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Abstract

This paper presents a pilot study of taxi-pooling in Washington, D.C. to demonstrate its potential for city-wide vehicle mileage reduction with real-world taxi trip data. In the taxi-pooling problem, riders specify their origins, destinations, earliest departure times, and latest arrival times. Taking all requests into consideration, the system dispatcher determines which requests can be grouped and thus served by one taxi, without violating any user-specified time windows and taxi capacity. This paper first presents a mathematical programming model whose objective is to minimize the system-wide vehicle miles traveled. Then an efficient solution approach to this problem is proposed. Results from analyzing the case of Washington, D.C. show that the total vehicle miles traveled can be reduced by 18% if the average buffer time in their travel schedule is 25% of their direct travel time.

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References

New Yorkers Try a Startling Idea: Sharing Yellow Cabs. New York Times. https://www.nytimes.com/2017/06/06/nyregion/new-york-yellow-taxis-ride-sharing.html. Accessed July 15, 2017.

Multiple Hiring . NSW Taxi Council, Australia. https://www.nswtaxi.org.au/passengers/multiple-hiring. Accessed July 15, 2017.

Taxi Fares. Taxi Services Commission, State Government of Victoria, Australia. http://taxi.vic.gov.au/passengers/taxi-passengers/taxi-fares. Accessed July 15, 2017.

Yan

Chen

C. Y.

C. C.

Solution Methods for the Taxi Pooling Problem. Transportation, Vol. 39, No. 3, 2012, pp. 723–748.

Santos

D. O.

Xavier

E. C.

Taxi and Ride Sharing: A Dynamic Dial-a-Ride Problem with Money as an Incentive. Expert Systems with Applications, Vol. 42, No. 19, 2015, pp. 6728–6737.

Agatz

Erera

Savelsbergh

Wang

Optimization for Dynamic Ride-sharing: A Review. European Journal of Operational Research, Vol. 223, No. 2, 2012, pp. 295–303.

Furuhata

Dessouky

Ordóñez

Brunet

M. E.

Wang

Koenig

Ridesharing: The State-of-the-art and Future Directions. Transportation Research Part B: Methodological, Vol. 57, 2013, pp. 28–46.

d’Orey

P. M.

Ferreira

Can Ride-Sharing Become Attractive? A Case Study of Taxi-Sharing Employing a Simulation Modelling Approach. IET Intelligent Transport Systems, Vol. 9, No. 2, 2014, pp. 210–220.

Santi

Resta

Szell

Sobolevsky

Strogatz

S. H.

Ratti

Quantifying the Benefits of Vehicle Pooling with Shareability Networks. Proceedings of the National Academy of Sciences, Vol. 111, No. 37, 2014, pp. 13290–13294.

10.

Qian

Zhang

Ukkusuri

S. V.

Yang

Optimal Assignment and Incentive Design in the Taxi Group Ride Problem. Transportation Research Part B: Methodological, Vol. 103, 2017, pp. 208–226.

11.

Zheng

Wolfson

Real-time City-scale Taxi Ridesharing. IEEE Transactions on Knowledge and Data Engineering, Vol. 27, No. 7, 2015, pp. 1782–1795.

12.

Hosni

Naoum-Sawaya

Artail

The Shared-taxi Problem: Formulation and Solution Methods. Transportation Research Part B: Methodological, Vol. 70, 2014, pp. 303–318.

13.

Jung

Jayakrishnan

Park

J. Y.

Dynamic Shared-Taxi Dispatch Algorithm with Hybrid-Simulated Annealing. Computer-Aided Civil and Infrastructure Engineering, Vol. 31, No. 4, 2016, pp. 275–291.

14.

Masoud

Jayakrishnan

A Decomposition Algorithm to Solve the Multi-Hop Peer-to-Peer Ride-matching Problem. Transportation Research Part B: Methodological, Vol. 99, 2017, pp. 1–29.

15.

New York City Taxi & Limousine Commission. 2016 TLC Fact Book. www.nyc.gov/html/tlc/downloads/pdf/2016_tlc_factbook.pdf. Accessed October 15, 2017.

Potential of Taxi-Pooling to Reduce Vehicle Miles Traveled in Washington,D.C.

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