Among other things, a model is maintained of an environment of a vehicle. A hypothetical object in the environment that cannot be perceived by sensors of the vehicle is included in the model.

A control device includes an electronic control unit executes steering control for avoiding a collision with an object that has a possibility of colliding with a host vehicle. The electronic control unit sets a timing when the host vehicle is predicted to pass the object as an end timing of the steering control when the steering control is performed. The electronic control unit determines whether or not a deviation possibility is present when the electronic control unit assumes that the steering control ends at the end timing. The deviation possibility is a possibility of the host vehicle deviating from a current traveling lane accompanying an end of the steering control. The electronic control unit performs reduction processing that reduces the deviation possibility when the electronic control unit determines that the deviation possibility is present.

Embodiments of the disclosure provide a method and apparatus for trajectory prediction, a device and a storage medium. The method includes that: location information of a reference end point of a moving object is determined according to location information of the moving object; a candidate trajectory set including multiple candidate trajectories is determined according to the location information of the moving object and the location information of the reference end point, wherein location information of an end point of each candidate trajectory is different from the location information of the reference end point; and a target trajectory of the moving object is determined from the candidate trajectory set.

A vehicle control device includes a pedestrian recognizer configured to recognize a pedestrian present in the periphery of a vehicle, and a driving controller configured to decelerate at least the vehicle irrespective of an occupant's operation of the vehicle in accordance with the vehicle and a pedestrian approaching each other, and delays a timing at which the vehicle is stopped in a case where a plurality of pedestrians recognized by the pedestrian recognizer are present on a traveling route of the vehicle.

The prediction system for predicting an information related to a pedestrian has a tracking module that detects and tracks in real-time a pedestrian in an operating area, from sensor data; a machine-learning prediction module that performs a prediction of information at future times related to the tracked pedestrian using a machine-learning algorithm from input data including data of the tracked pedestrian transmitted by the tracking module and map data of the operating area; a pedestrian behavior assessment module that determines additional data of the tracked pedestrian representative of a real time behavior of the pedestrian, and said additional data of the tracked pedestrian is used by the machine-learning prediction module as another input data to perform the prediction.

Provided are a system and a method for testing an ability of an automated vehicle to pass a traffic circle without traffic lights. The system includes an automated vehicle, a traffic circle, a control center, an attitude sensor and a panorama camera. In the method, the control center receives a test request and then sends a driving command to drive the automated vehicle to enter the traffic circle to start the test. The attitude sensor obtains a tilt angle and sends it to the control center in real time. The panorama camera is configured to obtain a driving trajectory, a driving speed and a state of turn signals of the automated vehicle. The obtained information is compared to a standard by the control center to evaluate the ability of the automated vehicle to pass the traffic circle without traffic lights.

Exemplary implementations may: generate output signals conveying contextual information and vehicle information; determine, based on the output signals, the contextual information; determine, based on the output signals, the vehicle information, determine, in an ongoing manner, based on the contextual information and/or the vehicle information, values of a complexity metric, the complexity metric quantifying predicted complexity of a current contextual environment and/or predicted complexity of a likely needed response to a change in the contextual information; filter, based on the values of the complexity metric, the contextual information spatially; and control, based on the vehicle information and the spatially filtered contextual information, the vehicle such that the likely needed response is satisfied.

In a recognition device, a recognition unit recognizes an object present in a direction of travel of an own vehicle and an estimated movement region of the object, a determination unit determines whether a path of the own vehicle is blocked by the object by determining whether the estimated movement region of the object overlaps with the path of the vehicle, based on a recognition result obtained by the recognition unit, in response to the determination unit determining that the path is blocked, an acquisition unit acquires information indicating whether the object is a moving object or a stationary object from an operator, and a change unit changes the estimated movement region recognized by the recognition unit, based on the information acquired by the acquisition unit.

Systems and methods for controlling autonomous vehicle are provided. A method can include obtaining, by a computing system, data indicative of a plurality of objects in a surrounding environment of the autonomous vehicle. The method can further include determining, by the computing system, one or more clusters of the objects based at least in part on the data indicative of the plurality of objects. The method can further include determining, by the computing system, whether to enter an operation mode having one or more limited operational capabilities based at least in part on one or more properties of the one or more clusters. In response to determining that the operation mode is to be entered by the autonomous vehicle, the method can include controlling, by the computing system, the operation of the autonomous vehicle based at least in part on the one or more limited operational capabilities.

The invention being presented here automates the functions of the driver of the garbage truck. It involves a waste collection truck designed to follow routes to collect waste using a human to pick up the bins with refuse or other material comprising a truck that includes a drive-by-wire kit, a database storing the collection routes, a mechanism for detecting the position of the human which collects the waste bins and empties them on the back of the truck and a control mechanism that follows the assigned route and speeds or slows down the truck as to minimize the distance that the human will need to walk to empty the trash in the back of the waste collection truck.