期刊
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
卷 23, 期 5, 页码 4187-4200出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2020.3042603
关键词
Planning; Path planning; Autonomous vehicles; Trajectory; Safety; Acceleration; Vehicle dynamics; Autonomous vehicles; path planning; autonomous systems; system analysis and design
资金
- National Natural Science Foundation of China [61773312, 61790563]
This article analyzes the issues with current path planning frameworks in autonomous driving systems and proposes a global path planning framework based on multiple models. The framework divides the planning process into layers and adaptsively adjusts the process according to changes in traffic scenes, ensuring safety and flexibility in driving.
Autonomous driving systems (ADSs) need to be able to respond quickly to changes in the dynamic traffic scenario. However, regardless of the changes occurring in traffic scenes, the current local path planning frameworks of ADSs are based on the fixed frequency re-planning path (i.e., running their planning algorithms repeatedly). This planning method makes it difficult to provide a reasonable traveling path, agility, and comfort for driverless vehicles in changing traffic scenarios. Therefore, this article performs an in-depth analysis of the problems of traditional planning frameworks which use a fixed frequency to replan the path and proposes a novel path planning framework that is universal based on multiple-models. The proposed framework divides the planning process into several layers, each of which has different functions. With this framework, the ADS can adaptively adjust the planning process according to the changes in traffic scenes and then provide different path planning algorithms to ensure its safety and flexibility in the process of driving. Moreover, the problems caused by the traditional planning framework can be solved. This framework has been applied to the autonomous vehicle Pioneer, which won first place in the 2019 China Intelligent Vehicle Future Challenge (IVFC). The effectiveness and rationality of the integrated framework of local path planning proposed in this article were verified by a large number of tests in real-world traffic scenarios.
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