Abstract: Obstacles located in an external environment of a vehicle can be classified. At least a portion of the external environment can be sensed using one or more sensors to acquire sensor data. An obstacle candidate can be identified based on the acquired sensor data. An occlusion status for the identified obstacle candidate can be determined. The occlusion status can be a ratio of acquired sensor data for the obstacle candidate that is occluded to all acquired sensor data for the obstacle candidate. A classification for the obstacle candidate can be determined based on the determined occlusion status. A driving maneuver for the vehicle can be determined at least partially based on the determined classification for the obstacle candidate. The vehicle can be caused to implement the determined driving maneuver. The vehicle can be an autonomous vehicle.

Abstract: A device and method for effecting an autonomous control handover for passing priority control from a vehicle control unit to a vehicle operator are disclosed. In operation, an autonomous control handover event may be detected that operates to prompt a transition from a first vehicle automation level to a second vehicle automation level. In response, a perception-and-cognition of the vehicle operator may occur by sampling user control data generated via a human-machine interface device and producing simulated user control data, which is compared with corresponding autonomous control data generated via a vehicle control unit. When the simulated user control data compares favorably with the corresponding autonomous control data, an autonomous control handover response is generated operable to transition to the second vehicle automation level, and transmitting the autonomous control handover response.

Abstract: A course evaluation apparatus includes an estimated-course-group generation portion that generates a plurality of estimated course groups for a movable body; and a course evaluation portion that performs a course evaluation on the plurality of estimated course groups with respect to at least two different evaluation criteria.

Abstract: Ray tracing can be used to detect hidden obstacles in an external environment of a vehicle. An outbound sensor signal can be transmitted into an external environment of the vehicle. The outbound sensor signal can be a LIDAR sensor signal. If a return sensor signal is not received for the outbound sensor signal, it can be determined whether an obstacle is located along a projected path of the outbound sensor signal. Such a determination can be made using one or more maps, such as a terrain map and/or a static obstacle map. Responsive to determining that an obstacle is located along the projected path of the outbound sensor signal, a driving maneuver for the vehicle relative to the obstacle can be determined. The vehicle can be caused to implement the determined driving maneuver.

Abstract: A course evaluation apparatus includes an estimated-course-group generation portion that generates a plurality of estimated course groups for a movable body; and a course evaluation portion that performs a course evaluation on the plurality of estimated course groups with respect to at least two different evaluation criteria.

Abstract: A parking assistance device includes: a ground object detection unit configured to, in a predetermined detection region set in advance in at least a portion of the vehicle periphery, perform detection of a ground object defining a parking stall in which garage parking is to be performed; an end portion specification unit configured to specify an end portion of the ground object detected by the ground object detection unit, the end portion being located on an entrance side of the parking stall; and a target parking stall setting unit configured to set, based on the end portion on the entrance side specified by the end portion specification unit, a corner portion of a rectangular parking frame that defines a target parking stall in which the vehicle is to be parked, and set the parking frame to extend from the corner portion in the depth direction of the parking stall.

Abstract: An autonomous driving vehicle system includes: a surrounding information detection unit that is configured to detect surrounding information on a vehicle; and at least one electronic control unit including: a travel plan generation unit configured to generate a travel plan along a pre-set target route based on the surrounding information and map information; a traveling control unit configured to autonomously control a traveling of the vehicle based on the travel plan; and a warning light control unit configured to turn on a warning light earlier than a start time of a braking of the vehicle in the travel plan, the warning light informing a following vehicle about the braking.

Abstract: Provided is a driving assist device 10 that recognizes an object in the vicinity of a moving body, and assists a driver in driving the moving body, the apparatus including: an object detecting unit 12 that detects the object in the vicinity of the moving body; a three dimensional object detecting unit 13 that detects a three dimensional object in the vicinity of the moving body; and an object recognition unit 18 that recognizes the object at a predetermined detection position as a non-obstacle when the object information storing unit 16 stores the position of the object, and the three dimensional object information storing unit 17 does not store the position of the three dimensional object at the predetermined position in which detection is performed by both of the object detecting unit 12 and the three dimensional object detecting unit 13.

