A system and method for estimating and communicating a path of travel of a reference vehicle by road side equipment (RSE) that includes establishing communication between the RSE and an on-board equipment of the reference vehicle and receiving vehicle parameters of the reference vehicle from the on-board of the reference vehicle. The system and method also include estimating the path of travel of the reference vehicle based on the vehicle parameters of the reference vehicle and environmental parameters determined by the RSE. The system and method further include establishing communication between the RSE and an on-board equipment of a target vehicle and communicating the estimated path of travel of the reference vehicle from the RSE to the target vehicle, wherein a probability of collision between the reference vehicle and the target vehicle is determined based on the estimated path of travel of the reference vehicle.

A driving assist device includes a first sensor, a second sensor, and a control device. The control device does not execute an inter-vehicle distance control under a predetermined first condition upon determination that at least one preceding object is detected based on the output of one of the first sensor and the second sensor without being detected based on the output of the other of the first and second sensors; and an environment of a non-detection sensor that is the other of the first and second sensors satisfies a first requirement for determination of a reliability of the output of the non-detection sensor; and the control device executes the inter-vehicle distance control under a predetermined second condition upon determination that the environment of the non-detection sensor satisfies a second requirement for determination of the reliability of the output of the non-detection sensor.

An autonomous vehicle can obtain sensor data. Upon determining that the autonomous vehicle is in a lane adjacent a shoulder, and there is an object in the shoulder, the autonomous vehicle can determine if performing a lane change maneuver out of the lane prior to the autonomous vehicle being positioned adjacent to the object is feasible. If it is, the lane change maneuver can be performed. If it is not, a nudge maneuver and/or a deceleration can be performed.

The present disclosure relates to a method and system for integrated path planning and path tracking control of an autonomous vehicle. The method includes: obtaining five input control variables and eleven system state variables of an autonomous vehicle at current time; constructing a vehicle path planning-tracking integrated state model according to the obtained variables at the current time; enveloping external contours of two autonomous vehicles using elliptical envelope curves to determine elliptical vehicle envelope curves of the two autonomous vehicles, respectively; determining time to collision (TTC) between the vehicles according to elliptical vehicle envelope curves and vehicle driving states; establishing an objective function of a model prediction controller (MPC) according to the model; and solving the objective function based on the TTC, and determining input control variables to the MPC at the next time. Autonomous vehicle collision avoidance can be achieved according to the present disclosure.

Systems and methods are provided to provide a steering indicator to a driver of a vehicle. It is determined whether a first obstacle is in a forward path of the vehicle and whether a second obstacle is present at a side of the vehicle. In response to (a) determining the first obstacle is in the forward path and (b) determining whether the second obstacle is present at the one or more sides of the vehicle, a suggested steering action indicator indicating one or more movements for the vehicle to avoid the first obstacle is provided to a user interface of the vehicle.

A system for providing an alert to an occupant of a vehicle may include one or more processors and a memory. The memory may store a free space detection module, a target detection module, a path prediction module, an activation threshold module, and an alert module. The modules include instructions that cause the one or more processors to determine one or more dimensions of a free space located adjacent to a side of the vehicle, determine one or more dimensions of one or more targets, determine one or more predicted paths of one or more targets, selectively adjust an activation threshold for providing an alert according to the one or more predicted paths, and activate the alert to inform the occupant of a hazard associated with the one or more targets according to whether the one or more predicted paths satisfies the activation threshold.

A method for controlling a vehicle including: based on map information including information of an installation position of a traffic light and information of a lane controlled by the traffic light and a range of the angle of view of a camera mounted on the own vehicle, calculating an imaging-enabled area in which an image of the traffic light can be captured on the lane by the camera; determining whether or not the own vehicle is positioned in the imaging-enabled area; and when the own vehicle is positioned in the imaging-enabled area, controlling the own vehicle in such a way that the traffic light is not shielded from the range of the angle of view of the camera by a preceding vehicle of the own vehicle.

A lateral virtual boundary for a host vehicle is identified based on a lateral distance between the host vehicle and a target vehicle, a longitudinal distance between the host vehicle and the target vehicle, and a speed of the target vehicle relative to the host vehicle. A forward virtual boundary for the host vehicle is identified based on the longitudinal distance between the host vehicle and the target vehicle. A lateral constraint value of the lateral virtual boundary and a forward constraint value of the forward virtual boundary are determined. A longitudinal acceleration and a steering angle are determined based on the lateral and forward virtual boundaries and the lateral and forward constraint values. One or both of a steering component or a brake are actuated based on the longitudinal acceleration and the steering angle.

Examples relating to vehicle velocity calculation using radar technology are described. An example method performed by a computing system may involve, while a vehicle is moving on a road, receiving, from two or more radar sensors mounted at different locations on the vehicle, radar data representative of an environment of the vehicle. The method may involve, based on the data, detecting at least one scatterer in the environment. The method may involve making a determination of a likelihood that the at least one scatterer is stationary with respect to the vehicle. The method may involve, based on the determination being that the likelihood is at least equal to a predefined confidence threshold, calculating a velocity of the vehicle based on the data from the sensors. The calculated velocity may include an angular and linear velocity. Further, the method may involve controlling the vehicle based on the calculated velocity.

In some aspects, a safety system may be configured to receive vehicle position data indicating a position of a vehicle, determine a first lane segment in a lane coordinate system based on the vehicle position data, the first lane segment being a lane segment in which the vehicle is located, determine a relevant set of lane segments based on a safety-range from the first lane segment, determine or receive obstacle position data indicating a second lane segment in the lane coordinate system, the second lane segment being a lane segment in which an obstacle is located, and classify the obstacle either as a non-relevant obstacle in the case that the second lane segment is not included in the relevant set of lane segments, or as a relevant obstacle in the case that the second lane segment is included in the relevant set of lane segments.