A prediction method and apparatus for an autonomous driving manual takeover, and a system are provided. One example method includes: A first vehicle sends a first message to a second vehicle when detecting that the first vehicle has a manual takeover requirement, where the first message includes information about a first location of the first vehicle, and the information about the first location is used to indicate a location of the first vehicle when the first vehicle detects that the first vehicle has the manual takeover requirement.

The present disclosure relates to a method for operating an assistance system of a motor vehicle, wherein the assistance system has a projector. A message relating to a wrong-way driver is received, and a position of the wrong-way driver transmitted with the message is compared with a current position. Depending on the comparison, a recommendation for adapting a driving parameter is projected into an area in front of the motor vehicle for the driver by means of the projector. The present disclosure also relates to an assistance system of a motor vehicle and to a motor vehicle.

A method for operating a first vehicle (100) with a parking assistance system (110) is proposed, comprising: a) sensing an obstructing parked position (BP) of the first vehicle (100) by means of the parking assistance system (110), wherein the obstructing parked position (BP) is a parked position which adjoins a parking space (PP) occupied by a parked second vehicle (150), b) reception of a sensor signal, acquired by a sensor apparatus (120, 130) of the vehicle (100), by means of the parking assistance system (110), c) detecting a request to exit a parking space of the parked second vehicle (150) in accordance with the received sensor signal by means of the parking assistance system (110), and d) autonomously driving the first vehicle (100) from the obstructing parked position (BP) into a position which is different from the obstructing parked position (BP) in accordance with the detected request to exit a parking space by means of the parking assistance system (110).

A traffic warning method and apparatus includes: obtaining driving status information of a dangerous vehicle on a target road and pavement status information of the target road; determining potential collision strength of the dangerous vehicle against a first vehicle according to driving status information of the first vehicle on the target road, the driving status information of the dangerous vehicle, and the pavement status information of the target road; correcting the potential collision strength of the dangerous vehicle against the first vehicle according to a difference between a performance parameter of the dangerous vehicle and a performance parameter of a non-dangerous vehicle on the target road; and performing traffic warning according to the corrected potential collision strength of the dangerous vehicle against the first vehicle.

Erroneous detection due to erroneous parallax measurement is suppressed to accurately detect a step present on a road. An in-vehicle environment recognition device 1 includes a processing device that processes a pair of images acquired by a stereo camera unit 100 mounted on a vehicle. The processing device includes a stereo matching unit 200 that measures a parallax of the pair of images and generates a parallax image, a step candidate extraction unit 300 that extracts a step candidate of a road on which the vehicle travels from the parallax image generated by the stereo matching unit 200, a line segment candidate extraction unit 400 that extracts a line segment candidate from the images acquired by the stereo camera unit 100, an analysis unit 500 that performs collation between the step candidate extracted by the step candidate extraction unit 300 and the line segment candidate extracted by the line segment candidate extraction unit 400 and analyzes validity of the step candidate based on the collation result and an inclination of the line segment candidate, and a three-dimensional object detection unit 600 that detects a step present on the road based on the analysis result of the analysis unit 500.

A vehicle sets a first determination region of a first obstacle and a second determination region, on the basis of a position of the first obstacle. The second determination region is located at a position farther than the first determination region. A reliability of the second obstacle is set to a first reliability in a case where a position of a second obstacle falls outside the first determination region and falls outside the second determination region. The reliability of the second obstacle is set to a second reliability higher than the first reliability in a case where the position of the second obstacle falls within the first determination region or falls within the second determination region. Braking is applied to the vehicle body and/or acceleration of the vehicle body is suppressed, on the basis of the reliability of the second obstacle and the position of the second obstacle.

An example operation includes one or more of determining a level of risk of a collision of a transport, wherein the level of risk is related to an occupant of the transport and an environment of the transport, accumulating an amount of data based on the level of risk, preparing the accumulated data for sending to one or more recipients when the level of risk exceeds a risk threshold, and sending the prepared data to the one or more recipients when the collision occurs.

Systems and methods for vehicle lane change control are described. Some implementations may include determining a kinematic state of a vehicle moving in an origin lane; detecting, based on data from one or more sensors of the vehicle, objects that are moving in a target lane of the road; determining a headway constraint in terms of a preparation time, a preparation acceleration to be applied to the vehicle during the preparation time, and an execution time during which the vehicle is to transition from the origin lane to the target lane; determining values of the preparation time, the execution time, and the preparation acceleration subject to a set of constraints including the headway constraint; and determining a motion plan that will transition the vehicle from the origin lane to the target lane based at least in part on the preparation time, the execution time, and the preparation acceleration.

Systems and methods for monitoring the lane of an object in an environment of an autonomous vehicle are disclosed. The methods include receiving sensor data corresponding to the object, and assigning an instantaneous probability to each of a plurality of lanes based on the sensor data as a measure of likelihood that the object is in that lane at a current time. The methods also include generating a transition matrix for each of the plurality of lanes that encode one or more probabilities that the object transitioned to that lane from another lane in the environment or from that lane to another lane in the environment at the current time. The methods then include determining an assigned probability associated with each of the plurality of lanes based on the instantaneous probability and the transition matrix as a measure of likelihood of the object occupying that lane at the current time.

Systems and methods for monitoring the lane of an object in an environment of an autonomous vehicle are disclosed. The methods include receiving sensor data corresponding to the object, and assigning an instantaneous probability to each of a plurality of lanes based on the sensor data as a measure of likelihood that the object is in that lane at a current time. The methods also include generating a transition matrix for each of the plurality of lanes that encode one or more probabilities that the object transitioned to that lane from another lane in the environment or from that lane to another lane in the environment at the current time. The methods then include determining an assigned probability associated with each of the plurality of lanes based on the instantaneous probability and the transition matrix as a measure of likelihood of the object occupying that lane at the current time.