Abstract: Described herein is a device for traffic light detection. The device comprises a memory and a traffic light detection module. The memory may store information, the information comprising first traffic light data of a first traffic light and second traffic light data of a second traffic light. The traffic light detection module may receive an image comprising a first candidate and a second candidate; determine a first region of interest based, at least in part, on the first traffic light data, the first region of interest comprising the first candidate; determine a second region of interest based, at least in part, on the second traffic light data, the second region of interest comprising the second candidate; and determine a confidence score for a first state of the first candidate, the confidence score based, at least in part, on a spatial relationship factor between the first candidate and the second candidate.

Abstract: An autonomous vehicle can encounter an external environment in which an object overhangs a current road of the autonomous vehicle. For example, the branch of a tree may overhang the road. Such an overhanging object can be detected and suitable driving maneuvers for the autonomous vehicle can be determined. Sensor data can be acquired from at least a forward portion of the external environment. One or more floating obstacle candidates can be identified based on the acquired sensor data. The identified one or more floating obstacle candidates can be filtered to remove any floating obstacle candidates that do not meet one or more predefined parameters. A driving maneuver for the autonomous vehicle can be determined at least partially based on a height clearance between the autonomous vehicle and floating obstacle candidates that remain after being filtered out. The autonomous vehicle can be caused to implement the determined driving maneuver.

Abstract: Ray tracing and static obstacle maps can be used in the operation of a vehicle. Sensor data of at least a portion of an external environment of the vehicle can be acquired. A dynamic obstacle in the external environment of the vehicle can be detected based on the acquired sensor data. In response to detecting a dynamic obstacle, it can be determined whether a secondary occluded area is located behind the dynamic obstacle relative to a current location of the vehicle based on a static obstacle map. Responsive to determining that a secondary occluded area is located behind the dynamic obstacle relative to a current location of the vehicle based on a static obstacle map, a driving maneuver for the vehicle can be determined based on at least the dynamic obstacle and the secondary occluded area. The vehicle can be caused to implement the determined driving maneuver.

Abstract: Described herein is a device for traffic light detection. The device comprises a memory and a traffic light detection module. The memory may store information, the information comprising first traffic light data of a first traffic light and second traffic light data of a second traffic light. The traffic light detection module may receive an image comprising a first candidate and a second candidate; determine a first region of interest based, at least in part, on the first traffic light data, the first region of interest comprising the first candidate; determine a second region of interest based, at least in part, on the second traffic light data, the second region of interest comprising the second candidate; and determine a confidence score for a first state of the first candidate, the confidence score based, at least in part, on a spatial relationship factor between the first candidate and the second candidate.

Abstract: Arrangements relating to the transitioning of a vehicle between operational modes are described. The vehicle can transition between a first operational mode and a second operational mode. The second operational mode has a greater degree of manual involvement than the first operational mode. For instance, the first operational mode can be an unmonitored autonomous operational mode, and the second operational mode can be a monitored autonomous operational mode or a manual operational mode. It can be determined whether an operational mode transition event has occurred while the vehicle is operating in the first operational mode. In response to determining that an operational mode transition event has occurred, a time buffer for continuing in the first operational mode before switching to the second operational mode can be determined. A transition alert can be presented within the vehicle. The transition alert can represent the determined time buffer.

Abstract: Provided is a driving assist device 10 that recognizes an object in the vicinity of a moving body, and assists a driver in driving the moving body, the apparatus including: an object detecting unit 12 that detects the object in the vicinity of the moving body; a three dimensional object detecting unit 13 that detects a three dimensional object in the vicinity of the moving body; and an object recognition unit 18 that recognizes the object at a predetermined detection position as a non-obstacle when the object information storing unit 16 stores the position of the object, and the three dimensional object information storing unit 17 does not store the position of the three dimensional object at the predetermined position in which detection is performed by both of the object detecting unit 12 and the three dimensional object detecting unit 13.

