On this page I am collecting references related to market-based on-demand transport. To distinguish between different approaches, I am using the classification introduced here. If you are an author of a paper is related to market-based on-demand transport and there is not yet a reference, please contact me at malcolm (dot) egan (at) gmail (dot) com.
In On-Demand Transport
Yang, H., Ye, M., Tang, W. and Wong, S., “A multiperiod dynamic model of taxi services with endogeneous service intensity,” Operations Research, vol. 53, no. 3, pp. 501-515, 2005.
Egan, M. and Jakob, M., “A profit-aware negotation mechanism for on-demand transport services,” in Proc. European Conference on Artificial Intelligence (ECAI), 2014.
Egan, M. and Jakob, M., “Market mechanism design for profitable on-demand transport services,” Transportation Research Part B, vol. 89, pp. 178-195
Gan, J., An, B., Wang, H., Sun, X. and Shi, Z., “Optimal pricing for improving efficiency of taxi systems,” in Proc. International Joint Conference on Artificial Intelligence (IJCAI), 2013.
Gan, J., An, B. and Miao, C., “Optimizing efficiency of taxi systems: scaling-up and handling arbitrary constraints,” in Proc. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2015.
Gan, J. and An, B., “Game theoretic considerations for optimizing efficiency of taxi systems,” in Proc. AAAI-15 Workshop on Computational Sustainability, 2015.
Gan, J. and An, B., “Game theoretic considerations for optimizing taxi system efficiency,” in IEEE Intelligent Systems, vol. 32, no. 3, pp. 46-52, 2017.
Zeng, C. and Oren, N., “Dynamic taxi pricing,” in Proc. European Conference on Artificial Intelligence, 2014.
Borgs, C., Candogan, J., Chayes, J., Lobel, I. and Nazerzadeh, H., “Optimal multiperiod pricing with service guarantees,” Management Science, vol. 60, no. 7, pp. 1792-1811, 2014.
Chawla, S., Hartline, J., Malec, D. and Siva, B., “Multi-parameter mechanism design and sequential posted pricing,” in Proc. ACM Conference on Theory of Computing (STOC), 2010.
Kleinberg, R. and Leighton, T., “The value of knowing a demand curve: bounds on regret for on-line posted-price auctions,” in Proc. IEEE Symposium on Foundations of Computer Science, 2003.
Besbes, O. and Zeevi, A., “Dynamic pricing without knowing the demand function: risk bounds and near-optimal algorithms,” Operations Research, vol. 57, no. 6, pp. 1407-1420, 2009.
Wang, R., “Auctions versus posted-price selling,” The American Economic Review,” vol. 83, no. 4, pp. 838-851, 1993.
Auer, P., Cesa-Bianchi, N. and Fischer, P., “Finite-time analysis of the multiarmed bandit problem,” Machine Learning, vol. 47, no. 2, pp. 235-256, 2002.
Double Auction Mechanisms
In On-Demand Transport
Egan, M., Schaefer, M., Jakob, M. and Oren, N., “A double auction mechanism for on-demand transport networks,” in Proc. PRIMA2015: Principles and Practice of Multi-Agent Systems, 2015.
Zhou, L. and Xu, H., “An efficient double auction mechanism for on-demand transport services in cloud-based mobile commerce,” in Proc. IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, 2017.
Zhang, J., Wen, D. and Zeng, S., “A discounted trade reduction mechanism for dynamic ridesharing pricing,” IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 6, pp. 1586-1595, 2015.
Haque, A., Alhashmi, S.M. and Parthiban, R., “A survey of economic models in grid computing,” Future Generation Computer Systems, vol. 27, no. 8, pp. 1056-1069, 2011.
Shoham, Y. and Leyton-Brown, K., Multiagent Systems: Algorithmic, game-theoretic, and logical foundations. Cambridge University Press, 2008.
McAfee, R., “Dominant strategy double auction,” Journal of Economic Theory, vol. 56, no. 2, pp. 434-450, 1992.
Parkes, D., “Online Mechanisms”, in N. Nissan et al. editors, Algorithmic Game Theory, Cambridge University Press, 2007.
Bredin, J., Parkes, D. and Duong, Q., “Chain: a double auction mechanism for matching patients,” Journal of Artificial Intelligence Research, vol. 30, pp. 133-179, 2007.
Bredin, J. and Parkes, D., “Models for truthful online double auctions,” in Proc. Conference on Uncertainty in Artificial Intelligence, 2007.
Myerson, R.B. and Satterthwaite, M.A., “Efficient mechanisms for bilateral trading,” Journal of Economic Theory, vol. 29, pp. 265-281, 1983.
Mrkos, J., Drchal J., Egan, M. and Jakob, M., “Liftago on-demand transport dataset and market formation algorithm based on machine learning,”, available https://arxiv.org/pdf/1608.02858, 2016.
