A non-transitory computer readable storage medium has instructions executed by a processor to obtain the relative speed between a first traffic object and a second traffic object. The separation distance between the first traffic object and the second traffic object is received. The relative speed and the separation distance are combined to form a quantitative measure of hazard encountered by the first traffic object. The obtain, receive and combine operations are repeated to form cumulative measures of hazard associated with the first traffic object. The cumulative measures of hazard are analyzed to derive a first traffic object safety score for the first traffic object.

A traffic safety control method is provided. The method includes obtaining first related information of a road when a vehicle is traveling on a road. Second related information is detected using a detecting device of the vehicle when the first related information indicates that there is the intersection in front of the vehicle on the road. The vehicle is controlled according to the first related information and the second related information.

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.

A map information correction method for correcting map information includes information of a lane boundary line, the method further including: detecting a position with respect to an own vehicle of a lane boundary line set in place on a road surface around the own vehicle; estimating an own position on a map of the own vehicle; and correcting, depending on the estimated own position and the detected position of the lane boundary line, a position of the lane boundary line included in the map information by, in a first region comparatively close to the own vehicle, a larger rotational correction amount than in a second region comparatively far from the own vehicle and, in the second region, a larger translational correction amount than in the first region.

An autonomous driving system includes: at least one sensor (1) configured to collect environment information around a vehicle; a primary decision unit (21) configured to calculate decision information based on the environment information collected by the at least one sensor (1), and transmit the decision information to a controller (3); an alternative decision unit (22) configured to calculate decision information based on the environment information collected by the at least one sensor (1) in response to detecting that the primary decision unit (21) is abnormal, and transmit the decision information to the controller (3); and the controller (3) configured to calculate vehicle control information based on the received decision information, and transmit the vehicle control information to a bottom vehicle controller. In this way, the stability and reliability of the autonomous driving system can be improved and safety of autonomous driving of the vehicle can be guaranteed.

An apparatus and method for controlling lane following include acquiring front image information through a camera installed at an ego-vehicle during travel of the ego-vehicle; setting a target trajectory of the ego-vehicle using line information and travel information of a preceding vehicle extracted based on the image information; and calculating a steering torque to control steering of the ego-vehicle along the set target trajectory.

Techniques are provided which may be implemented using various methods and/or apparatuses in a vehicle to utilize vehicle external sensor data, vehicle internal sensor data, vehicle capabilities and external CV2X input to determine, send, receive and utilize data elements to determine inter-vehicle spacing, intersection priority, lane change behavior and spacing and other autonomous vehicle behavior.

A self-localization estimation unit of a self-localization estimation device determines, based on mutual relationships between the in-lane position and the absolute position including the error, whether there is lane-relevant candidate information, the lane-relevant candidate information representing that one or more in-vehicle positions are each estimated to be in which of lanes identified by the lane information; and estimates, based on a result of the determination of whether there is lane-relevant candidate information, a localization of the own vehicle corresponding to the map information.

In various examples, systems are described herein that may evaluate one or more radar detections against a set of filter criteria, the one or more radar detections generated using at least one sensor of a vehicle. The system may then accumulate, based at least on the evaluating, the one or more radar detections to one or energy levels that correspond to one or more locations of the one or more radar detections in a zone positioned relative to the vehicle. The system may then determine one or more safety statuses associated with the zone based at least on one or more magnitudes of the one or more energy levels. The system may transmit data, or take some other action, that causes control of the vehicle based at least on the one or more safety statuses.

A method for matching a reference object and a test object includes providing a test object in a field of sensing of at least one sensor disposed at a vehicle. A volume match is determined based on a volume of the reference object and a volume of the test object. A distance match is determined based on a center and orientation of the reference object and a center and orientation of the test object. An angle match is determined based on a yaw angle of the reference object and a yaw angle of the test object. A superposition of the volume match, the distance match, and the angle match is determined based on a multiplication of the volume match, the distance match, and the angle match. A degree of matching of the reference object and the test object is determined based on the superposition.