In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.

An autonomous vehicle (AV) includes features that allows the AV to comply with applicable regulations and statutes for performing safe driving operation. Example embodiments relate to an autonomous vehicle having a trailer coupled to a rear thereof. An example method includes continuously predicting a trailer trajectory that is distinct from a planned trajectory of the autonomous vehicle. The method further includes determining that the predicted trailer trajectory is within a minimum avoidance distance away from a stationary vehicle located on a roadway on which the autonomous vehicle is located. The method further includes modifying the planned trajectory of the autonomous vehicle such that the predicted trailer trajectory satisfies the minimum avoidance distance. The method further includes causing the autonomous vehicle to navigate along the modified trajectory based on transmitting instructions to one or more subsystems of the autonomous vehicle.

An automatic reverse driving controller includes a control unit. The control unit includes a traveling information input unit, a traveling information storage unit, an automatic reverse traveling instruction input unit, and a processing unit. The traveling information input unit inputs information on a traveling trajectory of the vehicle and a road surface condition.

The traveling information storage unit stores the inputted information on the traveling trajectory and the road surface condition. The automatic reverse traveling instruction input unit receives an input of an instruction to switch from traveling by a driving operation of a driver of the vehicle to automatic reverse traveling by the control unit. The processing unit corrects, in response to the input of the instruction, a traveling trajectory of an outward route on the basis of the road surface condition to determine a traveling route for a return route, and control reverse traveling of the vehicle.

A computer-implemented method performed in a vehicle control unit for controlling motion of a heavy-duty vehicle. The method includes obtaining a vehicle motion request, wherein the vehicle motion request is indicative of a target curvature and a target acceleration, determining a motion support device, MSD, control allocation based on the vehicle motion request, determining a dynamic wheel slip angle limit based on the vehicle motion request, where dynamic wheel slip angle limit increases with a decreasing target acceleration, and controlling the motion of the heavy-duty vehicle based on the MSD control allocation constrained by the dynamic wheel slip angle limit.

A parallel computing method for man-machine coordinated steering control of a smart vehicle based on risk assessment is provided, comprising the following steps: building a lateral kinetic equation model of a vehicle; building a target function by targeting at minimizing an offset distance of a vehicle driving track from a lane center line and making a change in a front wheel steering angle and a longitudinal acceleration as small as possible in a driving process; building a parallel computing architecture of a prediction model and the target function, and employing a triggering parallel computing method; solving and computing a gradient with a manner of back propagation and using a gradient descent method to obtain an optimal control amount of the front wheel steering angle and an optimal control amount of the longitudinal acceleration; and computing a driving weight, obtaining a desired front wheel steering angle and completing real time control.

A vehicle control device of an embodiment includes a recognizer configured to recognize a surrounding situation of a vehicle, and a driving controller configured to execute driving control of controlling one or both of a speed and steering of the vehicle on the basis of the surrounding situation recognized by the recognizer, in which the recognizer recognizes a traffic participant present in front of the vehicle and a traffic participant priority section present in a traveling direction of the vehicle, and the driving controller sets a risk area for the traffic participant priority section on the basis of a position and a traveling direction of the traffic participant, and executes the driving control based on the set risk area and the position of the traffic participant.

A refuse vehicle comprising a chassis, a body assembly coupled to the chassis, the body assembly defining a refuse compartment, one or more sensors coupled to the body and configured to provide data relating to the presence of an obstacle within an area near the refuse vehicle, a controller configured to receive the data from the one or more sensors, determine, using an obstacle detector and the data, the presence of an obstacle within the area and initiate a control action, wherein the control action includes at least one of controlling the movement of the refuse vehicle, controlling the movement of a lift assembly attached to the body assembly, or generating an alert.

A proximity-detection and speed-control system for a materials-handling vehicle, such as a lift truck, is provided with a recommended direction of travel for the vehicle. A proximity sensor is provided to determine the vehicle's proximity to a restricted member, such as another vehicle, a high-value object, a dangerous location, or a pedestrian. If the vehicle is traveling in the recommended direction of travel, the speed control function is disabled. If, however, the vehicle is not travelling in the recommended direction and the proximity sensor indicates the vehicle is within a restricted distance of the restricted member, the speed control function is triggered to restrict the maximum speed of travel of the vehicle and to slow the vehicle if needed.

Systems and methods for basis path generation are provided. In particular, a computing system can obtain a target nominal path. The computing system can determine a current pose for an autonomous vehicle. The computing system can determine, based at least in part on the current pose of the autonomous vehicle and the target nominal path, a lane change region. The computing system can determine one or more merge points on the target nominal path. The computing system can, for each respective merge point in the one or more merge points, generate a candidate basis path from the current pose of the autonomous vehicle to the respective merge point. The computing system can generate a suitability classification for each candidate basis path. The computing system can select one or more candidate basis paths based on the suitability classification for each respective candidate basis path in the plurality of candidate basis paths.

A communication system that determines a context and an intent of a specific remote vehicle located in a surrounding environment of a host vehicle includes one or more controllers for receiving sensed perception data including sensed perception data. The one or more controllers execute instructions to determine a plurality of vehicle parameters related to the specific remote vehicle. The the one or more controllers execute instructions to associate the specific remote vehicle with a specific lane of travel of a roadway based on map data. The one or more controllers determines possible maneuvers, possible egress lanes, and a speed limit for the specific remote vehicle for the specific lane of travel based on the map data, and determines the context and the intent of the specific remote vehicle based on the plurality of vehicle parameters, the possible maneuvers, the possible egress lanes for the specific remote vehicle, and the speed limit related to the specific remote vehicle.