A method for providing a dynamic adaptive deep learning model other than a fixed deep learning model, to thereby support at least one specific autonomous vehicle to perform a proper autonomous driving according to surrounding circumstances is provided. And the method includes steps of: (a) a managing device which interworks with autonomous vehicles instructing a fine-tuning system to acquire a specific deep learning model to be updated; (b) the managing device inputting video data and its corresponding labeled data to the fine-tuning system as training data, to thereby update the specific deep learning model; and (c) the managing device instructing an automatic updating system to transmit the updated specific deep learning model to the specific autonomous vehicle, to thereby support the specific autonomous vehicle to perform the autonomous driving by using the updated specific deep learning model other than a legacy deep learning model.

A learning method for supporting a safer autonomous driving through a fusion of information acquired from images and communications is provided. And the method includes steps of: (a) a learning device instructing a first neural network and a second neural network to generate an image-based feature map and a communication-based feature map by using a circumstance image and circumstance communication information; (b) the learning device instructing a third neural network to apply a third neural network operation to the image-based feature map and the communication-based feature map to generate an integrated feature map; (c) the learning device instructing a fourth neural network to apply a fourth neural network operation to the integrated feature map to generate estimated surrounding motion information; and (d) the learning device instructing a first loss layer to train parameters of the first to the fourth neural networks.

A method for determining avoidance trajectories for a collision-free avoidance maneuver of transportation vehicles, wherein trajectory data describing a collection of possible driving trajectories is received from at least one trajectory generator for each transportation vehicle in real time, and a respective avoidance trajectory is determined in real time for each transportation vehicle based on the collection of possible driving trajectories for that transportation vehicle. For each transportation vehicle, the driving trajectories are divided into groups, and each group is represented by a single respective group trajectory. In at least one combination operation, each of the group trajectories of each transportation vehicle is selected and a resulting driving maneuver is checked based on the selected group trajectories to determine if the driving maneuver fulfils a predetermined optimization criterion, and the avoidance trajectories are determined based on the group trajectories of a combination operation with a fulfilled optimization criterion.

A vehicle control apparatus to be mounted on a vehicle including an engine includes a first power supply system, a second power supply system, a switch, and a switch controller. The first power supply system includes a first electricity storage device and an electric load. The second power supply system includes an electric motor and a second electricity storage device. The switch controller is configured to control the switch to a cutoff state on the condition that the electric motor is controlled to a powering state to bring the engine to starting rotation from a stopped state. The switch controller is configured to control the switch to an electrically conductive state on the condition that the electric motor is controlled to the powering state to bring the engine to an assisted drive from a rotating state.

Systems of an electrical vehicle and the operations thereof are provided.

Methods and apparatus to extricate a vehicle from a stuck condition, apparatus, systems and articles of manufacture are disclosed. An example apparatus includes: a user interface to receive a command to place a vehicle in an autonomous control mode of the vehicle; and a stuck mode controller to autonomously shift a transmission of the vehicle alternately between a reverse gear and a forward gear of the vehicle when in the autonomous control mode to autonomously rock the vehicle back and forth. A timing of the shifting of the transmission is based on a ratio of a velocity of the vehicle to an acceleration of the vehicle.

Systems of an electrical vehicle and the operations thereof are provided that use object profiles to select autonomous vehicle operations, including acceleration rate, deceleration rate, steering angle, and inter-vehicle spacing.

The present disclosure provides an method, an apparatus, a device and a storage medium for controlling an unmanned vehicle, where the method includes: receiving control messages transmitted by at least two automatic driving physical apparatuses, where the control messages include indication information; determining an optimal control message according to the indication information in each of the control messages; transmitting the optimal control message to a device for controlling an unmanned vehicle, so that the device for controlling an unmanned vehicle performs driving control on the unmanned vehicle according to the optimal control message. When a plurality of automatic driving physical apparatuses transmit control messages, at this time, the control messages are redundant, and a control message can be selected for execution, so that the unmanned vehicle can receive a control signal in time, which is beneficial to the safe driving of the unmanned vehicle.

In one embodiment, a system determines a difference in time between a local time source and a time of a GPS sensor. The system determines a max limit in difference and a max recovery increment or max recovery time interval for a smooth time source recovery. The system determines that the difference between the local time source and a time of the GPS sensor to be less than the max limit. The system plans a smooth recovery of the time source to converge the local time source to a time of the GPS sensor within the max recovery time interval. The system generates a timestamp based on the recovered time source to timestamp sensor data for a sensor unit of the ADV.

An automatic driving assistance device includes an information acquirer configured to acquire information on a state of a cabin of a vehicle capable of automatic driving and a modifier configured to modify traveling characteristics in automatic driving according to the state of the cabin of the vehicle.