustrated at block 106. The allowed autonomous lane change time parameter T lc refers to the time that the ADS 24 may attempt to complete the lane change. In an exemplary embodiment, the allowable autonomous lane change time parameter T lc is calculated as T lc= T end- T hb.It is determined whether the ADS still has enough time to attempt the merging maneuver, as illustrated at operation 108. In an exemplary embodiment, this determination is met responsive to T lc< k 1 if a lane change maneuver has not been initiated, and / or responsive to T lc< k 2 if a lane change maneuver has not been completed. In such embodiments, k 1 and k 2 are tuning parameters that may be obtained from a look-up table or otherwise determined based on road geometry and / or other factors. In such embodiments, k 1 and k 2 may be selected based on the performance test of the vehicle 12 and the ADS 24.In response to the determination of operation 108 being negative, i.e., the ADS 24 still remaining enough time to continue attempting the merging maneuver, it is determined whether the merging maneuver is complete, as illustrated at operation 110. The determination may be satisfied in response to the vehicle 12 being fully maneuvered into the target lane.In response to the determination of operation 110 being negative, i.e., the merging maneuver not being completed, control returns to block 102. The ADS 24 continues to attempt to perform the merging maneuver as long as it still has enough time to do so while reserving the time parameter for the manual control return T hb.In response to the determination of the operation 110 being positive, i.e., the merging maneuver being completed, the algorithm ends at block 112.Returning to operation 108, in response to the determination being negative, i.e., there being no longer any permitted time left for the ADS 24 to continue attempting the merging maneuver, then the ADS attempts to provide control to the human operator, as illustrated at block 114. This may also include signaling an alarm to the human operator, e.g., an audible, visual, or haptic alarm indicating that the human operator is to take control.A determination is made whether the human operator controls the vehicle, as illustrated at block 116. This determination may be based on, for example, determining that the operator has actuated one or more control interfaces such as a steering wheel, brake pedal, or accelerator pedal.In response to the determination of operation 116 being negative, control returns to block 114. The algorithm attempts to return control to the human operator.In response to the determination of operation 116 being positive, the algorithm ends at block 112.Referring now to FIG. 4, control of the host vehicle 12 is illustrated. In the illustrated configuration, the host vehicle 12 is traveling in a current lane 80. the ADS 24 determines that the current lane 80 merges with a target lane 82 at a merging location 84, e.g., based on signals from one or more of the sensors 26, mapping data stored in a non-transitory computer readable memory, other data, or any suitable combination thereof. The merging location 84 refers to a location where the current lane 80 connects to the target lane 82, such that only one vehicle at a time can pass through the merged lane beyond the merging location 84.As explained above with reference to FIG. 3, a distance D end to the merging location 84 is calculated and a corresponding merging time parameter T end is calculated based on D end.The reserved time parameter for the return to manual control T hb is then calculated. As discussed above, the value of T hb may be determined based on various parameters, such as a speed constraint of the target lane 82, the road geometry of the current lane 80 and the target lane 82, the current speed of the host vehicle 12, and the traffic density of the target vehicles 86 on the target lane 82 and the adjacent lanes. A distance parameter D hb, which corresponds to the manual control return time parameter T hb is shown in FIG. 4, but need not be explicitly calculated.The allowed autonomous lane change time parameter T lc is calculated based on T end and T hb as explained above. A corresponding distance parameter D lc is shown in FIG. 4, but does not have to be explicitly calculated.A determination is then made as to whether the ADS still has enough time to attempt the merging maneuver based on a comparison of T lc with the tuning parameters k 1 and k 2, as explained above with respect to FIG. 3. Based on this comparison, the ADS 24 may determine whether it continues to attempt to perform the merging maneuver or return control to the human operator.As can be seen, the present description provides a system and method for controlling a motor vehicle to autonomously attempt to transition from one lane to another and return control to a human operator when human control is desired.

Claims

A method of controlling a vehicle, the method comprising: providing the vehicle with an actuator configured to control a vehicle steering system, a sensor configured to provide signals indicative of road geometry in the environment of the vehicle, and a controller connected to the actuator and the sensor; controlling, via the controller, the actuator in an autonomous driving mode; determining, via the controller, a distance to a merging location between a current driving lane of the vehicle and a target lane adjacent to the current driving lane based on a signal of the sensor; calculating, via the controller, a first time parameter based on the distance to the merging location; calculating, via the controller, a merging time to complete the merging between the current driving lane and the target lane; determining, via the controller, whether a merging criterion is met based on a difference between the first time parameter and a second time parameter; and interrupting autonomous control of the actuator in response to the merging criterion being met; calculating a tuning parameter based on signals of the sensor, wherein the merging criterion is met in response to the difference between the first time parameter and the second time parameter being less than the tuning parameter.The method of claim 1, wherein the second time parameter is based on a speed limit of the target lane, a first road geometry parameter of the current lane, a second road geometry parameter of the target lane, a current speed of the vehicle, or a traffic density parameter of the target lane.The method of claim 1, further comprising calculating a second tuning parameter based on signals from the sensor, wherein the merging criterion is satisfied in response to the difference between the first time parameter and the second time parameter being less than the tuning parameter when no merging maneuver has been initiated, or is satisfied in response to the difference between the first time parameter and the second time parameter being less than the second tuning parameter when the merging maneuver has not been completed.The method of claim 1, further comprising, in response to the merging criterion not being met, automatically controlling, via the controller, the actuator to merge with the target track.

Images