The present teaching relates to method, system, medium, and implementation of automatic motion planning for an autonomous driving vehicle. Information is obtained with respect to a current location of the autonomous driving vehicle operating in a current vehicle motion, wherein the information is to be used to estimate the operational capability of the autonomous driving vehicle with respect to the current location. Sensor data are obtained, via one or more sensors in one or more media types. A reaction of a passenger present in the vehicle with respect to a current vehicle motion is estimated based on the sensor data. Motion planning is performed based on the information with respect to the current location and the reaction of the passenger to the current vehicle motion.

A gateway of a vehicle is connected to a telematics control unit (TCU) and a plurality of electronic control units (ECUs). The gateway is programmed to receive a command from the TCU, the command specifying an electronic serial number (ESN) of a target ECU of the ECUs, and forward the command to the target ECU responsive to confirmation that the ESN of the target ECU is included in the web of trust.

A method of determining a trajectory for an autonomous vehicle is disclosed. An ego-vehicle may detect a moving actor in an environment. To choose between candidate trajectories for the ego-vehicle, the system will consider the cost of each candidate trajectory to the moving actor. The system will use the candidate trajectory costs for the candidate trajectories to select one of the candidate trajectories via which to move the ego-vehicle. An autonomous vehicle system of the ego-vehicle may then move the ego-vehicle in the environment along the selected trajectory.

Systems and methods relating to controlling a driving system operatively coupled to a vehicle are disclosed. A location is identified using one or more sensors included with the vehicle. An input of the driving system is identified using the location. A desired output of the driving system is determined using the input.

Systems and methods are provided for autonomous vehicle navigation. The systems and methods may map a lane mark, may map a directional arrow, selectively harvest road information based on data quality, map road segment free spaces, map traffic lights and determine traffic light relevancy, and map traffic lights and associated traffic light cycle times.

Some embodiments are directed to methods and apparatus for predicting traffic conditions and controlling a host vehicle based on the predicted conditions for travel along a path. The methods and apparatus can perform the following: accessing current path data relevant to a location and speed the host vehicle; detecting data, from a vehicular communications network, from a merging vehicle intending to merge into the path of the host vehicle; detecting data, from the vehicular communications network, of preceding traffic in the path of the host vehicle; determining a speed and location of the merging vehicle from the data transmitted over the vehicle communications network; determining a speed and location of preceding traffic on the path of the host vehicle from the data transmitted over the vehicular communications network; and predicting whether the speed of the preceding traffic or the speed of the merging vehicle will slow down during the merge.

A computer-implemented method for controlling a host vehicle having a vehicle control system that controls motion of the host vehicle relative to a preceding vehicle that is immediately ahead of the host vehicle. The method includes determining a relative headway distance and a relative velocity between the host vehicle and the preceding vehicle, and an acceleration rate of the preceding vehicle. The method includes receiving message packets transmitted from a leading vehicle and the message packets contain parameters of the leading vehicle including an acceleration rate of the leading vehicle. Further, the method includes calculating an acceleration control rate for the host vehicle to maintain the headway reference distance between the host vehicle and the preceding vehicle, based on the relative headway distance, the relative velocity, the acceleration rate of the preceding vehicle, and the acceleration rate of the leading vehicle. The acceleration rate is output to a vehicle controller to control motion of the host vehicle.

Embodiments of the present disclosure relate to the technical field of autonomous driving, and in particular to methods for updating an autonomous driving system, autonomous driving systems, and on-board apparatuses. In the embodiments of the present disclosure, the autonomous driving system, in a manual driving mode, senses the surrounding environment of a vehicle, performs vehicle positioning, and plans a path for autonomous driving for the vehicle. However, the autonomous driving system does not issue an instruction to control the driving of the vehicle. Instead, it compares the path with a path along which a driver drives the vehicle in the manual driving mode to update a planning and control algorithm of the autonomous driving system. As such, the updated autonomous driving system better caters to the driving habits of the driver and improves the driving experience for the driver without compromising the reliability of planning and decision-making of autonomous driving.

An information processing apparatus comprises a control unit configured to execute: obtaining, from a first vehicle, vehicle data relating to travel of the first vehicle; and identifying, based on the vehicle data, one or more first points, which are one or more points at which the first vehicle has satisfied operating conditions for a predetermined driving support function included in the first vehicle while the first vehicle is traveling.

A vehicle control system is provided with: a database configured to store therein, for each vehicle, vehicle data including a plurality of types of information about vehicle operation; a group divider configured to divide the vehicle data of a plurality of vehicles into groups each including similar driving characteristics; a specifier configured to specify to which of the groups a host vehicle belongs, from a running history of the host vehicle; an extractor configured to extract the vehicle data of a vehicle with higher evaluation regarding a predetermined evaluation item, which can be evaluated by using the vehicle data, than that of the host vehicle, from the group specified by the specifier; and a controller configured to control a running aspect of the host vehicle such that it approaches to a running aspect performed on the basis of the vehicle operation indicated by the vehicle data extracted by the extractor.