A 5G-V2X Based Collaborative Motion Planning for Autonomous Industrial Vehicles at Road Intersections
| Autor: | Zihui Zhang, Yaohui Pan, Yanjun Shi, Yu Xiao, Yanqiang Li |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Operations research ta213 Computer science business.industry 010401 analytical chemistry Automotive industry 02 engineering and technology 01 natural sciences 0104 chemical sciences 020901 industrial engineering & automation Motion planning business 5G Intersection (aeronautics) |
| Zdroj: | SMC |
| Popis: | Self-driving and connected vehicles, communicating with one another and with the road infrastructure are expected to revolutionize the automotive industry and our life in the future. We propose a distributed heuristic algorithm based on 5G-V2X technology to solve the motion planning problem of industrial vehicles, especially passing through intersections in industrial parks. Autonomous industrial vehicles must not only ensure that vehicles do not collide with each other through intersections, but also ensure the safety of pedestrians. So this case demands highly on the communication and mutual cooperation among vehicles. To solve this problem, we employ 5G-V2X technology to ensure low delay and highly reliable communications. Then, we propose a distributed heuristic algorithm to solve the mutual cooperation problem among vehicles. Specifically speaking, intersection safety information system will download LDM (Local Dynamic Map) information to vehicle closest to the intersection, and then our solution will give higher priority to paths that have more vehicles and no pedestrians. Starting with highest priority approach, our solution sets a time period for the vehicle to establish a timetable for it to cross the intersection. Preliminary experiments results showed that on the premise of ensuring the safety of pedestrians, the industrial vehicles can pass through the intersection smoothly and have the lowest delay at the same time. |
| Databáze: | OpenAIRE |
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