A driving assistance device configured to execute deceleration assistance for a driver's vehicle when the driver's vehicle turns right or left at an intersection is configured to recognize, based on a detection result from an external sensor of the driver's vehicle, an adjacent vehicle traveling in an adjacent lane adjacent to a traveling lane of the driver's vehicle, determine whether the adjacent vehicle turns in the same direction of the driver's vehicle at the intersection based on the detection result from the external sensor when the adjacent vehicle is recognized and the driver's vehicle turns right or left at the intersection, and execute the deceleration assistance to cause a vehicle-to-vehicle distance between the driver's vehicle and the adjacent vehicle to reach a distance equal to or larger than a target driver's vehicle-to-adjacent vehicle distance when the driving assistance device determines that the adjacent vehicle turns in the same direction.

The present disclosure provides a vehicle behavior prediction method and apparatus, an electronic device, and a computer-readable storage medium, which relates to the field of intelligent driving. The method includes: determining a target traffic light corresponding to t a target vehicle a current intersection; determining a neighboring traffic light corresponding to the target traffic light and the indication status of the neighboring traffic light according to the target traffic light, the indication status of the target traffic light and a traffic light status mapping relationship table; acquiring a position of an obstacle vehicle and predicting each possible travel path of the obstacle vehicle, and determining a traffic light corresponding to each possible travel path; and determining a final possible travel path of the obstacle vehicle according to each possible travel path and the indication status of the traffic light corresponding to each possible travel path.

A risk prediction determination device includes a predicted traveling route specifying unit, a risk location specifying unit, and a risk prediction determination unit. The predicted traveling route specifying unit specifies a predicted traveling route of a subject vehicle based on traveling lane information indicating a traveling lane of the subject vehicle, road type information indicating a type of a road around the subject vehicle, road link information related to a road link, and sensor information of the subject vehicle. The risk location specifying unit specifies a location with risk based on road shape information around the subject vehicle and location information of an obstacle. The risk prediction determination unit performs a risk prediction determination based on a specified result of the predicted traveling route specifying unit and a specified result of the risk location specifying unit.

A vehicle, system and a method of operating the vehicle is disclosed. The system includes a first sensor, a second sensor and a processor. The first sensor captures an image of a traffic control device. The second sensor identifies a lane within a road that is occupied by the vehicle. The processor is configured to determine an attribute of the lane occupied by the vehicle, associate a semantic meaning to a motion control signal of the traffic control device, determine a maneuver for the vehicle based on the semantic meaning of the motion control signal and the attribute of the lane occupied by the vehicle, and perform the maneuver at the vehicle.

A traveling lane planning device has a processor configured to determine whether or not a branching terrain exists that has a first lane and a second lane adjacent to the first lane wherein the first lane branches into a third lane and a fourth lane at a branching start location in the traveling direction of the vehicle within a driving zone, when the branching terrain exists and the vehicle is located before the branching start location, to acquire lane movement information for movement between the first lane and second lane came off in the past, and based on the lane movement information, to select one lane from among the third lane and fourth lane as the lane to be taken at the branching start location and generate a traveling lane plan that indicates a scheduled traveling lane for traveling of the vehicle in the driving zone.

A method for minimizing disturbance due to wind forces of a trailer being towed by a vehicle. The method also includes receiving, at a data processing hardware data from a sensor system for the tow vehicle. The method also includes determining, at the data processing hardware, a passing object profile. The method also includes predicting, at the data processing hardware, a wind force profile based upon the sensor data the passing object profile. The method also includes determining, at the data processing hardware, at least one preventative action for the vehicle to minimize the effect of disturbance on the trailer.

The disclosure relates to a lane change method and system, a storage medium, and a vehicle. The lane change method includes the following steps: receiving consecutive frames of condition information, the condition information including velocity information of a current vehicle, state information of an adjacent vehicle, and lane information; with the condition information as an input to a neural network, processing the condition information by means of the neural network, to obtain an initial lane change strategy; and correcting the initial lane change strategy based on a predetermined rule and the condition information, to generate and output a corrected lane change strategy. According to this lane change method, intelligent, safe and efficient lane change may be achieved during an autonomous driving or driving assistance process.

A system for automatedly changing a first road lane of a vehicle to a second road lane to maintain engagement of an automated driving unit. The system comprises an ECU to check a location of the vehicle, defining a map segment of the first and second road lanes. The first road lane is a host lane that the vehicle occupies and the second road lane is an available lane. The ECU detects whether the first road lane has poor availability. The system further comprises a sensor to monitor availability of the first road lane. The system further comprises a backoffice to flag the first road lane if the first road lane is detected to have poor availability, to log the first road lane in an instance counter (IC), and to designate the first road lane as non-preferred if an occurrence threshold of the IC is reached. The system further comprises an automated lane change (ALC) unit to move the vehicle to the second road lane.

Provided is an apparatus for assisting travelling of a vehicle, the apparatus including: a camera disposed in the vehicle, having a field of view of a front of the vehicle, and acquiring image data; and a controller including a processor for processing the image data, wherein the controller is configured to: identify a lane being travelled on by the vehicle and a preceding vehicle travelling in front of the vehicle based on the image data processed, and in response to the preceding vehicle crossing a center line, generate a control signal for controlling the vehicle based on the preceding vehicle crossing the center line.

Systems and methods described herein relate to coordinated vehicle lane assignment. One embodiment receives from a locality manager, at a section manager that communicates with one or more connected vehicles in a section of a roadway, target lateral flows for two or more lanes of the roadway in the section of the roadway; converts the target lateral flows to a target number of connected vehicles N at the section manager; selects for lane change, at the section manager, a set of N connected vehicles whose ranked distances from a following vehicle in a target lane are greatest among the one or more connected vehicles, when a direction of lane change is uniform among the set of N connected vehicles; and transmits lane-change actions from the section manager to the set of N connected vehicles.