Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle Navigation
Lane-level route planning is a critical issue for a lane-level navigation system for autonomous vehicles. Current route-planning methods mainly focus on the road level and applying them directly to search for lane-level routes results in a reduction in search efficiency. In addition, previously deve...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/14/4/98 |
| _version_ | 1797603131588083712 |
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| author | Ke He Haitao Ding Nan Xu Konghui Guo |
| author_facet | Ke He Haitao Ding Nan Xu Konghui Guo |
| author_sort | Ke He |
| collection | DOAJ |
| description | Lane-level route planning is a critical issue for a lane-level navigation system for autonomous vehicles. Current route-planning methods mainly focus on the road level and applying them directly to search for lane-level routes results in a reduction in search efficiency. In addition, previously developed lane-level methods lack consideration for vehicle characteristics and adaptability to multiple road network structures. To solve this issue, this study proposes an accelerated and refined lane-level route-planning algorithm based on a new lane-level road network model. First, five sub-layers are designed to refine the internal structure of the divided road and intersection areas so that the model can express multiple variations in road network structures. Then, a multi-level route-planning algorithm is designed for sequential planning at the road level, lane group level, lane section level, and lane level to reduce the search space and significantly improve routing efficiency. Last, an optimal lane determination algorithm considering traffic rules, vehicle characteristics, and optimization objectives is developed at the lane level to find the optimal lanes on roads with different configurations, including those with a constant or variable number of lanes while satisfying traffic rules and vehicle characteristics. Tests were performed on simulated road networks and a real road network. The results demonstrate the algorithm’s better adaptability to changing road network structures and vehicle characteristics compared with past hierarchical route planning, and its higher efficiency compared with direct route planning, past hierarchical route planning, and the Apollo route-planning method, which can better support autonomous vehicle navigation. |
| first_indexed | 2024-03-11T04:25:03Z |
| format | Article |
| id | doaj.art-555b7d61e67a441a881b8feb5500e2a5 |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-11T04:25:03Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-555b7d61e67a441a881b8feb5500e2a52023-11-17T21:50:09ZengMDPI AGWorld Electric Vehicle Journal2032-66532023-04-011449810.3390/wevj14040098Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle NavigationKe He0Haitao Ding1Nan Xu2Konghui Guo3State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaState Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, ChinaLane-level route planning is a critical issue for a lane-level navigation system for autonomous vehicles. Current route-planning methods mainly focus on the road level and applying them directly to search for lane-level routes results in a reduction in search efficiency. In addition, previously developed lane-level methods lack consideration for vehicle characteristics and adaptability to multiple road network structures. To solve this issue, this study proposes an accelerated and refined lane-level route-planning algorithm based on a new lane-level road network model. First, five sub-layers are designed to refine the internal structure of the divided road and intersection areas so that the model can express multiple variations in road network structures. Then, a multi-level route-planning algorithm is designed for sequential planning at the road level, lane group level, lane section level, and lane level to reduce the search space and significantly improve routing efficiency. Last, an optimal lane determination algorithm considering traffic rules, vehicle characteristics, and optimization objectives is developed at the lane level to find the optimal lanes on roads with different configurations, including those with a constant or variable number of lanes while satisfying traffic rules and vehicle characteristics. Tests were performed on simulated road networks and a real road network. The results demonstrate the algorithm’s better adaptability to changing road network structures and vehicle characteristics compared with past hierarchical route planning, and its higher efficiency compared with direct route planning, past hierarchical route planning, and the Apollo route-planning method, which can better support autonomous vehicle navigation.https://www.mdpi.com/2032-6653/14/4/98lane-levelroad network modelroute planning |
| spellingShingle | Ke He Haitao Ding Nan Xu Konghui Guo Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle Navigation World Electric Vehicle Journal lane-level road network model route planning |
| title | Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle Navigation |
| title_full | Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle Navigation |
| title_fullStr | Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle Navigation |
| title_full_unstemmed | Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle Navigation |
| title_short | Accelerated and Refined Lane-Level Route-Planning Method Based on a New Road Network Model for Autonomous Vehicle Navigation |
| title_sort | accelerated and refined lane level route planning method based on a new road network model for autonomous vehicle navigation |
| topic | lane-level road network model route planning |
| url | https://www.mdpi.com/2032-6653/14/4/98 |
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