Abstract
Taxicab service plays a vital role in public transportation by offering passengers quick personalized destination service in a semi-private and secure manner. Taxicabs cruise the road network looking for a fare at designated taxi stands or alongside the streets. However, this service is often inefficient due to a low ratio of live miles (miles with a fare) to cruising miles (miles without a fare). The unpredictable nature of passengers and destinations make efficient systematic routing a challenge. With higher fuel costs and decreasing budgets, pressure mounts on taxicab drivers who directly derive their income from fares and spend anywhere from 35-60 percent of their time cruising the road network for these fares. Therefore, the goal of this paper is to reduce the number of cruising miles while increasing the number of live miles, thus increasing profitability, without systematic routing. This paper presents a simple yet practical method for reducing cruising miles by suggesting profitable locations to taxicab drivers. The concept uses the same principle that a taxicab driver uses: follow your experience. In our approach, historical data serves as experience and a derived Spatio-Temporal Profitability (STP) map guides cruising taxicabs. We claim that the STP map is useful in guiding for better profitability and validate this by showing a positive correlation between the cruising profitability score based on the STP map and the actual profitability of the taxicab drivers. Experiments using a large Shanghai taxi GPS data set demonstrate the effectiveness of the proposed method.
This work was partially supported by the National Science Foundation under Grant No. IIS-1017926.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Schaller Consulting: The New York City Taxicab Fact Book, Schaller Consulting, Brooklyn, NY (2006), http://www.schallerconsult.com/taxi/taxifb.pdf
Yamamoto, K., Uesugi, K., Watanabe, T.: Adaptive Routing of Cruising Taxis by Mutual Exchange of Pathways. Knowledge-Based Intelligent Information and Engineering Systems 5178, 559–566 (2008)
Li, Q., Zeng, Z., Bisheng, Y., Zhang, T.: Hierarchical route planning based on taxi GPS-trajectories. In: 17th International Conference on Geoinformatics, Fairfax, pp. 1–5 (2009)
Wang, H.: The Strategy of Utilizing Taxi Empty Cruise Time to Solve the Short Distance Trip Problem, Masters Thesis. The University of Melbourne (2009)
Cheng, S., Qu, X.: A service choice model for optimizing taxi service delivery. In: 12th International IEEE Conference on Intelligent Transportation Systems, ITSC 2009, St. Louis, pp. 1–6 (2009)
Phithakkitnukoon, S., Veloso, M., Bento, C., Biderman, A., Ratti, C.: Taxi-aware map: identifying and predicting vacant taxis in the city. In: de Ruyter, B., Wichert, R., Keyson, D.V., Markopoulos, P., Streitz, N., Divitini, M., Georgantas, N., Mana Gomez, A. (eds.) AmI 2010. LNCS, vol. 6439, pp. 86–95. Springer, Heidelberg (2010)
Hong-Cheng, G., Xin, Y., Qing, W.: Investigating the effect of travel time variability on drivers’ route choice decisions in Shanghai, China. Transportation Planning and Technology 33, 657–669 (2010)
Li, Y., Miller, M.A., Cassidy, M.J.: Improving Mobility Through Enhanced Transit Services: Transit Taxi Service for Areas with Low Passenger Demand Density. University of California, Berkeley (2009)
Cooper, J., Farrell, S., Simpson, P.: Identifying Demand and Optimal Location for Taxi Ranks in a Liberalized Market. Transportation Research Board 89th Annual Meeting (2010)
Sirisoma, R.M.N.T., Wong, S.C., Lam, W.H.K., Wang, D., Yan, H., Zhang, P.: Empirical evidence for taxi customer-search model. Transportation Research Board 88th Annual Meeting 163, 203–210 (2009)
Yang, H., Fung, C.S., Wong, K.I., Wong, S.C.: Nonlinear pricing of taxi services. Transportation Research Part A: Policy and Practice 44, 337–348 (2010)
Chintakayala, P., Maitra, B.: Modeling Generalized Cost of Travel and Its Application for Improvement of Taxies in Kolkata. Journal of Urban Planning and Development 136, 42–49 (2010)
Wikipedia, Shanghai — Wikipedia The Free Encyclopedia (2011), http://en.wikipedia.org/w/index.php?title=Shanghai&oldid=412823222 (accessed May 21, 2011)
TravelChinaGuide.com, Get Around Shanghai by Taxi, Shanghai Transportation (2011), http://www.travelchinaguide.com/cityguides/shanghai/transportation/taxi.htm (accessed February 9, 2011)
Shanghai Taxi Cab Rates and Companies, Kuber (2011), http://kuber.appspot.com/taxi/rate (accessed February 9, 2011)
Yuan, J., Zheng, Y., Zhang, C., Xie, W., Xie, X., Sun, G., Huang, Y.: T-drive: driving directions based on taxi trajectories. In: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2010, San Jose, pp. 99–108 (2010)
Ge, Y., Xiong, H., Tuzhilin, A., Xiao, K., Gruteser, M., Pazzani, M.: An energy-efficient mobile recommender system. In: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD 2010, Washington, DC, pp. 899–908 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Powell, J.W., Huang, Y., Bastani, F., Ji, M. (2011). Towards Reducing Taxicab Cruising Time Using Spatio-Temporal Profitability Maps. In: Pfoser, D., et al. Advances in Spatial and Temporal Databases. SSTD 2011. Lecture Notes in Computer Science, vol 6849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22922-0_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-22922-0_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22921-3
Online ISBN: 978-3-642-22922-0
eBook Packages: Computer ScienceComputer Science (R0)