A method detects a risk of collision between a motor vehicle and a secondary object located in traffic lanes adjacent to the main traffic lane of the vehicle, in the event of a lane change by the vehicle, which involves detecting objects in a predetermined danger zone, and estimating a time-to-collision between the vehicle and a detected object. Detecting objects in a danger zone involves: calculating the actual distance between the vehicle and each object detected by the radar, the actual distance corresponding to the length of an arc between two points; determining a danger zone as a function of lines of the main traffic lane and a width of the main traffic line; and checking, for each object detected by the radar, whether its coordinates are inside the predetermined danger zone.

A method detects a risk of collision between a motor vehicle and a secondary object located in traffic lanes adjacent to the main traffic lane of the vehicle, in the event of a lane change by the vehicle, which involves detecting objects in a predetermined danger zone, and estimating a time-to-collision between the vehicle and a detected object. Detecting objects in a danger zone involves: calculating the actual distance between the vehicle and each object detected by the radar, the actual distance corresponding to the length of an arc between two points; determining a danger zone as a function of lines of the main traffic lane and a width of the main traffic line; and checking, for each object detected by the radar, whether its coordinates are inside the predetermined danger zone.

A method for a vehicle, in particular a vehicle which is operated in an at least partially automated manner, for detecting an impact event. The method includes of: a. developing a driving environment model for the vehicle as a function of first sensor signals from at least one driving environment sensor system of the vehicle; b. using the driving environment model to determine a probability of contacting an object; c. opening a measurement window for second signals of a contact sensor system as a function of the determined contact probability; d. detecting an impact event as a function of the second sensor signals, in particular within the measurement window.

A moving body control apparatus includes a travel control section that controls travel of a moving body based on vicinity information, and a lane change control section that performs a lane change of the moving body from a first lane to a second lane, if the lane change of the moving body from the first lane to the second lane is approved. The travel control section performs first acceleration/deceleration control to accelerate or decelerate the moving body according to a velocity of another moving body travelling in the second lane, if the lane change of the moving body from the first lane to the second lane is denied.

A system for preventing abnormal acceleration of a vehicle includes a device configured such that in a state in which the vehicle is stopped while the vehicle is turned on, the device is configured to determine whether abnormal acceleration prevention is necessary based on a final destination or a current position of the vehicle before the vehicle is turned off to thereby limit a vehicle speed. The system and a method for preventing abnormal operation of the vehicle can prevent a vehicle accident due to the abnormal acceleration caused by misoperation by a driver, such as misoperation of an accelerator pedal of the vehicle.

A method for determining information related to a lane change of a target vehicle includes obtaining information related to an environment of the target vehicle. The information related to the environment relates to a plurality of features of the environment of the target vehicle. The plurality of features are partitioned into two or more groups of features. The method further determines two or more weighting factors for the two or more groups of features. An attention mechanism is used for determining the two or more weighting factors. The method further determines the information related to the lane change of the target vehicle based on the information related to the environment of the target vehicle using a machine-learning network. A weighting of the plurality of features of the environment of the target vehicle within the machine-learning network is based on the two or more weighting factors for the two or more groups of features.

The application disclose an autonomous-driving-based control method performed by a computer device. The method includes: acquiring scene information of a target vehicle; determining a current lane changing scene type of the target vehicle according to the scene information; recognizing, when the current lane changing scene type is a mandatory lane changing scene type, a first lane for completing a navigation travel route, and, when the first lane satisfies a lane changing safety check condition, controlling the target vehicle to perform lane changing operation according to the first lane. The second lane for optimizing the travel time is recognized according to the scene information when the current lane changing scene type is the free lane changing scene type. When the second lane satisfies the lane changing safety check condition, the target vehicle is controlled to perform lane changing operation according to the second lane.

A computer-implemented method comprises: generating first output using a first sensor of a vehicle comprising an infrared camera or an event-based sensor, the first output indicating a portion of surroundings of the vehicle; providing the first output to a LiDAR of the vehicle having a field of view (FOV); configuring a resolution of the LiDAR based at least in part on the first output; generating a representation of at least part of the surroundings of the vehicle using the LiDAR; providing, to a perception component of the vehicle, second output of a second sensor of the vehicle and third output of the LiDAR, the perception component configured to perform object detection, sensor fusion, and object tracking regarding the second and third outputs, wherein the first output bypasses at least part of the perception component; and performing motion control of the vehicle using a fourth output of the perception component.

A vehicle and a system method of operating the vehicle is disclosed. The system includes a monitoring module and a mitigation module operating on a processor. The monitoring module is configured to measure a degradation in an operation parameter of the vehicle, the vehicle operating in a first state based on a first value of a set of adaptive parameters. The mitigation module is configured to determine a threat to the vehicle due to operating the vehicle in the first state with the degradation in the operation parameter and adjust the set of adaptive parameters from the first value to a second value that mitigates the threat to the vehicle, wherein the processor operates the vehicle in a second state based on the second value.

Methods and systems for controlling navigation of a vehicle are disclosed. The system will first detect a URU within a threshold distance of a drivable area that a vehicle is traversing or will traverse. The system will then receive perception information relating to the URU, and use a plurality of features associated with each of a plurality of entry points on a drivable area boundary that the URU can use to enter the drivable area to determine a likelihood that the URU will enter the drivable area from that entry point. The system will then generate a trajectory of the URU using the plurality of entry points and the corresponding likelihoods, and control navigation of the vehicle while traversing the drivable area to avoid collision with the URU.