Techniques are provided for autonomous vehicle operation using linear temporal logic. The techniques include using one or more processors of a vehicle to store a linear temporal logic expression defining an operating constraint for operating the vehicle. The vehicle is located at a first spatiotemporal location. The one or more processors are used to receive a second spatiotemporal location for the vehicle. The one or more processors are used to identify a motion segment for operating the vehicle from the first spatiotemporal location to the second spatiotemporal location. The one or more processors are used to determine a value of the linear temporal logic expression based on the motion segment. The one or more processors are used to generate an operational metric for operating the vehicle in accordance with the motion segment based on the determined value of the linear temporal logic expression.

A method for predicting traffic light information by using a LIDAR is provided. The method includes steps of: (a) on condition that each of metadata has been allocated for each of virtual boxes included in a region covered by the LIDAR, obtaining, by a server, at least part of start timing information and stop timing information of a plurality of vehicles for each of the virtual boxes; and (b) predicting, by the server, each of pieces of the traffic light information respectively corresponding to each of the virtual boxes by referring to at least part of the start timing information and the stop timing information of the vehicles for each of the virtual boxes.

A vehicle collision avoidance assist apparatus keeps stopping a collision avoidance control when a forbiddance condition is satisfied, and a collision condition is satisfied. The forbiddance condition is a condition that the collision angle is equal to or greater than a predetermined collision angle threshold. The collision condition is a condition that an own vehicle is going to collide with an object. While the own vehicle turns, the apparatus acquires an own vehicle turning angle which the own vehicle has turned about a turning center from when the own vehicle starts turning and sets the predetermined collision angle threshold such that the predetermined collision angle threshold set for the greater own vehicle turning angle is smaller than the predetermined collision angle threshold set for the smaller own vehicle turning angle.

A vehicle collision avoidance assist apparatus keeps stopping a collision avoidance control to avoid a collision of an own vehicle with an object ahead of the own vehicle when the own vehicle turns, a predetermined condition is satisfied, and a collision condition is satisfied. While the own vehicle turns, the apparatus acquires an own vehicle turning angle which is an angle which the own vehicle has turned about a turning center from when the own vehicle starts turning and change the predetermined condition, depending on the own vehicle turning angle.

A method for providing a positive decision signal for a vehicle which is about to perform a traffic scenario action. The method includes receiving information about at least one surrounding road user, which information is indicative of distance to the surrounding road user with respect to the vehicle and at least one of speed and acceleration of the surrounding road user; calculating a value based on the received information; providing the positive decision signal to perform the traffic scenario action when the calculated value is fulfilling a predetermined condition. The value is calculated based on an assumption that the surrounding road user will react on the traffic scenario action by changing its acceleration.

A vehicle control system is provided that includes a control unit that can be disposed onboard a vehicle to control movement of the vehicle; and one or more transceiver devices that can emit plural signals from the vehicle, with at least one of the plural signals containing a vehicle identifier, and, responsive to a receiver unit disposed off-board the vehicle receiving at least one of the plural signals, the control unit can determine a location of the vehicle and can communicate a signal to the one or more transceiver devices based on the location. The control unit can change the movement of the vehicle based on the vehicle location information.

A system comprising a computer including instructions to collect object data about each of a plurality of objects within a zone from sensors on a roadside infrastructure unit. The zone includes a road intersection. The object data includes an object type, an object location, an object speed and an object direction of travel for each object. The computer further includes instructions to determine, based on the object data, an availability level for execution of one or more paths through the road intersection by a vehicle wherein the availability level for each of the one or more paths is based on a likelihood of interference between any of the objects and the vehicle as the vehicle traverses the respective path. The computer further includes instructions to transmit an availability message to the vehicle including the availability level for each of the one or more paths.

Method and systems for generating vehicle motion planning model simulation scenarios are disclosed. The method receives a base simulation scenario with features of a scene through which a vehicle may travel, defines an interaction zone in the scene, generates an augmentation element that includes an object and a behavior for the object, and adds the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario. The augmented simulation scenario is applied to a vehicle motion planning model to train the model.

A computer system for planning mobile robot trajectories, the computer system comprising: an input configured to receive a set of scenario description parameters describing a scenario and a desired goal for the mobile robot therein; a runtime optimizer configured to compute a final mobile robot trajectory that substantially optimizes a cost function for the scenario, subject to a set of hard constraints that the final mobile robot trajectory is guaranteed to satisfy; and a trained function approximator configured to compute, from the set of scenario description parameters, initialization data defining an initial mobile robot trajectory. The computer system is configured to initialize the runtime optimizer with the initialization data, in order to guide the optimizer from the initial mobile robot trajectory to the final mobile robot trajectory that satisfies the hard constraints, the function approximator having been trained on example sets of scenario description parameters and ground truth initialization data for the example sets of scenario description parameters.

A driving assistance device configured to execute deceleration assistance for a driver's vehicle when the driver's vehicle turns right or left at an intersection is configured to recognize, based on a detection result from an external sensor of the driver's vehicle, an adjacent vehicle traveling in an adjacent lane adjacent to a traveling lane of the driver's vehicle, determine whether the adjacent vehicle turns in the same direction of the driver's vehicle at the intersection based on the detection result from the external sensor when the adjacent vehicle is recognized and the driver's vehicle turns right or left at the intersection, and execute the deceleration assistance to cause a vehicle-to-vehicle distance between the driver's vehicle and the adjacent vehicle to reach a distance equal to or larger than a target driver's vehicle-to-adjacent vehicle distance when the driving assistance device determines that the adjacent vehicle turns in the same direction.