Comparative Study on Solving the Minimum Fleet of Shared Autonomous Vehicles

被引:0
|
作者
Wang, Guan [1 ]
机构
[1] Wuhan Planning & Design Co Ltd, Wuhan, Hubei, Peoples R China
来源
CICTP 2020: TRANSPORTATION EVOLUTION IMPACTING FUTURE MOBILITY | 2020年
关键词
Shared autonomous vehicle; Minimum fleet size; Graph theory; Hopcroft-Karp algorithm; Multiple travelling salesman problem; Genetic algorithm;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Assuming that all travel demands are met by shared autonomous vehicle (SAV), the paper compares graph theory method and the multiple travelling salesman problem (MTSP) method in solving the minimum fleet size problem. With the trajectory data of 50 new energy private cars in Shanghai for 1 year, travel demands are extracted. A specific method for calculating whether two trips can be served by one SAV is developed. Then, the minimum fleet size problem are transformed into the minimum path cover problem on directed graph (graph theory method) and MTSP shortest path problem (MTSP method). Hopcroft-Karp algorithm is adopted in graph theory method, while genetic algorithm (GA) is adopted in the MTSP method. Results show that graph theory method outperforms the MTSP method both in the quality of solution and the computing time. Results indicate that a SAV can replace 2.5 traditional private cars on average.
引用
收藏
页码:522 / 534
页数:13
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