Author(s)

Kevin M. Curtin 

Published

2019

Citation

Xia, J., K.M. Curtin, J. Huang, D. Wu, W. Xiu, & Z. Huang. 2019. A carpool matching model with both social and route networks. Computers, Environment and Urban Systems 75(3): 90-102. https://doi.org/10.1016/j.compenvurbsys.2019.01.008.

Publication URL

Link

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.