GPS data in urban online car-hailing: Simulation on optimization and prediction in reducing void cruising distance

Wang，Yuxuan1; Chen，Jinyu1; Xu，Ning2; Li，Wenjing1; Yu，Qing1,3; Song，Xuan1,4

2020

10.1155/2020/6890601

MATHEMATICAL PROBLEMS IN ENGINEERING   影响因子和分区

1024-123X

1563-5147

Ride-hailing, as a popular shared-transportation method, has been operated in many areas all over the world. Researchers conducted various researches based on global cases. They argued on whether car-hailing is an effective travel mode for emission reduction and drew different conclusions. The detailed emission performance of the ride-hailing system depends on the cases. Therefore, there is an urgent demand to reduce the overall picking up distance during the dispatch. In this study, we try to satisfy this demand by proposing an optimization method combined with a prediction model to minimize the global void cruising distance when solving the dispatch problem. We use Didi ride-hailing data on one day for simulation and found that our method can reduce the picking up distance by 7.51% compared with the baseline greedy algorithm. The proposed algorithm additionally makes the average waiting time of passengers more than 4 minutes shorter. The statistical results also show that the performance of our method is stable. Almost the metric in all cases can be kept in a low interval. What is more, we did a day-to-day comparison. We found that, despite the different spatial-temporal distribution of orders and drivers on different day conditions, there are little differences in the performance of the method. We also provide temporal analysis on the changing pattern of void cruising distance and quantity of orders on weekdays and weekends. Our findings show that our method can averagely reduce more void cruising distance when ride-hailing is active compared with the traditional greedy algorithm. The result also shows that the method can stably reduce void cruising distance by about 4000 to 5000 m per order across one day. We believe that our findings can improve deeper insight into the mechanism of the ride-hailing system and contribute to further studies.

SCI ; EI

英语

通讯

Engineering ; Mathematics

Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications

WOS:000598345200005

HINDAWI LTD

20205109623547

Air Pollution Control:451.2

ENGINEERING

2-s2.0-85097579020

Scopus

1.Center for Spatial Information Science,University of Tokyo,Kashiwa Chiba,5-1-5 Kashiwanoha,277-8563,Japan
2.Beijing Key Laboratory of Urban Oil and Gas Distribution Technology,China University of Petroleum-Beijing,Changping District, Beijing,Fuxue Road No. 18,102249,China
3.Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai,4800 Cao’an Road,201804,China
4.SUSTech-UTokyo Joint Research Center on Super Smart City,Department of Computer Science and Engineering,Southern University of Science and Technology (SUSTech),Shenzhen,China

Wang，Yuxuan,Chen，Jinyu,Xu，Ning,et al. GPS data in urban online car-hailing: Simulation on optimization and prediction in reducing void cruising distance[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2020,2020.

Wang，Yuxuan,Chen，Jinyu,Xu，Ning,Li，Wenjing,Yu，Qing,&Song，Xuan.(2020).GPS data in urban online car-hailing: Simulation on optimization and prediction in reducing void cruising distance.MATHEMATICAL PROBLEMS IN ENGINEERING,2020.

Wang，Yuxuan,et al."GPS data in urban online car-hailing: Simulation on optimization and prediction in reducing void cruising distance".MATHEMATICAL PROBLEMS IN ENGINEERING 2020(2020).