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Hyperdemand: A static traffic model with backward-bending demand curves

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  • Lehe, Lewis J.
  • Pandey, Ayush

Abstract

Static traffic models, in the tradition of Walters (1961), typically feature a ‘‘demand curve’’ giving the vehicle flow demanded for each unit travel time (inverse speed). Traditionally, the demand curve declines because people want to drive more as travel times fall. This paper proposes that the vehicle flow demanded can, instead, plausibly rise with unit travel time (a phenomenon we call ‘‘hyperdemand’’), if congestion somehow induces some people to switch from high-to low-occupancy modes. To illustrate, we present a model of travel in an isotropic downtown where people choose among not traveling, a low-occupancy mode called ‘‘Alone’’ and a high-occupancy mode called ‘‘Pool.’’ Pool trips detour to pick up and drop off passengers en route, so congestion delays them more than Alone trips. Consequently, multiple equilibria can arise even in ‘‘light congestion,’’ and small toll increases can have dramatic impacts by eliminating equilibria.

Suggested Citation

  • Lehe, Lewis J. & Pandey, Ayush, 2020. "Hyperdemand: A static traffic model with backward-bending demand curves," Economics of Transportation, Elsevier, vol. 24(C).
  • Handle: RePEc:eee:ecotra:v:24:y:2020:i:c:s2212012220301180
    DOI: 10.1016/j.ecotra.2020.100182
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    References listed on IDEAS

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    Cited by:

    1. Liu, Hao & Devunuri, Saipraneeth & Lehe, Lewis & Gayah, Vikash V., 2023. "Scale effects in ridesplitting: A case study of the City of Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).

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