Scaling Law of Urban Ride Sharing

Sharing rides could drastically improve the efficiency of car and taxi transportation. Unleashing such potential, however, requires understanding how urban parameters affect the fraction of individual trips that can be shared, a quantity that we call shareability. Using data on millions of taxi trips in New York City, San Francisco, Singapore, and Vienna, we compute the shareability curves for each city, and find that a natural rescaling collapses them onto a single, universal curve. We explain this scaling law theoretically with a simple model that predicts the potential for ride sharing in any city, using a few basic urban quantities and no adjustable parameters. Accurate extrapolations of this type will help planners, transportation companies, and society at large to shape a sustainable path for urban growth.

[1]  Rachel Botsman,et al.  What's Mine Is Yours: The Rise of Collaborative Consumption , 2010 .

[2]  Everett M. Rogers,et al.  Innovation Diffusion As a Spatial Process , 1967 .

[3]  Hunter N. B. Moseley,et al.  Limits of Predictability in Human Mobility , 2010 .

[4]  J. Dall,et al.  Random geometric graphs. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[5]  Chaoming Song,et al.  Modelling the scaling properties of human mobility , 2010, 1010.0436.

[6]  Nathan Eagle,et al.  Limits of Predictability in Commuting Flows in the Absence of Data for Calibration , 2014, Scientific Reports.

[7]  Nicholas A. John The Social Logics of Sharing , 2013 .

[8]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[9]  T. Geisel,et al.  The scaling laws of human travel , 2006, Nature.

[10]  R. Prud’homme,et al.  Size, Sprawl, Speed and the Efficiency of Cities , 1999 .

[11]  G. Lepage A new algorithm for adaptive multidimensional integration , 1978 .

[12]  Paolo Santi,et al.  Supporting Information for Quantifying the Benefits of Vehicle Pooling with Shareability Networks Data Set and Pre-processing , 2022 .

[13]  William J. Mitchell,et al.  Reinventing the Automobile: Personal Urban Mobility for the 21st Century , 2010 .

[14]  Clarice Maraschin,et al.  Growth dynamic of retail locations: a methodological approach using a logistic model , 2013 .

[15]  L. Mumford,et al.  The City in History. Its Origins, Its Transformations, and Its Prospects , 1961 .

[16]  Paolo Santi,et al.  Supersampling and Network Reconstruction of Urban Mobility , 2015, PloS one.

[17]  Torsten Hägerstrand,et al.  Innovation Diffusion As a Spatial Process , 1967 .

[18]  Pietro Liò,et al.  Collective Human Mobility Pattern from Taxi Trips in Urban Area , 2012, PloS one.

[19]  K. Small,et al.  The Economics Of Traffic Congestion , 1993 .