期刊
IEEE ACCESS
卷 8, 期 -, 页码 160396-160406出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3020861
关键词
Public transportation; Vehicle dynamics; Roads; Dispatching; Real-time systems; Urban areas; Delays; Dispatching strategies; dynamic ridesharing; ridesharing efficiency; carrying capacity
资金
- National Natural Science Foundation of China [61803100, U1911401]
- Guangdong Provincial Key Laboratory of Intelligent Transportation System [202005003]
- Science and Technology Planning Project of Guangdong Province, China [2019B010121001, 2019B010118001, 2019B01019001]
- Industrial Internet innovation and development project of Ministry of Industry and Information Technology of the People's Republic of China [TC190A3X9-2-2]
- National Key Research and Development Project, China [2018YFB1802400]
The application of ridesharing strategy to autonomous taxi system holds great promise for improving the efficiency in the future on-demand ride-hailing services. Prior to the implementation of dispatching strategies to the autonomous taxi system, it is necessary to gain insight into the performance of the dispatching strategies. This study aims to solve the dynamic ridesharing problem and conduct a comprehensive quantity analysis of the ridesharing efficiency for various demand levels and carrying capacities in a metropolitan area. We quantify the success rate of serviced requests, the trip travel time, the discount rate of taxi fare, and total energy consumption for different carrying capacities and demand levels in the road network of Shenzhen city. The simulation results show that the ride-matching success rate within 3 minutes enables to increase by more than 13% in the ridesharing mode, and over 80% of the passengers can be served within 6 minutes if the carrying capacity is set to four. The trip travel time and energy consumption also show a significant downward trend as the capacity of the taxi increases in the ridesharing mode.
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