A navigation system for a host vehicle is provided. The system may comprise at least one processing device comprising circuitry and a memory. The memory includes instructions that when executed by the circuitry cause the at least one processing device to: receive a plurality of images acquired by a camera, the plurality of images being representative of an environment of the host vehicle; analyze the plurality of images to identify a presence in the environment of the host vehicle a navigation rule suspension condition; temporarily suspend at least one navigational rule in response to identification of the navigation rule suspension condition; and cause at least one navigational change of the host vehicle unconstrained by the temporarily suspended at least one navigational rule.

Provided is a preceding vehicle determining device including: a signal acquisition unit configured to acquire a signal from an object detection device; a border setting unit configured to set a border of a lane on which the own vehicle is traveling; a determination area setting unit configured to set a preceding vehicle determination area being an area forward of the own vehicle based on at least one piece of information out of vehicle type information, device type information, detection state information, or preceding vehicle information being information on a vehicle set as a preceding vehicle in previous processing, and based on the border set by the border setting unit; and a preceding vehicle determining unit configured to determine whether the another vehicle is to be set as the preceding vehicle based on a position of the another vehicle with respect to the preceding vehicle determination area.

The disclosure provides an obstacle avoidance control method and device, an advanced driver-assistance system, a vehicle, and a medium. The method includes the steps of: receiving vehicle sensor data; calculating an obstacle safe boundary and a lane safe boundary based on the vehicle sensor data; and determining a passing region and a passing status for a current vehicle according to the obstacle safe boundary and the lane safe boundary.

Techniques are described that enable automatic emergency braking (AEB) for a path-crossing target when a collision between a host vehicle and the target that is deemed imminent. Based on whether an acceleration of the host vehicle is above a threshold. Based on the acceleration, and, optionally, a location of the target relative to a crossing path (e.g., whether a portion of the target is within a suppression zone), an AEB system of the host vehicle is either activated or not activated, for example, suppressed. This suppression of the AEB system may include gating or nulling an AEB activation signal to prevent an emergency braking event. By managing the AEB system in a path-crossing scenario, many common false-positive AEB events (warnings, alerts, and/or braking) may be avoided. Furthermore, intentional vehicle maneuvers that comply with normal driving etiquette or rules can still be allowed for operator and passenger comfort, without risking safety.

A system and method for mitigating or avoiding risks due to hazards encountered by platooning vehicles. The system and method involve interrogating, with one or more sensors, a space radially extending from a lead vehicle as the lead vehicle travels over the road surface, perceiving the environment within the space, ascertaining a hazard caused by an object in the space, and causing a following vehicle, operating in a platoon with the lead vehicle, to take a preemptive braking action to avoid or mitigate risks resulting from the hazard caused by the object in the space.

Embodiments of the present application provide a collision detection method and apparatus based on an autonomous vehicle, a device and a storage medium, where the method includes: acquiring first point cloud data of each obstacle in each region around the autonomous vehicle, where the first point cloud data represents coordinate information of the obstacle and the first point cloud data is based on a world coordinate system; converting the first point cloud data of the each obstacle into second point cloud data based on a relative coordinate system, where an origin of the relative coordinate system is a point on the autonomous vehicle; determining, according to the second point cloud data of the each obstacle in all regions, a possibility of collision of the autonomous vehicle. A de-positioning manner for collision detection is provided, thereby improving the reliability and stability of collision detection.

A method and apparatus for controlling a vehicle are provided. A lane in which a target vehicle is driving, and an object in a vicinity of the lane are detected from an image of surroundings of the target vehicle, a degree of danger of the object is evaluated, driving information of the target vehicle is determined based on the degree of danger, and the target vehicle is controlled based on the driving information.

An approach to arrange sensors needed for automated driving, especially where semitrailer trucks are operating in an autonomous convoy with one automated or semi-automated truck following another. The sensors are fitted to a location adjacent to or within the exterior rearview mirrors, on each of the left- and right-hand side of the tractor. The sensors provide overlapping fields of view looking forward of the vehicle and to both the left and right hand sides at the same time.

There is presented a method for controlling an activation threshold of a safety system of a vehicle. The method comprises receiving map data from a remote data repository, said map data comprising a geographical location of a dynamic object located in a surrounding area of an expected path of the vehicle, determining a geographical location of the vehicle by means of a localization system of the vehicle, and lowering an activation threshold value of the safety system when the geographical location of the vehicle is within a predefined distance from the dynamic object. The presented method provides for an efficient means for preparing e.g. an emergency brake assist system of a vehicle in potentially critical situations.

A side collision risk estimation system for a vehicle comprises a speed sensor, a road line markers detector, a movement sensor, an object detector, and a controller. The controller is configured to estimate: the current speed of the vehicle, a heading of the adjacent road line ahead of the vehicle, a heading of the vehicle, a compensated heading of the vehicle, a predicted lateral change position of the vehicle, a heading of a target vehicle relative to the vehicle, the current speed of the target vehicle, the current lateral distance between the vehicles, the heading of the adjacent road line ahead of the target vehicle, a compensated relative heading of the target vehicle, a predicted lateral change position of the target vehicle, a predicted lateral distance over time between the vehicles, and a side collision risk over time from the predicted lateral distance between the vehicles.