A method for controlling a subject vehicle with a braking system, a drive system and a distance control system, wherein the distance control system is configured to control an actual following distance between the subject vehicle and a vehicle ahead to a predetermined target following distance, wherein the target following distance is predetermined as a function of an activated operating mode of the distance control system, including performing a plausibility check by checking whether V2X data is exchanged or can be exchanged between the vehicle ahead and the subject vehicle over a V2X connection, and activating, if no V2X data is exchanged or can be exchanged between the vehicle ahead and the subject vehicle over the V2X connection, a first operating mode in which a first target following distance is predetermined as a function of a reaction time of a driver of the subject vehicle.

A vehicle behavior generation device sets multiple possible behaviors of an own vehicle when the own vehicle travels along a planned route; sets multiple possible behaviors of a different vehicle existing around the own vehicle corresponding to each of the set multiple possible behaviors of the own vehicle; outputs information indicating a contact possibility between the own vehicle and the different vehicle for each of combinations of the set multiple possible behaviors of the own vehicle and the set multiple possible behaviors of the different vehicle; and selects one of the multiple possible behaviors of the own vehicle based on the outputted information.

A driving support device includes a prediction unit, a trajectory determination unit, and a necessity determination unit. The prediction unit is configured to predict an increase degree of an inter-vehicle distance between other vehicles in response to the cut-in of the subject vehicle, and determine whether the lane change is permissible based on the increase degree. The necessity determination unit is configured to determine whether a necessity level of the lane change is within an acceptable range. The prediction unit is configured to cancel the determination whether the lane change is permissible based on the increase degree when it is determined that the necessity level is within the acceptable range, and determine whether the lane change is permissible based on a linear prediction of a behavior of the other vehicles.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statues for performing safe driving operation. An example method for operating the AV includes determining a trajectory related information of a vehicle operating on a roadway on which the AV is operating; receiving sensor data of a first area that includes the vehicle; determining an additional trajectory related information for the AV by comparing the trajectory related information of the vehicle to a current trajectory related information of the AV, wherein the additional trajectory related information is based on a category to which the vehicle belongs, and wherein the additional trajectory related information allows the AV to maintain at least a distance between the AV and the vehicle; and causing the AV to operate in accordance with the additional trajectory related information.

A parking assist system comprises: a backward position determining unit for changing, upon inputting of a notification that the travel of the vehicle has stopped in a forward route, the starting point of a reverse route to the stopping point wherein travel of the vehicle has stopped, and, if the vehicle has traveled along the backward route wherein the starting point has been changed to the stopping position, identifies a backward position wherein the vehicle can be reversed; a control information generating unit for generating control information for causing the vehicle to travel from the stopping position to the backward position; and a route generating unit for generating a second parking route, for causing the vehicle to travel to the parking position, based on the state of surroundings, acquired by a state acquiring unit, when the vehicle travels to the backward route.

A trajectory for an autonomous machine may be evaluated for safety based at least on determining whether the autonomous machine would be capable of occupying points of the trajectory in space-time while still being able to avoid a potential future collision with one or more objects in the environment through use of one or more safety procedures. To do so, a point of the trajectory may be evaluated for conflict based at least on a comparison between points in space-time that correspond to the autonomous machine executing the safety procedure(s) from the point and arrival times of the one or more objects to corresponding position(s) in the environment. A trajectory may be sampled and evaluated for conflicts at various points throughout the trajectory. Based on results of one or more evaluations, the trajectory may be scored, eliminated from consideration, or otherwise considered for control of the autonomous machine.

A parking assist system comprises a route generating unit for generating a generating position for generating a parking route for parking a vehicle in a determined parking space and for generating a travel route for the vehicle to travel to the generating position; and a control information generating unit for generating control information for the vehicle to travel along the travel route by controlling a driving system 80 for causing the vehicle to travel, and for outputting the generated control information to a vehicle controlling unit for controlling the driving system, wherein: the route generating unit determines a generating position such that at least a portion of the back end of the vehicle will be positioned within a parking space, and, after the vehicle has arrived at the generating position, generates, at the generating position, a parking route for the vehicle to park in the parking space.

A controlling and warning system based on traffic conditions feedback and a method thereof are disclosed. In the controlling and warning system, a camera disposed on a rear of a vehicle body is configured to generate and transmit a rear video to a controlling host, and the controlling host identifies a vehicle object in the rear video and calculates a separation distance between the vehicle object and the vehicle body; the vehicle object is inputted into a large-sized vehicle recognition model which is built based on artificial intelligence neural network and trained completely, to recognize whether the vehicle object is a large-sized vehicle; when the vehicle object is recognized as the large-sized vehicle and the separation distance reaches to a safe distance, a warning signal is generated. Therefore, the technical effect of improving the warning immediacy of an approaching large vehicle can be achieved.

Techniques for analyzing a parameter space are discussed. Techniques may include receiving policy data for evaluating a vehicle controller. The techniques may further include determining, using a Bayesian optimization and based at least in part on the vehicle controller, parameter sets associated with adverse events. The adverse events may be associated with a violation of the policy data. The techniques may associate, based on exposure data, parameter bounds of the adverse events and probabilities of the adverse events in a driving environment. A safety metric may be determined based on the Bayesian optimization. The techniques may also include weighting an impact of an adverse event based on the safety metric.

An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.