Urban transit decarbonization via stochastic programming and statistical inference under uncertainty

IF 7.3 1区工程技术 Q1 ENVIRONMENTAL STUDIES

Transportation Research Part D-transport and Environment Pub Date : 2025-03-22 DOI:10.1016/j.trd.2025.104711

Jing Wang, Majid Gholami Shirkoohi, Rubina Akter, Walter Mérida

{"title":"Urban transit decarbonization via stochastic programming and statistical inference under uncertainty","authors":"Jing Wang, Majid Gholami Shirkoohi, Rubina Akter, Walter Mérida","doi":"10.1016/j.trd.2025.104711","DOIUrl":null,"url":null,"abstract":"<div><div>Urban transit decarbonization is integral to achieving a net-zero public transportation systems. This work proposes an optimization model for bus fleet transition planning, involving purchases and allocation to routes, fueling and charging infrastructure, and financing. The model adopts stochastic programming to address decision-making under uncertainty and is formulated as a mixed-integer linear program. A confidence interval estimation method is derived to accommodate diverse decision values and non-uniform scenario probabilities, alongside an efficient scenario construction approach. A case study of the Metro Vancouver regional bus network is conducted to explore transition pathways for adopting battery electric and hydrogen fuel cell buses. Results indicate that shifting to a battery electric fleet is more cost-effective overall, while the hydrogen pathway demands smaller infrastructure investments. The competitiveness of hydrogen could significantly improve if the substantial potential for cost reductions is realized. A mixed fleet can integrate the advantages of both pathways.</div></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"142 ","pages":"Article 104711"},"PeriodicalIF":7.3000,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part D-transport and Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S136192092500121X","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}

引用次数: 0

Abstract

Urban transit decarbonization is integral to achieving a net-zero public transportation systems. This work proposes an optimization model for bus fleet transition planning, involving purchases and allocation to routes, fueling and charging infrastructure, and financing. The model adopts stochastic programming to address decision-making under uncertainty and is formulated as a mixed-integer linear program. A confidence interval estimation method is derived to accommodate diverse decision values and non-uniform scenario probabilities, alongside an efficient scenario construction approach. A case study of the Metro Vancouver regional bus network is conducted to explore transition pathways for adopting battery electric and hydrogen fuel cell buses. Results indicate that shifting to a battery electric fleet is more cost-effective overall, while the hydrogen pathway demands smaller infrastructure investments. The competitiveness of hydrogen could significantly improve if the substantial potential for cost reductions is realized. A mixed fleet can integrate the advantages of both pathways.

查看原文本刊更多论文

不确定条件下随机规划与统计推理的城市交通脱碳研究

城市交通脱碳是实现净零公共交通系统不可或缺的一部分。本文提出了公交车队过渡规划的优化模型，包括路线的购买和分配、加油和充电基础设施以及融资。该模型采用随机规划来解决不确定条件下的决策问题，并将其表述为一个混合整数线性规划。提出了一种适应不同决策值和非均匀情景概率的置信区间估计方法，以及一种高效的情景构建方法。以大温哥华地区公交网络为例，探讨采用纯电动公交车和氢燃料电池公交车的过渡途径。结果表明，转向电池电动车队总体上更具成本效益，而氢途径需要更少的基础设施投资。如果实现成本降低的巨大潜力，氢的竞争力将大大提高。混合车队可以整合这两种途径的优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Transportation Research Part D-transport and Environment 工程技术-运输科技

CiteScore

14.40

自引率

9.20%

发文量

314

审稿时长

39 days

期刊介绍： Transportation Research Part D: Transport and Environment focuses on original research exploring the environmental impacts of transportation, policy responses to these impacts, and their implications for transportation system design, planning, and management. The journal comprehensively covers the interaction between transportation and the environment, ranging from local effects on specific geographical areas to global implications such as natural resource depletion and atmospheric pollution. We welcome research papers across all transportation modes, including maritime, air, and land transportation, assessing their environmental impacts broadly. Papers addressing both mobile aspects and transportation infrastructure are considered. The journal prioritizes empirical findings and policy responses of regulatory, planning, technical, or fiscal nature. Articles are policy-driven, accessible, and applicable to readers from diverse disciplines, emphasizing relevance and practicality. We encourage interdisciplinary submissions and welcome contributions from economically developing and advanced countries alike, reflecting our international orientation.