Abstract
Taxi sharing is a promising approach to reducing energy consumptions, utilizing limited taxi resources efficiently while preserving the interest of individuals. The existing studies mostly fail to locate a pick-up/drop-off point for each individual passenger in scheduling the sharing route. Besides, they can hardly provide personalized services. To this end, we propose a new taxi-sharing system called Flexi-Sharing to provide flexible and personalized taxi sharing services. It considers the nearby alternative pick-up/drop-off locations and schedules a flexible sharing route with the maximum reduced travel distance by letting passengers walk a short distance. For a sharing request, Flexi-Sharing generates the sharing schedule consisting of a set of companions, the shortest sharing route and the best pick-up/drop-off locations by maximizing the satisfaction of involved passengers. Extensive experiments are conducted using a one-month taxi trajectory data collected in Chengdu, China. Experimental results show that Flexi-Sharing achieves 60% sharing rate and reduces 28 000 km travel distances per hour in the city, which are 15% higher and 16% longer than those of the method that delivers passengers at exact requested locations, respectively. Flexi-Sharing also promises a satisfactory system response time and provides superior sharing experiences.
Original language | English |
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Article number | 8786246 |
Pages (from-to) | 9399-9413 |
Number of pages | 15 |
Journal | IEEE Transactions on Vehicular Technology |
Volume | 68 |
Issue number | 10 |
DOIs | |
Publication status | Published - Oct 2019 |
Scopus Subject Areas
- Automotive Engineering
- Aerospace Engineering
- Electrical and Electronic Engineering
- Applied Mathematics
User-Defined Keywords
- intelligent transportation systems
- location-based services
- Taxi sharing
- taxi trajectories