Abstract
Ride-sharing is considered as one of the promising solutions for reducing fuel consumption of fuel and reducing the congestion in urban cities, hence reducing the environmental pollution. With the advancement of mobile social networking technologies, it is necessary to reconsider the principles and desired characteristics of ride-sharing systems. Ride-sharing systems can be popular among people if we can provide more flexible and adaptive solution according to preferences of the participants and solve the social challenges. In this paper, we focus on encouraging people to use a ride-sharing system by satisfying their demands in terms of safety, privacy, convenience and also provide enough incentives for drivers and riders. We formalized the ride sharing problem as a multi source-destination path planning problem. An objective function is developed which models different conflicting objectives in a unified framework. We provide the flexibility to each driver that he can generate the sub-optimal paths according to his own requirements by suitably adjusting the weights. These sub-optimal paths are generated in an order of priority (optimality). The simulation results have shown that the system has the potential to compute multiple optimal paths.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Vanoutrive, T., Van De Vijver, E., Malderen, L.V., Jourquin, B., Thomas, I., Verhetsel, A., Witlox, F.: What determines carpooling to workplaces in Belgium: location, organisation, or promotion? Journal of Transport Geography 22, 77–86 (2012)
Trasarti, R., Pinelli, F., Nanni, M., Giannotti, F.: Mining mobility user profiles for car pooling. In: KDD 2011, pp. 1190–1198 (2011)
Kleiner, A., Nebel, B., Ziparo, V.A.: A Mechanism for Dynamic Ride Sharing Based on Parallel Auctions. In: IJCAI 2011, pp. 266–272 (2011)
Herbawi, W., Weber, M.: Evolutionary multiobjective route planning in dynamic multi-hop ridesharing. In: Merz, P., Hao, J.-K. (eds.) EvoCOP 2011, pp. 84–95. Springer, Heidelberg (2011)
Agatz, N., Erera, A., Savelsbergh, M., Wang, X.: Sustainable passenger transportation: Dynamic ride-sharing. Tech. rep., Erasmus Research Inst. of Management (ERIM), Erasmus Uni., Rotterdam (2010)
Jeanes, P.: Can total car emissions be reduced enough by 2020? In: Traffic Engineering & Control. PA Associates (January 2010)
Vetter, C.: Fast and Exact Mobile Navigation with OpenStreetMap Data. Diploma thesis, Algorithmics II, University of Karlsruhe, Germany (2010)
Kirshner, D.: Ride Now (2010), http://www.ridenow.org
Morris, J.H.: SafeRide: Reducing Single Occupancy Vehicles. Carnegie Mellon school of computer science, Tech. Rep. (2009)
Gilbert, E., Karahalios, K.: Predicting tie strength with social media. In: CHI 2009, pp. 211–220. ACM, New York (2009)
Kelley, K.L.: Casual Carpooling - Enhanced. Journal of Public Transportation 10(4), 119–130 (2007)
Murphy, P.: The Smart Jitney: Rapid, Realistic Transport. New Solutions 12, 12 (2007)
Pangilinan, J., Janssens, G.: Evolutionary algorithms for the multi-objective shortest path problem. IJASET 4(1), 205–210 (2007)
Mooney, P., Winstanley, A.: An evolutionary algorithm for multicriteria path optimization problems. IJGIS 20, 401–423 (2006)
Roozbeh, S., Hamid, E., Mohsen, G.: Evaluation of route finding methods in GIS application. In: Map Asia 2003, Bejing, China, pp. 12–20 (2003)
Resnick, P.: SocioTechnical Support for Ride Sharing. University of Michigan, School of Information, Tech. Rep. (2003)
Müller-Hannemann, M., Weihe, K.: Pareto Shortest Paths is Often Feasible in Practice. In: Brodal, G.S., Frigioni, D., Marchetti-Spaccamela, A. (eds.) WAE 2001. LNCS, vol. 2141, pp. 185–197. Springer, Heidelberg (2001)
Martins, E., Santos, J.: The labeling algorithm for the multiobjective shortest path problem. Tech. rep., University of Coimbra, Portugal (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yousaf, J., Li, J., Chen, L., Tang, J., Dai, X., Du, J. (2012). Ride-Sharing: A Multi Source-Destination Path Planning Approach. In: Thielscher, M., Zhang, D. (eds) AI 2012: Advances in Artificial Intelligence. AI 2012. Lecture Notes in Computer Science(), vol 7691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35101-3_69
Download citation
DOI: https://doi.org/10.1007/978-3-642-35101-3_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35100-6
Online ISBN: 978-3-642-35101-3
eBook Packages: Computer ScienceComputer Science (R0)