Quantifying the external costs of autonomous on-demand ride pooling services

IF 2.4 Q3 TRANSPORTATION
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引用次数: 0

Abstract

Mobility On Demand (MOD) services, such as ride-pooling, provide convenient and cost-effective transportation options. While previous studies focused on operational costs and service quality, we take a broader perspective by examining the external costs associated with autonomous ride-pooling services. Incorporating external costs into the design and evaluation of MOD services enables a comprehensive understanding of their impact on the entire urban population, informing effective regulations and incentives. We present an approach for calculating space-varying external costs, accounting for factors like air pollution, climate impact, noise and accidents. These costs are integrated into FleetPy, an agent-based simulation tool for ridesharing analysis and optimization. A case study in Munich uncovers the tradeoffs between external costs, internal costs, and service quality. Our findings suggest that mid-sized vehicles with a three-person capacity strike a balance between energy efficiency and transport capacity. By applying our approach, external costs can be reduced by up to 37%.
量化自主按需拼车服务的外部成本
按需移动(MOD)服务,如拼车,提供了便捷且经济高效的交通选择。以往的研究侧重于运营成本和服务质量,而我们则从更广阔的视角出发,研究了与自主拼车服务相关的外部成本。将外部成本纳入 MOD 服务的设计和评估中,可以全面了解其对整个城市人口的影响,从而制定有效的法规和激励措施。我们提出了一种计算空间变化外部成本的方法,其中考虑了空气污染、气候影响、噪音和事故等因素。这些成本被整合到基于代理的模拟工具 FleetPy 中,用于共享出行的分析和优化。慕尼黑的一项案例研究揭示了外部成本、内部成本和服务质量之间的权衡。我们的研究结果表明,可容纳三人的中型车辆可以在能源效率和运输能力之间取得平衡。采用我们的方法,外部成本最多可降低 37%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.00
自引率
12.00%
发文量
222
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