News | The Transportation Marketplace: A Real-time System in Support of Dynamic Ridesharing

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METRANS Celebrates 20 Years of Research

This article is part of an ongoing series that describes research accomplishments and achievements of the METRANS Transportation Center in recognition of its 20th Anniversary. The author is Dr. Maged Dessouky, Professor and Chair of the Daniel J. Epstein Department of Industrial and Systems Engineering in the Viterbi School of Engineering at the University of Southern California. His research has been funded by the National Science Foundation, Society of Manufacturing Engineers, PATH, Caltrans, FTA, Department of Defense, and Department of Homeland Security and its National Center for Risk and Economic Analysis of Terrorism Events (CREATE) among others.

The Transportation Marketplace: A Real-time System in Support of Dynamic Ridesharing

The transportation sector represents a major part in the current and future United States economy, with more than 10% of the United States’ GDP directly related to transportation activity. The significant congestion and projected demand increases with limited infrastructure investment make necessary the development of significant improvement on transportation systems. Transportation planners must therefore find ways to improve transportation conditions in a cost efficient manner. Significant advances have been made in the procurement and provision of real-time information that would be required for the effective control of a transportation system. Yet, this information is mostly used in centralized transit system design and operation or congestion pricing. These efforts have had limited success to date addressing congestion in most American cities, which have a dispersed demand due to a lack of single high density business and residential centers. Congestion in the US continues to rise, stressing vital infrastructure, causing delayed shipments, late employees, and countless other problems. The increased adoption of dynamic ridesharing as a transportation mode could help alleviate some of this traffic and its related nuisances. Obviously dynamic ridesharing is not the complete answer to congestion nationwide, but its ability to augment existing public infrastructure, such as mass transit, will help to solve many problems.

Our objective is to harness emerging information technologies in an innovative use of new communication systems and computation abilities to develop a new type of decentralized transportation system, the Transportation Market, capable of real-time allocation of resources. The idea is that an intelligent use of traffic information will help users make decisions that will tap into unused vehicle capacity, radically transforming the way people use transportation systems. The proposed Transportation Market is based on developing new intelligent systems that require both the exploitation of a large amount of traffic data to find good coordination policies and an understanding of the transportation system with human and man-made components.

Funding for the prototype development of the Transportation Market was obtained from the FHWA under the Exploratory Advanced Research Program Broad Agency program. Supported by this funding, we created a distributed simulation system for negotiating routes and prices between consumers and providers of transportation in real-time. In particular, we created a networked market for transportation in which consumers and providers of transportation negotiate with each other to determine routes and prices.

A review of the “state-of-the-art” and future challenges of dynamic ridesharing systems was published in Transportation Research Part B: Methodological (our publication is the 3rd highest cited paper since 2013 in this top research journal in the transportation field), and the activities of the primary three research areas of this project included: Market Mechanism and Models, Agent Systems, and Analytic and Planning Tools. Market mechanisms and models determine procedures of negotiation between drivers and passengers with respect to pricing and vehicle assignment. Agent systems aim to maximize profits of transportation providers, subject to constraints such as the capacity of the vehicle, cost of operation, time to stop for gas and geographical constraints, resulting in a difficult computational problem which requires path planning, multivariate optimization, and some forecasting of consumer demand. Analytics and planning tools aim to evaluate the Transportation Market system proposed and help create mechanisms to design, regulate, and operate such a market, which involve optimization problems over the traffic equilibrium achieved when the different users decide their transportation alternatives.

Funds from this project supported six doctoral students and two post-doctoral researchers as well as the Principal Investigators (Professors Dessouky, Ordóñez, and Koenig). Three of the six doctoral students completed dissertations on topics related to dynamic ridesharing. One of them, Huayu Xu, won the Best Dissertation Award by the Viterbi School of Engineering of the University of Southern California in May, 2014. To date, we have published five papers in an archived referred journal, and three conference proceedings on topics related to the Transportation Market.  We also organized an international colloquium on the topic of dynamic ridesharing, which was held on May 6, 2013 at the University of Southern California. The workshop was sponsored by the Federal Highway Administration (FHWA) and the Daniel J. Epstein Institute. Nearly 40 participants attended, among them were members of local governments, professors, private ridesharing firms, and DOTs. Topics discussed were the current state of ridesharing, methods of promoting the adoption of ridesharing as a mode-share, and research that can further develop and enhance existing ridesharing.

Journal Publications:

"A Pickup and Delivery Problem for Ridesharing Considering Congestion," Transportation Letters: the International Journal of Transportation Research, 8, 259-269, 2016 (X. Wang, M. M. Dessouky, and F. Ordonez)

"A Traffic Assignment Model for a Ridesharing Transportation Market," Journal of Advanced Transportation, 49, 793-816, 2015 (H. Xu, F. Ordonez, and M. M. Dessouky)

"Complementarity Models for Traffic Equilibrium with Ridesharing," Transportation Research Part B: Methodological, 81, 161-182, 2015 (H. Xu, J.-S. Pang, F. Ordonez, and M. M. Dessouky)

"Online Cost-Sharing Mechanism Design for Demand-Responsive Transportation Systems," IEEE Transactions on Intelligent Transportation Systems, 16, 692-707, 2015 (M. Furuhata, K. Daniel, S. Koenig, F. Ordonez, M. M. Dessouky, M. Brunet, L. Cohen, and X. Wang)

"Ridesharing: the State-of-the-art and Future Directions," Transportation Research Part B: Methodological, 57, 28-46, 2013 (M. Furuhata, M. M. Dessouky, F. Ordonez, M. Brunet, X. Wang, S. Koenig)

Conference Proceedings Publications

“Characterizing Online Cost-Sharing Mechanisms for Demand Responsive Transport Systems,” 2014 Autonomous Agents and Multiagents Systems (AAMAS) Conference, Extended Abstract, Paris, France (M. Furuhata, L. Cohen, S. Koenig, M. M. Dessouky, and F. Ordonez)

“Online Cost-Sharing Mechanism Design, for Demand-Responsive Transport,” 2014 AAMAS Workshop on Agents in Traffic and Transportation, Paris, France (M. Furuhata, K. Daniel, S. Koenig, F. Ordonez, M. M. Dessouky, M. Brunet, L. Cohen, and X. Wang)

“Research, Practice, and Future Directions of Dynamic Ridesharing,” Conference Proceedings on Advanced Systems for Public Transport (CASPT 12), Santiago, Chile, 2012 (M. Furuhata, F. Ordonez, M. M. Dessouky, S. Koenig, and X. Wang)