A carpool matching model with both social and route networks |
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| Affiliation: | 1. Guangdong Key Laboratory of Urban Informatics, Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen, China;2. Department of Geography, University of Alabama, AL, United States;3. China Three Gorges International Corporation, China;4. Shenzhen Urban Public Safety and Technology Institute, China;5. Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen, China |
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| Abstract: | Carpooling is an effective solution for traffic congestion. However, social obstructions (lack of trust) and cost obstructions (high commute cost) are still two major challenges for promoting carpool activities. In this paper, a social-route-network carpooling model (SRNC model) is proposed. The model combines commuters' social networks and commute route networks to provide optimization on both trust and cost in different carpooling teams. The trust optimization improves the social comfort between commuters by introducing the concept of degrees-of-separation and the user preference. The cost optimization reduces the total commute distance with integer programming model. Finally, both trust and cost are balanced in a unified model—the SRNC model. By using the Twitter social network and the Washington, D.C. road network, the SRNC model is evaluated. Results demonstrate a significantly improvement of the trust (around decuple) with a small loss in route cost (around 6.3%) as compared to a route-network-only carpooling model. |
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