交通运输系统工程与信息

交通运输系统工程与信息 ›› 2025, Vol. 25 ›› Issue (1): 122-132.DOI: 10.16097/j.cnki.1009-6744.2025.01.013

• 系统工程理论与方法 • 上一篇    下一篇

考虑运能利用和碳排放的绿色城轨开行方案研究

杨雯雯1a,2，孟学雷*1a，高如虎1a，林立1b   

  1. 1. 兰州交通大学，a.交通运输学院，b.机电工程学院，机械工程博士后流动站，兰州730070；2. 兰州石化职业技术大学，国际商务学院，兰州730060
  • 收稿日期:2024-10-14 修回日期:2024-12-02 接受日期:2024-12-11 出版日期:2025-02-25 发布日期:2025-02-21
  • 作者简介:杨雯雯(1993—)，女，甘肃平凉人，博士生。
  • 基金资助:
    甘肃省科技计划(24JRRA865)；国家自然科学基金(72361020)。

Train Operation Plan of Green Urban Rail Transit Considering Transportation Capacity Utilization and Carbon Emissions

YANG Wenwen1a,2, MENG Xuelei*1a, GAO Ruhu1a, LIN Li1b   

  1. 1a. School of Traffic and Transportation, 1b. Postdoctoral Station of Mechanical Engineering, School of Mechanical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China; 2. School of International Business, Lanzhou Petrochemical University of Vocational Technology, Lanzhou 730060, China
  • Received:2024-10-14 Revised:2024-12-02 Accepted:2024-12-11 Online:2025-02-25 Published:2025-02-21
  • Supported by:
    Gansu Provincial Science and Technology Program Funding (24JRRA865)；National Natural Science Foundation of China (72361020)。

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摘要： 随着“双碳”目标上升为国家战略，构建绿色交通体系势在必行。立足于绿色交通“提效降碳”的核心内涵，本文提出一种考虑资源、环境、乘客和企业四方效益，基于大小交路多编组模式的城市轨道交通列车开行方案编制方法。为研究不同交路对客流分布的影响，根据乘客出行特征划分客流，进而分析不同客流的出行成本，建立以列车运输资源利用率最大，列车运行中碳排放量最小，企业运营成本和乘客出行时间成本最低为优化目标，以线路通过能力、发车频率和运用车辆数为约束的多目标优化模型。提出一种改进的麻雀搜索算法用于模型求解，并与单一交路、单一编组方案进行对比分析，同时将其求解结果与传统的麻雀搜索算法及粒子群算法进行比较。结果表明：与单一交路和单一编组的列车开行方案相比，多交路和多编组的方案在运能利用、碳排放、企业运营成本及乘客出行时间成本方面表现更优；此外，改进后的麻雀搜索算法在求解效率和结果质量上也明显优于传统算法。因此，本文提出的方法不仅能够平衡企业和乘客的利益，还有效提高了资源利用率，减少了碳排放，为城轨系统的绿色化运营提供了决策支持。

关键词: 城市交通, 开行方案, 麻雀搜索算法, 绿色城轨, 输送能力利用率, 碳排放

Abstract: As the "dual carbon" goal of Carbon Peak and Carbon Neutrality rises to the national strategic level, the establishment of a green transportation system has become increasingly urgent. This paper proposes a train operation plan for urban rail transit that focuses on the core principle of "efficiency enhancement and carbon reduction" in green transportation. The operation plan is based on a multi-route, multi-type formation configuration, taking into account the benefits of resources, the environment, passengers, and enterprises. To investigate the impact of different routes on passenger flow distribution, passenger flows are classified based on their travel characteristics, and an analysis of the associated travel costs for each passenger group is conducted. A multi-objective optimization model is established with the objectives of maximizing train transportation resource utilization, minimizing carbon emissions during train operations, and reducing both the operational expenditures of enterprises and the time costs associated with passenger travel. The model is subject to various constraints such as line capacity, departure frequency, and the number of vehicles in operation. To solve the model, an improved Sparrow Search Algorithm (SSA) was proposed, with a comparative analysis conducted against a full-length route, single-type formation operation plan. Furthermore, the solution results were compared with those obtained from the traditional SSA and Particle Swarm Optimization (PSO) algorithms. The results demonstrate that the multi- route, multi-type formation operation plan performs better than full-length route, single-type formation plan in terms of capacity utilization, carbon emissions reduction, enterprise operational costs, and passenger travel time costs. Moreover, the improved SSA shows significant advantages over traditional algorithms in terms of solution efficiency and quality. Therefore, the method proposed effectively balances the interests of enterprises and passengers, and also enhances resource utilization and reduces carbon emissions, providing strong decision-making support for the green operation of urban rail transit systems.

Key words: urban traffic, train operation plan, sparrow search algorithm, green urban rail transit, transportation capacity utilization, carbon emissions

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