期刊
ENGINEERING
卷 5, 期 2, 页码 305-318出版社
ELSEVIER
DOI: 10.1016/j.eng.2018.11.032
关键词
Lane-level; Route planning; Tsinghua map model; Travel cost model
资金
- National Key Research and Development Program of China [2018YFB0105000]
- National Natural Science Foundation of China [61773234, U1864203]
- Project of Tsinghua University
- Toyota Joint Research Center for AI Technology of Automated Vehicle [TT2018-02]
- International Science and Technology Cooperation Program of China [2016YFE0102200]
- Beijing Municipal Science and Technology Program [D171100005117001, Z181100005918001]
An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety. In the near future, digital map navigation systems are expected to play more important roles in transportation systems. In order to extend current navigation systems to more applications, two fundamental problems must be resolved: the lane-level map model and lane-level route planning. This study proposes solutions to both problems. The current limitation of the lane-level map model is not its accuracy but its flexibility; this study proposes a novel seven-layer map structure, called as Tsinghua map model, which is able to support autonomous driving in a flexible and efficient way. For lane-level route planning, we propose a hierarchical route-searching algorithm to accelerate the planning process, even in the presence of complicated lane networks. In addition, we model the travel costs allocated for lane-level road networks by analyzing vehicle maneuvers in traversing lanes, changing lanes, and turning at intersections. Tests were performed on both a grid network and a real lane-level road network to demonstrate the validity and efficiency of the proposed algorithm. (C) 2019 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.
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