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Mitigating traffic congestion induced by transportation network companies: A policy analysis

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  • Zhang, Kenan
  • Nie, Yu (Marco)

Abstract

This paper analyzes and evaluates several policies aiming to mitigate the congestion effect a Transportation Network Company (TNC) brings to bear on an idealized city that contains a dense central core surrounded by a larger periphery. The TNC offers both solo and pooling e-hail services to the users of public transport. We develop a spatial market equilibrium model over two building blocks: an aggregate congestion model that describes the traffic impact of TNC operations on all travelers in the city, including private motorists, and a matching model that estimates the TNC’s level of service based on the interactions between riders and TNC drivers. Based on the equilibrium model, we formulate and solve the optimal pricing problem, in which the TNC seeks to optimize its profit or social welfare subject to regulatory costs and/or constraints. Three congestion mitigation policies are implemented in this study: (i) a trip-based policy that charges a congestion fee on each solo trip starting or ending in the city center; (ii) a cordon-based policy that charges TNC vehicles entering the city center with zero or one passenger; and (iii) a cruising cap policy that requires the TNC to maintain the fleet utilization ratio in the city center above a threshold. Based on a case study of Chicago, we find TNC operations may have a significant congestion effect. Failing to anticipate this effect in the pricing problem leads to sub-optimal decisions that worsen traffic congestion and hurt the TNC’s profitability. Of the three policies, the trip-based policy delivers the best performance. It reduces traffic congestion modestly, keeps the TNC’s level of service almost intact, and improves overall social welfare substantially. The cruising cap policy benefits private motorists, thanks to the extra congestion relief it brings about. However, because other stakeholders together suffer a much greater loss, its net impact on social welfare is negative. Paradoxically, the policy could worsen the very traffic conditions in the city center that it is designed to improve.

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  • Zhang, Kenan & Nie, Yu (Marco), 2022. "Mitigating traffic congestion induced by transportation network companies: A policy analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 96-118.
    • Handle: RePEc:eee:transa:v:159:y:2022:i:c:p:96-118
    DOI: 10.1016/j.tra.2022.01.017
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    2. Zhang, Kenan & Mittal, Archak & Djavadian, Shadi & Twumasi-Boakye, Richard & Nie, Yu (Marco), 2023. "RIde-hail vehicle routing (RIVER) as a congestion game," Transportation Research Part B: Methodological, Elsevier, vol. 177(C).
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    4. Shetty, Akhil & Li, Sen & Tavafoghi, Hamidreza & Qin, Junjie & Poolla, Kameshwar & Varaiya, Pravin, 2022. "An analysis of labor regulations for transportation network companies," Economics of Transportation, Elsevier, vol. 32(C).
    5. Yuan Liang & Bingjie Yu & Xiaojian Zhang & Yi Lu & Linchuan Yang, 2022. "The Short-term Impact of Congestion Taxes on Ridesourcing Demand and Traffic Congestion: Evidence from Chicago," Papers 2207.01793, arXiv.org, revised Feb 2023.

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