Mitigating traffic congestion induced by transportation network companies: A policy analysis
Mitigating traffic congestion induced by transportation network companies: A policy analysis
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缓解交通网络公司造成的交通拥堵：政策分析
DOI：
10.1016/j.tra.2022.01.017
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Nie, Yu
中科院分区：
文献类型：
--
作者：
Zhang, Kenan;Nie, Yu
本文分析和评估了几项旨在缓解交通网络公司（TNC）给一个理想化城市带来的拥堵效应的政策，该城市包含一个密集的中心核心，周围环绕着一个更大的外围。TNC为公共交通用户提供单独和联合的电子叫车服务。我们在两个构建块上开发了一个空间市场均衡模型：一个是总体拥堵模型，描述跨国公司运营对城市中所有旅客（包括私人驾车者）的交通影响；另一个是匹配模型，根据乘客和跨国公司司机之间的互动来估计跨国公司的服务水平。基于均衡模型，我们制定并解决了最优定价问题，其中跨国公司寻求在监管成本和/或约束下优化其利润或社会福利。本研究实施了三种拥堵缓解政策：(i)基于出行的政策，对每一次在市中心开始或结束的独自出行收取拥堵费；（ii）以警戒线为基础的政策，对进入市中心的跨国公司车辆收取零或一名乘客的费用；（iii）巡航上限政策，要求TNC将城市中心的车队利用率保持在阈值以上。基于芝加哥的案例研究，我们发现跨国公司的运营可能会产生显著的拥堵效应。在定价问题上未能预见到这种影响会导致次优决策，从而加剧交通拥堵，损害跨国公司的盈利能力。在这三种策略中，基于行程的策略提供了最好的性能。它适度地减少了交通拥堵，使跨国公司的服务水平几乎保持不变，并大大提高了整体社会福利。巡航上限政策有利于私人驾车者，因为它带来了额外的拥堵缓解。然而，由于其他利益相关者共同遭受更大的损失，其对社会福利的净影响为负。矛盾的是，这项政策可能会恶化市中心的交通状况，而这正是它旨在改善的。
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.