Abstract: Ray tracing can be used to detect hidden obstacles in an external environment of a vehicle. An outbound sensor signal can be transmitted into an external environment of the vehicle. The outbound sensor signal can be a LIDAR sensor signal. If a return sensor signal is not received for the outbound sensor signal, it can be determined whether an obstacle is located along a projected path of the outbound sensor signal. Such a determination can be made using one or more maps, such as a terrain map and/or a static obstacle map. Responsive to determining that an obstacle is located along the projected path of the outbound sensor signal, a driving maneuver for the vehicle relative to the obstacle can be determined. The vehicle can be caused to implement the determined driving maneuver.

Abstract: Ray tracing and static obstacle maps can be used in the operation of a vehicle. Sensor data of at least a portion of an external environment of the vehicle can be acquired. A dynamic obstacle in the external environment of the vehicle can be detected based on the acquired sensor data. In response to detecting a dynamic obstacle, it can be determined whether a secondary occluded area is located behind the dynamic obstacle relative to a current location of the vehicle based on a static obstacle map. Responsive to determining that a secondary occluded area is located behind the dynamic obstacle relative to a current location of the vehicle based on a static obstacle map, a driving maneuver for the vehicle can be determined based on at least the dynamic obstacle and the secondary occluded area. The vehicle can be caused to implement the determined driving maneuver.

Abstract: Obstacles located in an external environment of a vehicle can be classified. At least a portion of the external environment can be sensed using one or more sensors to acquire sensor data. An obstacle candidate can be identified based on the acquired sensor data. An occlusion status for the identified obstacle candidate can be determined. The occlusion status can be a ratio of acquired sensor data for the obstacle candidate that is occluded to all acquired sensor data for the obstacle candidate. A classification for the obstacle candidate can be determined based on the determined occlusion status. A driving maneuver for the vehicle can be determined at least partially based on the determined classification for the obstacle candidate. The vehicle can be caused to implement the determined driving maneuver. The vehicle can be an autonomous vehicle.

Abstract: Disclosed is a route evaluation device that enables traveling along a route in consideration of an operation of the driver of another vehicle, and can realize a safer traffic environment. A route evaluation device includes a route candidate generation section that generates route candidates of a host-vehicle, a route prediction section that predicts routes of another vehicle, a classification section that classifies the interference states of the route candidates of the host-vehicle and the predicted routes of another vehicle into a plurality of interference forms, and a route evaluation section that evaluates the routes of the host-vehicle on the basis of the interference forms classified by the classification section.

Abstract: Provided is a driving assist device 10 that recognizes an object in the vicinity of a moving body, and assists a driver in driving the moving body, the apparatus including: an object detecting unit 12 that detects the object in the vicinity of the moving body; a three dimensional object detecting unit 13 that detects a three dimensional object in the vicinity of the moving body; and an object recognition unit 18 that recognizes the object at a predetermined detection position as a non-obstacle when the object information storing unit 16 stores the position of the object, and the three dimensional object information storing unit 17 does not store the position of the three dimensional object at the predetermined position in which detection is performed by both of the object detecting unit 12 and the three dimensional object detecting unit 13.

Abstract: Disclosed is a route evaluation device that enables traveling along a route in consideration of an operation of the driver of another vehicle, and can realize a safer traffic environment. A route evaluation device includes a route candidate generation section that generates route candidates of a host-vehicle, a route prediction section that predicts routes of another vehicle, a classification section that classifies the interference states of the route candidates of the host-vehicle and the predicted routes of another vehicle into a plurality of interference forms, and a route evaluation section that evaluates the routes of the host-vehicle on the basis of the interference forms classified by the classification section.