Optimal planner switch method for three point turn of autonomous driving vehicles

    公开(公告)号:US11338855B2

    公开(公告)日:2022-05-24

    申请号:US16314352

    申请日:2018-12-26

    发明人: Lin Ma Fan Zhu Xin Xu

    IPC分类号: B62D15/02 B60W30/18 G01C21/34

    摘要: A three-point-turn is planned and executed in the operation of an autonomous driving vehicle (ADV). A candidate route from a start point and going through an end point is determined, the start point and the end point being in lanes associated with opposite travel directions. The candidate route is categorized into partially overlapping first, second, and third segments. A total cost associated with the candidate route is determined based at least in part on the first and second segments. Whether the total cost is below a threshold cost is determined. In response to a determination that the total cost is below the threshold cost, the three-point-turn is planned based on the candidate route. Further, driving signals are generated based at least in part on the planned three-point-turn to control operations of the ADV.

    Map-less and camera-based lane markings sampling method for level-3 autonomous driving vehicles

    公开(公告)号:US11267476B2

    公开(公告)日:2022-03-08

    申请号:US16338447

    申请日:2019-03-28

    发明人: Xin Xu Fan Zhu Lin Ma

    摘要: A computer-implemented method, apparatus, and system for discretizing lane markings and for generating a lane reference line is disclosed. A polynomial defined over an (x,y) coordinate system is received, the polynomial being representative of at least a portion of a lane boundary line. A length of the polynomial is determined. The polynomial is discretized, comprising determining a plurality of discretization points on the polynomial to represent the polynomial, wherein a first discretization point is a first end of the polynomial, wherein subsequent discretization points are determined successively until the polynomial is completely discretized, and wherein each discretization point other than the first discretization point is determined based at least in part on a slope of the polynomial at a previous discretization point. Thereafter, a lane reference line comprising a plurality of points is generated based on the discretized polynomial.

    Pedestrian probability prediction system for autonomous vehicles

    公开(公告)号:US11230297B2

    公开(公告)日:2022-01-25

    申请号:US16099883

    申请日:2018-09-28

    发明人: Fan Zhu Lin Ma

    摘要: According to some embodiments, a system receives a captured image perceiving an environment of an ADV from an image capturing device of the ADV. The system identifies an obstacle in motion near the ADV based on the captured image. The system predicts a location for the moving obstacle at each of a number of time points. The system generates a probability ellipse based on the predicted location at the each time point, where the probability ellipse includes a probability indicator indicating different probabilities of the moving obstacle for different locations within the probability ellipse at the each time point.

    Method of parking an autonomous driving vehicle for autonomous charging

    公开(公告)号:US11584248B2

    公开(公告)日:2023-02-21

    申请号:US16753204

    申请日:2020-03-20

    IPC分类号: B60L53/36 G05D1/02

    摘要: In one embodiment, an exemplary method of autonomously charging an autonomous driving vehicle includes receiving, from a sensor in an autonomous driving vehicle (ADV), indication that a batter level of the ADV falls below a threshold; and selecting a charging pile from a plurality of charging piles on a high definition map based on information received from a cloud server. The method further includes generating a first trajectory based on a current location of the ADV and a location of the selected charging pile, the first trajectory connecting a first point representing the current location of the ADV to a second point at the selected charging pile, and including a first segment and a second segment. The method further includes driving forward along the first segment of the first trajectory, and driving backward along the second segment of the first trajectory when the ADV drives towards the selected charging pile along the first trajectory.

    Method for determining passable area in planning a path of autonomous driving vehicles

    公开(公告)号:US11442450B2

    公开(公告)日:2022-09-13

    申请号:US16711118

    申请日:2019-12-11

    IPC分类号: G05D1/00 G01C21/34 G05D1/02

    摘要: According to one embodiment, in response to determining that an obstacle blocks at least a portion of a current lane in which an ADV is driving, an obstacle boundary of the obstacle is determined based on the size and shape of the obstacle. A lane configuration is determined based on map data of a map corresponding to a road associated with the lanes. A passing lane boundary that can be utilized by the ADV is determined based on the lane configuration of the road and the obstacle boundary of the obstacle. A passable area is calculated within the passing lane boundary based on a size of the ADV. The passable area is utilized by the ADV to pass the obstacle without collision. Thereafter, a trajectory is planned within the passable area boundary to control the ADV to pass the obstacle.

    Corner negotiation method for autonomous driving vehicles without map and localization

    公开(公告)号:US11312380B2

    公开(公告)日:2022-04-26

    申请号:US16314368

    申请日:2018-12-26

    发明人: Xin Xu Fan Zhu Lin Ma

    摘要: An ADV perceives a driving environment surrounding the ADV based on sensor data obtained from a variety of sensors mounted on the ADV including, for example, perceiving and recognizing a corner the ADV may be about to turn. Based on the perception data of the driving environment, a set of features representing the characteristics of an entrance point of a corner that the ADV is about to turn. Based on the characteristics of the corner, an entrance point of the corner is determined. Based on the entrance point, a lookup operation is performed in a corner mapping table to locate a mapping entry matching the entrance point. A turning radius is then obtained from the mapping entry of the corner mapping table. The turning radius obtained from the corner mapping table is then utilized to plan a trajectory (e.g., steering angle) to drive the ADV to turn the corner.