A Low-Cost Vector Map Assisted Navigation Method for Autonomous Vehicle


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    Traditional differential global positioning system usually demands high-definition map to realize automatic path tracking. However, the high-definition map occupies large storage space and requires highperformance on-board computer or large communication bandwidth. In this paper, a low-cost vector mapbased navigation method for autonomous vehicle is introduced. By recording the vector map offline, the method initializes an optimal global route by giving any starting and ending position on the map. During runtime, the in-vehicle computer filters the real-time positioning data from differential global positioning system and tracks the planned path according to geometric rules. While any obstacles are detected, the system can adjust the local path automatically. In addition, the proposed method can calculate the angle of steering wheel, levels of throttle, brake pedals in real-time, and transmit these actuation commands through controller area network bus interface. Feasibility and accuracy of the proposed navigation method is verified on our autonomous vehicle testing platform.

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LI Wenda, WANG Zheng, LI Huiyun, et al. A Low-Cost Vector Map Assisted Navigation Method for Autonomous Vehicle[J]. Journal of Integration Technology,2018,7(6):69-80

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  • Online: November 20,2018
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