Optimal path library for local path planning of an autonomous vehicle

    公开(公告)号:US11619943B2

    公开(公告)日:2023-04-04

    申请号:US16826117

    申请日:2020-03-20

    Applicant: TUSIMPLE, INC.

    Abstract: Methods, systems and apparatus for autonomous vehicle path planning and path navigation are described. One example system includes an offline server configured to generate a library of optimal paths for navigating a geographic area, wherein the geographic area is represented as a grid node map and an orientation grid bin map and wherein the optimal paths correspond to paths between pairs of grid node pairs in the grid node map based on optimization criteria, a storage device on the autonomous vehicle for storing the library of optimal paths, and an online server located on the autonomous vehicle configured to access information from the library of optimal paths from the storage device based on a current position and a current heading of the autonomous vehicle, and navigating the autonomous vehicle through the geographic area based on the information.

    Vehicle powertrain integrated predictive dynamic control for autonomous driving

    公开(公告)号:US12195003B2

    公开(公告)日:2025-01-14

    申请号:US18343837

    申请日:2023-06-29

    Applicant: TUSIMPLE, INC.

    Abstract: Devices, systems, and methods for integrated predictive dynamic control of a vehicle powertrain in an autonomous vehicle are described. An example method for controlling a vehicle includes generating, based on performing an optimization on a blended smooth wheel domain fuel consumption map subject to a modified torque availability constraint, one or more wheel domain control commands, converting the one or more wheel domain control commands to one or more powertrain-executable engine domain control commands, and transmitting the one or more powertrain-executable engine domain control commands to a powertrain of the vehicle, the powertrain configured to operate a plurality of gears, wherein the one or more powertrain-executable engine domain control commands enable the vehicle to track a reference kinematic trajectory associated with a vehicle speed driving plan within a predetermined tolerance.

    Optimal path library for local path planning of an autonomous vehicle

    公开(公告)号:US12174634B2

    公开(公告)日:2024-12-24

    申请号:US18186137

    申请日:2023-03-17

    Applicant: TUSIMPLE, INC.

    Abstract: Methods, systems and apparatus for autonomous vehicle path planning and path navigation are described. One example system includes an offline server configured to generate a library of optimal paths for navigating a geographic area, wherein the geographic area is represented as a grid node map and an orientation grid bin map and wherein the optimal paths correspond to paths between pairs of grid node pairs in the grid node map based on optimization criteria, a storage device on the autonomous vehicle for storing the library of optimal paths, and an online server located on the autonomous vehicle configured to access information from the library of optimal paths from the storage device based on a current position and a current heading of the autonomous vehicle, and navigating the autonomous vehicle through the geographic area based on the information.

    Two-level path planning for autonomous vehicles

    公开(公告)号:US12122419B2

    公开(公告)日:2024-10-22

    申请号:US16912444

    申请日:2020-06-25

    Applicant: TUSIMPLE, INC.

    CPC classification number: B60W60/0011 G05D1/0022 G05D1/0274 H04W4/40

    Abstract: Described is a two-level optimal path planning process for autonomous tractor-trailer trucks which incorporates offline planning, online planning, and utilizing online estimation and perception results for adapting a planned path to real-world changes in the driving environment. In one aspect, a method of navigating an autonomous vehicle includes determining, by an online server, a current vehicle state of the autonomous vehicle in a mapped driving area. The method includes receiving, by the online server from an offline path library, a path for the autonomous driving vehicle through the mapped driving area from the current vehicle state to a destination vehicle state, and receiving fixed and moving obstacle information. The method includes adjusting the path to generate an optimized path that avoids the fixed and moving obstacles and ends at a targeted final vehicle state, and navigating the autonomous vehicle based on the optimized path.

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