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A Weighted Travel Time Index Based on Data From E-Hailing Trips: An Application for São Paulo, Brazil

Author

Listed:
  • Renato Schwambach Vieira
  • Eduardo Amaral Haddad

Abstract

In this paper, we combine data from Uber Movement and from a representative household travel survey to constructs a weighted travel time index for the Metropolitan Region of São Paulo. The index is calculated based on the average travel time of Uber trips taken between each pair of traffic zone and in each hour between January 1st, 2016 to December 31, 2018. The index is weighted based on the travel patterns reported in a representative household travel survey, thus the results reflect average congestion levels faced by individuals in the city. We show that the index has a strong correlation with traditional measures of congestion, however, it has a broader coverage of the road network. Finally, we run two analyses using the index: 1) we evaluate the trends of traffic congestion between 2016 and 2018, showing a significant decline in average time spent in traffic; 2) We analyze the effect of different events on traffic congestion in the city, including holidays, public transit strikes, road shutdowns, rain and Major sport events.

Suggested Citation

  • Renato Schwambach Vieira & Eduardo Amaral Haddad, 2020. "A Weighted Travel Time Index Based on Data From E-Hailing Trips: An Application for São Paulo, Brazil," Working Papers, Department of Economics 2020_15, University of São Paulo (FEA-USP).
    • Handle: RePEc:spa:wpaper:2020wpecon15
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    References listed on IDEAS

    as
    1. Haddad, Eduardo & Vieira, Renato, 2015. "Mobilidade, Acessibilidade e Produtividade: Nota sobre a Valoração Econômica do Tempo de Viagem na Região Metropolitana de São Paulo," TD NEREUS 8-2015, Núcleo de Economia Regional e Urbana da Universidade de São Paulo (NEREUS).
    2. Matthias Sweet & Mengke Chen, 2011. "Does regional travel time unreliability influence mode choice?," Transportation, Springer, vol. 38(4), pages 625-642, July.
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    More about this item

    Keywords

    Traffic Congestion; Travel Time Index; E-Hailing Data;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • D62 - Microeconomics - - Welfare Economics - - - Externalities
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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