System and method for autonomous vehicle control to minimize energy cost

    公开(公告)号:US12253850B2

    公开(公告)日:2025-03-18

    申请号:US18510352

    申请日:2023-11-15

    Applicant: TUSIMPLE, INC.

    Abstract: A system and method for autonomous vehicle control to minimize energy cost are disclosed. A particular embodiment includes: generating a plurality of potential routings and related vehicle motion control operations for an autonomous vehicle to cause the autonomous vehicle to transit from a current position to a desired destination; generating predicted energy consumption rates for each of the potential routings and related vehicle motion control operations using a vehicle energy consumption model; scoring each of the plurality of potential routings and related vehicle motion control operations based on the corresponding predicted energy consumption rates; selecting one of the plurality of potential routings and related vehicle motion control operations having a score within an acceptable range; and outputting a vehicle motion control output representing the selected one of the plurality of potential routings and related vehicle motion control operations.

    Method and system for modeling autonomous vehicle behavior

    公开(公告)号:US12001208B2

    公开(公告)日:2024-06-04

    申请号:US17184438

    申请日:2021-02-24

    Applicant: TUSIMPLE, INC.

    Abstract: The system and method make it feasible to develop an autonomous vehicle control system for complex vehicles, such as for cargo trucks and other large payload vehicles. The method and system commence by first obtaining 3-dimensional data for one or more sections of roadway. Once the 3-dimensional roadway data is obtained, that data is used to run computer simulations of a computer model of a specific vehicle being controlled by a generic vehicle control algorithm or system. The generic vehicle control algorithm is optimized by running the simulations utilizing the 3-dimensional roadway data until an acceptable performance result is achieved. Once an acceptable simulation is executed using the generic vehicle control algorithm, the control algorithm/system is used to run one or more real-world driving tests on the roadway for which the 3-dimensional data was obtained. Finally, the computer model for the vehicle is modified.

    Neural network based vehicle dynamics model

    公开(公告)号:US10895877B2

    公开(公告)日:2021-01-19

    申请号:US15672207

    申请日:2017-08-08

    Applicant: TuSimple, Inc.

    Abstract: A system and method for implementing a neural network based vehicle dynamics model are disclosed. A particular embodiment includes: training a machine learning system with a training dataset corresponding to a desired autonomous vehicle simulation environment; receiving vehicle control command data and vehicle status data, the vehicle control command data not including vehicle component types or characteristics of a specific vehicle; by use of the trained machine learning system, the vehicle control command data, and vehicle status data, generating simulated vehicle dynamics data including predicted vehicle acceleration data; providing the simulated vehicle dynamics data to an autonomous vehicle simulation system implementing the autonomous vehicle simulation environment; and using data produced by the autonomous vehicle simulation system to modify the vehicle status data for a subsequent iteration.

    SYSTEM AND METHOD FOR PROVIDING MULTIPLE AGENTS FOR DECISION MAKING, TRAJECTORY PLANNING, AND CONTROL FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20200371521A1

    公开(公告)日:2020-11-26

    申请号:US16991599

    申请日:2020-08-12

    Applicant: TUSIMPLE, INC.

    Abstract: A system and method for providing multiple agents for decision making, trajectory planning, and control for autonomous vehicles are disclosed. A particular embodiment includes: partitioning a multiple agent autonomous vehicle control module for an autonomous vehicle into a plurality of subsystem agents, the plurality of subsystem agents including a deep computing vehicle control subsystem and a fast response vehicle control subsystem; receiving a task request from a vehicle subsystem; dispatching the task request to the deep computing vehicle control subsystem or the fast response vehicle control subsystem based on the content of the task request or a context of the autonomous vehicle; causing execution of the deep computing vehicle control subsystem or the fast response vehicle control subsystem by use of a data processor to produce a vehicle control output; and providing the vehicle control output to a vehicle control subsystem of the autonomous vehicle.

    System and method for real world autonomous vehicle trajectory simulation

    公开(公告)号:US12242274B2

    公开(公告)日:2025-03-04

    申请号:US18536635

    申请日:2023-12-12

    Applicant: TuSimple, Inc.

    Abstract: A system and method for real world autonomous vehicle trajectory simulation may include: receiving training data from a data collection system; obtaining ground truth data corresponding to the training data; performing a training phase to train a plurality of trajectory prediction models; and performing a simulation or operational phase to generate a vicinal scenario for each simulated vehicle in an iteration of a simulation. Vicinal scenarios may correspond to different locations, traffic patterns, or environmental conditions being simulated. Vehicle intention data corresponding to a data representation of various types of simulated vehicle or driver intentions.

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