Congestion Pricing for Efficiency and Equity: Theory and Applications to the San Francisco Bay Area

Chinmay Maheshwari, Kshitij Kulkarni, Druv Pai, Jiarui Yang, Manxi Wu +1 more
1/30/2024
cs.GTcs.CYcs.MA

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Abstract

Congestion pricing, while adopted by many cities to alleviate traffic congestion, raises concerns about widening socioeconomic disparities due to its disproportionate impact on low-income travelers. We address this concern by proposing a new class of congestion pricing schemes that not only minimize total travel time, but also incorporate an equity objective, reducing disparities in the relative change in travel costs across populations with different incomes, following the implementation of tolls. Our analysis builds on a congestion game model with heterogeneous traveler populations. We present four pricing schemes that account for practical considerations, such as the ability to charge differentiated tolls to various traveler populations and the option to toll all or only a subset of edges in the network. We evaluate our pricing schemes in the calibrated freeway network of the San Francisco Bay Area. We demonstrate that the proposed congestion pricing schemes improve both the total travel time and the equity objective compared to the current pricing scheme. Our results further show that pricing schemes charging differentiated prices to traveler populations with varying value-of-time lead to a more equitable distribution of travel costs compared to those that charge a homogeneous price to all.

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Cite this paper

@article{maheshwari2024congestion,
  title  = {Congestion Pricing for Efficiency and Equity: Theory and Applications to the San Francisco Bay Area},
  author = {Chinmay Maheshwari and Kshitij Kulkarni and Druv Pai and Jiarui Yang and Manxi Wu and Shankar Sastry},
  year   = {2024},
  eprint = {2401.16844},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.16844v2}
}

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