Systems and methods for vehicle motion planning based on uncertainty are provided. A method can include obtaining scene data descriptive of one or more objects within a surrounding environment of the autonomous vehicle. The method can include determining one or more subproblems based at least in part on the scene data. In some implementation, each of the one or more subproblems can correspond to at least one object within the surrounding environment of the autonomous vehicle. The method can include generating one or more branching policies based at least in part on the one or more subproblems. In some implementations, each of the one or more branching policies can include scene data associated with the autonomous vehicle and one or more objects within the surrounding environment of the autonomous vehicle. The method can include determining one or more costs associated each of the one or more branching policies. The method can include selecting a motion plan based at least in part on the one or more costs associated with each of the one or more branching policies. The method can include providing the motion plan for use in controlling a motion of the autonomous vehicle.

The disclosure relates to a lane departure warning method and a lane departure warning system. The lane departure warning method of the disclosure includes: a warning area calculation step in which a warning area for lane departure of a vehicle is calculated based on information about the vehicle and information around the vehicle; a decision making step in which a current position of the vehicle is compared with the warning area calculated in the warning area calculation step, to determine whether the vehicle is located in the warning area and output a decision instruction; and a warning step in which a warning action is performed based on the decision instruction. According to the disclosure, a lane departure status of the vehicle can be more accurately estimated and timely warning can be performed when there is a tendency for lane departure.

When a subject vehicle performs first autonomous lane change control from a subject vehicle lane to an adjacent lane and then consecutively perform autonomous lane change control to a next adjacent lane in the same direction of lane change, lateral speed to perform second and subsequent autonomous lane change control is set slower than lateral speed to perform the first autonomous lane change control. Thus, the second and subsequent autonomous lane change control to the adjacent lane in the same direction of lane change is performed more slowly than the previously performed autonomous lane change control. Time used for confirming surrounding situations is lengthened, and the surrounding situations can be properly confirmed prior to the lane change.

The present disclosure relates to an autonomous vehicle system or a driver assistance system that detects an object in front of the vehicle, judges whether a condition calls for an operation of a lateral movement system for collision avoidance, determines a direction of the lateral movement, and executes the lateral movement.

A lane keeping controller, a vehicle system including the same, and a method thereof are provided. The lane keeping controller includes a processor that monitors a risk level of a vehicle in real time, upon a lane keeping control, calculates a target lateral movement distance based on a line component, integrates an offset from a predetermined offset threshold to the vehicle, when an offset between a target route and the vehicle departs from the predetermined offset threshold, and corrects the target lateral movement distance based on the integrated value to calculate a final target lateral movement distance and a storage storing data and an algorithm run by the processor.

A method of operating a vehicle having a driver assistance system includes detecting driving parameters pertaining to the vehicle while the vehicle is being driven on a roadway using a sensor system of the vehicle. Objects including road signs, lane indicators, and other vehicles are detected using the sensor system. The objects include at least road signs, lane indicators, and other vehicles on the roadway. A traffic rule pertaining to the roadway is identified using a traffic violation warning and prevention system of the driver assistance system. A traffic situation pertaining to the traffic rule is detected based on the detected objects and the driving parameters. An alert is generated that warns the driver of a potential traffic violation when the traffic situation is detected. Alternatively, the driver assistance system may be configured to take control of the vehicle to prevent violation of the traffic rule.

In one example, a method performed by a processing system including at least one processor includes receiving a plurality of data from an autonomous driving vehicle, presenting the plurality of data in a contextually aware dynamic visual indicator, generating an output that the autonomous driving vehicle is operating improperly based on an analysis of the plurality of data, and transmitting a control signal to the autonomous driving vehicle in response to the output that the autonomous driving vehicle is operating improperly to modify an operation of the autonomous driving vehicle.

A mobile work machine includes a frame; ground engaging elements movably supported by the frame and driven by a power source to drive movement of the machine; a moveable element movably supported by the frame to move relative to the frame; an actuator coupled to the moveable element to controllably drive movement of the moveable element; a control system that generates an actuator control signal, indicative of a commanded movement of the actuator, and provides the actuator control signal to the actuator to control the actuator to perform the commanded movement; a terrain identifier configured to identify a characteristic of terrain in a geographic area around the machine; and a stability system that determines whether the commanded movement will result in an unstable state of the machine based on the characteristic of the terrain and, if so, generates a restriction signal, restricting the commanded movement to avoid the unstable state.

An automotive electronic dynamics control system for an automated motor-vehicle. The electronic dynamics control system is designed to implement two distinct Model Predictive Control (MPC)-based Trajectory Planners comprising a Longitudinal Trajectory Planner designed to compute a planned longitudinal trajectory for the automated motor-vehicle; and a Lateral Trajectory Planner designed to compute a planned lateral trajectory for the automated motor-vehicle. The electronic dynamics control system is further designed to cause the planned longitudinal trajectory to be computed before the planned lateral trajectory.

The invention relates to a method for lane-changing prediction of a target vehicle, the method including: receiving a velocity and a position of the target vehicle; respectively obtaining, based on the velocity and the position of the target vehicle, a first lane-changing probability and a second lane-changing probability of the target vehicle by using a first machine learning model and a second machine learning model; and determining a possibility of lane changing of the target vehicle based on the first lane-changing probability and the second lane-changing probability, the first machine learning model and the second machine learning model being pre-trained and being different from each other. The invention further relates to a device for lane-changing prediction of a target vehicle, a computer storage medium, and a vehicle.