Egan, M., Oren, N. and Jakob, M., “Hybrid mechanisms for on-demand transport,” accepted for publication in IEEE Transactions on Intelligent Transportation.
Čertický, M., Jakob, M., Píbil, R. and Moler, Z., “Agent-based simulation testbed for on-demand mobility services,” In Proc. of the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2014. [Software available here]
Nykl, J., Jakob, M. and Hrncir, J., “Advanced public transport network analyzer,” in Proc. of the European Conference on Artificial Intelligence, 2014.
The Dial-A-Ride Problem and Taxi Scheduling
Cordeau, J.-F., “The dial-a-ride problem: models and algorithms,” Annals of Operations Research, vol. 153, pp. 29-46, 2007.
Barbucha, D., “A multi-agent approach to the dynamic vehicle routing problem with time windows,” in Proc. of the International Conference on Computational Collective Intelligence, 2013.
Cubillos, C., Guido-Polanco, F. and Demartini, C., “Madarp: multi-agent architecture for passenger transportation systems,” in Proc. IEEE International Conference on Intelligent Transport Systems, 2005.
Glaschenko, A., Ivaschencko, A., Rzevski, G. and Skobolev, P., “Multi-agent real time scheduling system for taxi companies,” in Proc. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2009.
Bai, R., Li, J., Atkin, J. and Kendell, G., “A novel approach to independent taxi scheduling problem based on stable matching,” Journal of the Operational Research Society, vol. 65, 2014.
Seow, K., Dang, N. and Lee, D.-H., “A collaborative multi-agent taxi-dispatch system,” IEEE Transactions on Automation Science and Engineering, vol. 7, no. 3, 2010.
Dumas, Y., Desrosiers, J. and Soumis, F., “The pickup and delivery problem with time windows,” European Journal of Operations Research, vol. 54, pp. 7-22, 1991.
Vidal, T., Crainic, T., Gendreau, M. and Prins, C., “Timing problems and algorithms: time decisions for sequences of activities,” Networks, vol. 65, no. 2, pp. 102-128, 2015.
Kümmel, M., Busch, F. and Wang, D., “Framework for automated taxi operation: the family model,” Transport Research Procedia, vol. 22, pp. 529-540, 2017.
Demand and Trip Information Estimation
Balan, R., Khoa, N. and Jiang, L., “Real-time trip information service for a large taxi fleet,” in Proc. International Conference on Mobile Systems, Applications, and Services, 2011.
Guo, S., Liu, Y., Xu, K., and Chiu, D., “Understanding ride-on-demand service: demand and dynamic pricing,” in Proc. IEEE International Conference on Pervasive Computing and Communications Workshops, 2017.
Guo, S., Liu, Y., Xu, K., and Chiu, D., “Understanding passenger reaction to dynamic prices in ride-on-demand service,” in Proc. IEEE International Conference on Pervasive Computing and Communications Workshops, 2017.
Moreira, L., Gama, J., Ferreira, M., Mendes-Moreira, J. and Damas, J., “Predicting taxi-passenger demand using streaming data,” IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 3, pp. 1393-1402, 2013.
Equilibrium Properties of Taxi Markets
Yang, H. and Yang, T., “Equilibrium properties of taxi markets with search frictions,” Transportation Research Part B: Methodological, vol. 45, no. 4, pp. 696-713, 2011.
Yang, H., Ye, M., Tang, W. and Wong, S., “Regulating taxi services in the presence of congestion externality,” Transportation Research Part A, vol. 39, pp. 17-40, 2005.
Yang, H., Fung, C., Wong, K. and Wong, S., “Nonlinear pricing of taxi services,” Transportation Research Part A: Policy and Practice,” vol. 44, no. 5, pp. 337-348, 2010.
Related Economic and Public Policy Literature
Cont, R., “Empirical properties of asset returns: stylized facts and statistical issues,” Quantitative Finance, vol. 1, pp. 223-236, 2001.
Tesfatsion, L., “Introduction to the special issue on agent-based computational economics,” Journal of Economic Dynamics and Control, vol. 25, no. 3-4, pp. 281-292, 2001.
Brooks, C. and Durfee, E., “Congregating and market formation,” in Proc. International Joint Conference on Autonomous Agents and Multiagent Systems, 2002.
Verplanken, B. and Wood, W., “Interventions to break and create customer habits,” Journal of Public Policy and Marketing, vol. 25, no. 1, pp. 90-103, 2006.
Cruz, M., Peters, G. and Shevshenko, P., Fundamental Aspects of Operational Risk and Insurance Analytics, Wiley, 2015.
Related Machine Learning Literature
Pedregosa, F. et al., “Scikit-learn: machine learning in Python,” Journal of Machine Learning Research, vol. 12, pp. 2825-2830, 2011.
Breiman, L., “Random forests,” Machine Learning, vol. 45, no. 1, pp. 5-32, 2001.