The present teaching relates to method, system, medium, and implementation of in-situ perception in an autonomous driving vehicle. A plurality of types of sensor data are acquired continuously via a plurality of types of sensors deployed on the vehicle, where the plurality of types of sensor data provide information about surrounding of the vehicle. One or more items surrounding the vehicle are tracked, based on some models, from a first of the plurality of types of sensor data from a first type of the plurality of types of sensors. A second of the plurality of types of sensor data are obtained from a second type of the plurality of sensors and are used to generate validation base data. Some of the one or more items are labeled, automatically, via validation base data to generate labeled at least some item, which is to be used to generate model updated information for updating the at least one model.

A non-transitory computer-readable medium storing instructions, the instructions, when executed by a processor, cause the processor to: perform a follow-up steering control for changing a steering angle of a vehicle in such a manner that the vehicle travels along a target traveling line determined based on a preceding vehicle trajectory, which is a travel trajectory of a preceding vehicle traveling ahead of the vehicle; and when a first distance condition and a manual steering condition are both satisfied while the follow-up steering control is being performed, stop the follow-up steering control, the first distance condition being a condition satisfied when a deviation distance in a road-width direction between the preceding vehicle trajectory and the vehicle is equal to or longer than a predetermined first threshold, and the manual steering condition being a condition satisfied when a driver operates a steering wheel to change a position in the road-width direction.

A non-transitory computer-readable medium storing instructions, the instructions, when executed by a processor, cause the processor to: perform a follow-up steering control for changing a steering angle of a vehicle in such a manner that the vehicle travels along a target traveling line determined based on a preceding vehicle trajectory, which is a travel trajectory of a preceding vehicle traveling ahead of the vehicle; and when a first distance condition and a manual steering condition are both satisfied while the follow-up steering control is being performed, stop the follow-up steering control, the first distance condition being a condition satisfied when a deviation distance in a road-width direction between the preceding vehicle trajectory and the vehicle is equal to or longer than a predetermined first threshold, and the manual steering condition being a condition satisfied when a driver operates a steering wheel to change a position in the road-width direction.

A device according to one aspect of the present disclosure is an on-vehicle control device configured to control a traveling speed of a vehicle including the on-vehicle control device. The on-vehicle control device includes: an acquisition unit configured to acquire a present light color of a traffic light unit installed at an intersection; a calculation unit configured to calculate an avoidance position and an avoidance speed with respect to a dilemma zone at a time when yellow light starts; and a control unit configured to execute a first deceleration process of reducing the traveling speed of the vehicle at the avoidance position to a speed equal to or lower than the avoidance speed, in a case where a present position of the vehicle is on an upstream side relative to the avoidance position and the present light color is green.

Various technologies described herein pertain to a fused camera and lidar system for an autonomous vehicle. The fused camera and lidar system includes a fused receiver. The fused receiver includes optics configured to receive a received electromagnetic signal from an environment nearby the fused camera and lidar system. The fused receiver further includes a beam splitter configured to split the received electromagnetic signal into a first split electromagnetic signal (including wavelengths in a visible spectrum) and a second split electromagnetic signal (including wavelengths in an infrared spectrum). The fused receiver also includes a camera pipeline and a lidar pipeline. The camera pipeline can generate image data based on the first split electromagnetic signal, and the lidar pipeline can generate lidar data based on the second split electromagnetic signal.

Various technologies described herein pertain to a fused camera and lidar system for an autonomous vehicle. The fused camera and lidar system includes a fused receiver. The fused receiver includes optics configured to receive a received electromagnetic signal from an environment nearby the fused camera and lidar system. The fused receiver further includes a beam splitter configured to split the received electromagnetic signal into a first split electromagnetic signal (including wavelengths in a visible spectrum) and a second split electromagnetic signal (including wavelengths in an infrared spectrum). The fused receiver also includes a camera pipeline and a lidar pipeline. The camera pipeline can generate image data based on the first split electromagnetic signal, and the lidar pipeline can generate lidar data based on the second split electromagnetic signal.

Aspects of the disclosure relate to controlling an autonomous vehicle to respond to a detected collision. An autonomous vehicle control system may receive sensor data associated with an autonomous vehicle in which the autonomous vehicle control system is installed. The autonomous vehicle control system may analyze the sensor data in real-time as the sensor data is received and may detect an occurrence of a collision involving the autonomous vehicle. In response to detecting the occurrence of the collision, the autonomous vehicle control system may generate claim information based on the sensor data and may process the claim information based on at least one insurance profile maintained by the autonomous vehicle control system. Then, the autonomous vehicle control system may generate a claim notification based on processing the claim information and may send the claim notification to a vehicle management computer system.

Aspects of the disclosure relate to controlling an autonomous vehicle to respond to a detected collision. An autonomous vehicle control system may receive sensor data associated with an autonomous vehicle in which the autonomous vehicle control system is installed. The autonomous vehicle control system may analyze the sensor data in real-time as the sensor data is received and may detect an occurrence of a collision involving the autonomous vehicle. In response to detecting the occurrence of the collision, the autonomous vehicle control system may generate claim information based on the sensor data and may process the claim information based on at least one insurance profile maintained by the autonomous vehicle control system. Then, the autonomous vehicle control system may generate a claim notification based on processing the claim information and may send the claim notification to a vehicle management computer system.

The disclosure generally relates to autonomous or semi-autonomous driving vehicles. An exemplary embodiment of the disclosure relates to a system to provide one or more threat vectors to a cluster of vehicles. An exemplary vehicle detection system includes a communication module configured to receive a first threat vector from a first vehicle in a cluster of vehicles. The first threat vector may include a plurality of primary attributes associated with a moving object. The vehicle detection system may also include a detector module configured to detect the moving object and to provide one or more secondary attributes associated with the moving object; and a controller to construct a second threat vector as a function of one or more of the first threat vector, the primary attributes and the secondary attributes associated with the moving object.

The disclosure generally relates to autonomous or semi-autonomous driving vehicles. An exemplary embodiment of the disclosure relates to a system to provide one or more threat vectors to a cluster of vehicles. An exemplary vehicle detection system includes a communication module configured to receive a first threat vector from a first vehicle in a cluster of vehicles. The first threat vector may include a plurality of primary attributes associated with a moving object. The vehicle detection system may also include a detector module configured to detect the moving object and to provide one or more secondary attributes associated with the moving object; and a controller to construct a second threat vector as a function of one or more of the first threat vector, the primary attributes and the secondary attributes associated with the moving object.