Method and apparatus for isolating a fault in a controller area network
    12.
    发明授权
    Method and apparatus for isolating a fault in a controller area network 有权
    用于隔离控制器区域网络中的故障的方法和装置

    公开(公告)号:US09009523B2

    公开(公告)日:2015-04-14

    申请号:US13686361

    申请日:2012-11-27

    Abstract: A controller area network (CAN) has a plurality of CAN elements including a communication bus and controllers. A method for monitoring the CAN includes identifying each of the controllers as one of an active controller and an inactive controller. A fault-active controller isolation process is executed to detect and isolate presence of a fault-active controller. A fault isolation process can be executed to detect and isolate presence of one of a wire open fault, a wire short fault and a controller fault when one of the controllers is identified as an inactive controller. Presence of a fault associated with a persistent bus disturbance in the CAN is detected when a bus error count is greater than a predetermined threshold continuously for a predetermined period of time.

    Abstract translation: 控制器局域网(CAN)具有包括通信总线和控制器的多个CAN元件。 用于监视CAN的方法包括将每个控制器识别为主动控制器和非活动控制器之一。 执行故障主动控制器隔离过程以检测和隔离故障主动控制器的存在。 当一个控制器被识别为非活动控制器时,可以执行故障隔离过程来检测和隔离有线打开故障,电线短路故障和控制器故障之一的存在。 当总线错误计数大于预定阈值持续预定时间段时,检测出存在与CAN中的持久总线干扰有关的故障。

    Virtual lane mark generation
    13.
    发明授权

    公开(公告)号:US12190608B2

    公开(公告)日:2025-01-07

    申请号:US17738328

    申请日:2022-05-06

    Abstract: A vehicle, system method for operating the vehicle is disclosed. The system includes a camera and a processor. The camera is configured to obtain a camera image of a road segment. The processor determines a location of a road edge for the road segment within the camera image, obtains a lane attribute for the road segment, generates a virtual lane mark for the road segment based on the road edge and the lane attribute, and moves the vehicle along the road segment by tracking the virtual lane mark.

    Method of enhanced component failure diagnosis for suggesting least probable fault

    公开(公告)号:US11288900B2

    公开(公告)日:2022-03-29

    申请号:US16561711

    申请日:2019-09-05

    Abstract: A method and system of diagnosing and suggesting least probable faults for an exhibited vehicle failure. The method includes initiating a vehicle health management (VHM) algorithm to monitor a state of health (SOH) for at least one vehicle component at each vehicle operating event over a predetermined time period. The VHM algorithm determines at least one of a Green SOH, a Yellow SOH, and a Red SOH designation with a confidence level for the at least one vehicle component; calculating a number of Green SOH designations (Ncalculated) over the predetermined time period; and upon an exhibited vehicle failure, providing a least probable cause indication for the at least one component when a set of conditions are met. The set of conditions includes (i) Ncalculated is equal to or greater than a predetermined number of Green SOH designations and (ii) no Yellow SOH and Red SOH designations are present.

    METHOD OF ENHANCED COMPONENT FAILURE DIAGNOSIS FOR SUGGESTING LEAST PROBABLE FAULT

    公开(公告)号:US20210074087A1

    公开(公告)日:2021-03-11

    申请号:US16561711

    申请日:2019-09-05

    Abstract: A method and system of diagnosing and suggesting least probable faults for an exhibited vehicle failure. The method includes initiating a vehicle health management (VHM) algorithm to monitor a state of health (SOH) for at least one vehicle component at each vehicle operating event over a predetermined time period. The VHM algorithm determines at least one of a Green SOH, a Yellow SOH, and a Red SOH designation with a confidence level for the at least one vehicle component; calculating a number of Green SOH designations (Ncalculated) over the predetermined time period; and upon an exhibited vehicle failure, providing a least probable cause indication for the at least one component when a set of conditions are met. The set of conditions includes (i) Ncalculated is equal to or greater than a predetermined number of Green SOH designations and (ii) no Yellow SOH and Red SOH designations are present.

    Method and apparatus for monitoring of an autonomous vehicle

    公开(公告)号:US10678247B2

    公开(公告)日:2020-06-09

    申请号:US15688451

    申请日:2017-08-28

    Abstract: An autonomic vehicle control system includes a perception module of a spatial monitoring system that is disposed to monitor a spatial environment proximal to the autonomous vehicle. A method for evaluating vehicle dynamics operation includes determining a desired trajectory for the autonomous vehicle, wherein the desired trajectory includes desired vehicle positions including an x-position, a y-position and a heading. Vehicle control commands are determined based upon the desired trajectory, and include a commanded steering angle, an acceleration command and a braking command. Actual vehicle states responsive to the vehicle control commands are determined. An estimated trajectory is determined based upon the actual vehicle states, and a trajectory error is determined based upon a difference between the desired trajectory and the estimated trajectory. The trajectory error is monitored over a time horizon, and a first state of health (SOH) is determined based upon the trajectory error over the time horizon.

    Method and apparatus for monitoring of an autonomous vehicle

    公开(公告)号:US10558217B2

    公开(公告)日:2020-02-11

    申请号:US15688429

    申请日:2017-08-28

    Abstract: A perception module of a spatial monitoring system to monitor and characterize a spatial environment proximal to an autonomous vehicle is described. A method for evaluating the perception module includes capturing and storing a plurality of frames of data associated with a driving scenario for the autonomous vehicle, and executing the perception module to determine an actual spatial environment for the driving scenario, wherein the actual spatial environment for the driving scenario is stored in the controller. The perception module is executed to determine an estimated spatial environment for the driving scenario based upon the stored frames of data associated with the driving scenario, and the estimated spatial environment is compared to the actual spatial environment for the driving scenario. A first performance index for the perception module is determined based upon the comparing, and a fault can be detected.

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