基于优化的自动驾驶运动基元自动机

IF 0.7 4区计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS

At-Automatisierungstechnik Pub Date : 2023-04-01 DOI:10.1515/auto-2022-0158

Matheus V. A. Pedrosa, Patrick Scheffe, Bassam Alrifaee, K. Flaßkamp

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引用次数: 0

摘要

摘要自动驾驶汽车的轨迹规划可以通过基于基元的方法来解决，该方法将非线性动力系统的行为编码为自动机。在本文中，我们关注的是最优轨迹规划。由于通常必须考虑多个标准，因此必须解决多目标优化问题。对于由此产生的Pareto最优运动基元，我们引入了一种通用自动机，它可以在规划过程中根据优先级标准进行减少或重新配置。我们通过模拟和实验室实验评估了相应的多车辆规划场景。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimization-based motion primitive automata for autonomous driving

Abstract Trajectory planning for autonomous cars can be addressed by primitive-based methods, which encode nonlinear dynamical system behavior into automata. In this paper, we focus on optimal trajectory planning. Since, typically, multiple criteria have to be taken into account, multiobjective optimization problems have to be solved. For the resulting Pareto-optimal motion primitives, we introduce a universal automaton, which can be reduced or reconfigured according to prioritized criteria during planning. We evaluate a corresponding multi-vehicle planning scenario with both simulations and laboratory experiments.

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来源期刊

At-Automatisierungstechnik 工程技术-自动化与控制系统

CiteScore

2.00

自引率

10.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Automatisierungstechnik (AUTO) publishes articles covering the entire range of automation technology: development and application of methods, the operating principles, characteristics, and applications of tools and the interrelationships between automation technology and societal developments. The journal includes a tutorial series on "Theory for Users," and a forum for the exchange of viewpoints concerning past, present, and future developments. Automatisierungstechnik is the official organ of GMA (The VDI/VDE Society for Measurement and Automatic Control) and NAMUR (The Process-Industry Interest Group for Automation Technology). Topics control engineering digital measurement systems cybernetics robotics process automation / process engineering control design modelling information processing man-machine interfaces networked control systems complexity management machine learning ambient assisted living automated driving bio-analysis technology building automation factory automation / smart factories flexible manufacturing systems functional safety mechatronic systems.