A collision avoidance apparatus includes a travelling state calculation section, a target detection section, a target state calculation section, a lateral moving object determination section, a collision determination section, and a collision avoidance control section. The collision avoidance control section calculates, based on (i) a passing-through period of the lateral moving object in which the lateral moving object passes through an own vehicle course that is a moving course of the own vehicle and (ii) a reaching time of the own vehicle that is a period remaining before the own vehicle reaching a lateral moving object course that is a moving course of the lateral moving object, an operation timing of the brakes for the lateral moving object passing through the own vehicle course before the own vehicle reaches the lateral moving object course, and operates the brakes at the calculated operation timing of the brakes.

A collision avoidance system for a subject vehicle. The system includes a secondary vehicle detection module that, based on at least one of inputs from sensors of the subject vehicle or a message transmitted by a secondary vehicle, detects the following: location, speed, and heading of the secondary vehicle, and whether the secondary vehicle intends to turn or change lanes. A warning module warns an operator of the subject vehicle of the secondary vehicle and the identified intention of the secondary vehicle, and modifies warning intensity based on the detected intention of the secondary vehicle to turn or change lanes. An adaptive cruise control module modifies at least one of speed and heading of the subject vehicle based on the detected intention of the secondary vehicle to turn or change lanes.

The disclosure provides a vehicle control system capable of mitigating the impact when an object collides with a vehicle by exerting active driving control on the vehicle, and capable of protecting an occupant. In a vehicle control system, a driving control part includes a relative speed calculating part which detects an advancing direction of an object approaching the vehicle and calculates a relative speed between the vehicle and the object approaching the vehicle, and an acceleration control part which, based on the relative speed, a position of the object, and the advancing direction of the object approaching the vehicle, in a case where it is determined that the object is going to collide with the vehicle, performs acceleration control to exert driving control which accelerates the vehicle in the advancing direction, so as to reduce the relative speed calculated by the relative speed calculating part.

An autonomous vehicle configured for active sensing may also be configured to weigh expected information gains from active-sensing actions against risk costs associated with the active-sensing actions. An example method involves: (a) receiving information from one or more sensors of an autonomous vehicle, (b) determining a risk-cost framework that indicates risk costs across a range of degrees to which an active-sensing action can be performed, wherein the active-sensing action comprises an action that is performable by the autonomous vehicle to potentially improve the information upon which at least one of the control processes for the autonomous vehicle is based, (c) determining an information-improvement expectation framework across the range of degrees to which the active-sensing action can be performed, and (d) applying the risk-cost framework and the information-improvement expectation framework to determine a degree to which the active-sensing action should be performed.

Systems and methods are provided for controlling an autonomous vehicle (AV). A map generator module processes sensor data to generate a world representation of a particular driving scenario (PDS). A scene understanding module (SUM) processes navigation route data, position information and a feature map to define an autonomous driving task (ADT), and decomposes the ADT into a sequence of sub-tasks. The SUM selects a particular combination of sensorimotor primitive modules (SPMs) to be enabled and executed for the PDS. Each one of the SPMs addresses a sub-task in the sequence. A primitive processor module executes the particular combination of the SPMs such that each generates a vehicle trajectory and speed (VTS) profile. A selected one of the VTS profiles is then processed to generate the control signals, which are then processed at a low-level controller to generate commands that control one or more of actuators of the AV

A collision mitigation apparatus configured to mitigate a shock to an occupant of a vehicle when a rearward vehicle collides into the vehicle from behind, including a driving unit generating a driving force, and an electronic control unit having a microprocessor and a memory. The microprocessor is configured to perform predicting whether the rearward vehicle collides into the vehicle, and controlling the driving unit so that when it is predicted that the rearward vehicle collides into the vehicle, a difference between a vehicle speed of the vehicle and a vehicle speed of the rearward vehicle reduces and a driving force of a rear wheel is greater than a driving force of a front wheel immediately before the rearward vehicle collides into the vehicle.

In a vehicle-to-everything (V2X) environment and by a self-vehicle, methods and systems therefor, the methods comprising calculating a safety relevance value of a sensor detected road user or calculating a first movement similarity between the self-vehicle and a road user ahead or behind the self-vehicle and a second movement similarity between a sensor detected road user and a road user ahead or behind the sensor detected road user, and adjusting Dynamic Congestion Control (DCC) triggering condition parameters based on the calculated safety relevance value or based on the calculated first and/or second movement similarities.

The disclosure includes embodiments of a lane change timing indicator for a connected vehicle. In some embodiments, a method includes determining a time and a path for an ego vehicle to change lanes. In some embodiments, the method includes displaying, on an electronic display device of the ego vehicle, one or more graphics that depict the time and the path.

A collision avoidance apparatus includes a travelling state calculation section, a target detection section, a target state calculation section, a lateral moving object determination section, a collision determination section, and a collision avoidance control section. The collision avoidance control section calculates, based on (i) a passing-through period of the lateral moving object in which the lateral moving object passes through an own vehicle course that is a moving course of the own vehicle and (ii) a reaching time of the own vehicle that is a period remaining before the own vehicle reaching a lateral moving object course that is a moving course of the lateral moving object, an operation timing of the brakes for the lateral moving object passing through the own vehicle course before the own vehicle reaches the lateral moving object course, and operates the brakes at the calculated operation timing of the brakes.

Techniques are described herein for determining one or more actions for an autonomous vehicle to perform, based on simulation of at least one possible scenario. A possible scenario may involve, for example, the autonomous vehicle interacting with an object in the environment. The possible scenario may be simulated by modifying a first internal map containing information about the autonomous vehicle and the environment. As part of the simulation, one or more parameters of the first internal map can be modified in order to, for example, determine the state of the object at a particular point in the future. Based on the modification of the one or more parameters, a second internal map representing a possible scenario is generated from the first internal map. Both the first internal map and the second internal map can be evaluated to decide which action to take.