基于多源数据的按需共享自主交通与公共交通的生态友好型整合

IF 14.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xinghua Liu , Xuan Shao , Ye Li
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引用次数: 0

摘要

按需共享自主交通(SAMoD)被认为是未来城市最高效的交通方式之一,因此受到广泛关注。然而,它可能会吸引公共交通(PT)系统的乘客,导致交通拥堵和环境污染等负面外部效应。只有将 SAMoD 与公共交通系统无缝整合,充分利用 SAMoD 的灵活性和公共交通的大规模运输能力,才能实现更大的社会效益。因此,本研究考虑了 SAMoD 与公共交通(如地铁、快速公交和公交车)之间各种复杂的潜在互动,包括首末站服务和替代方案,旨在研究 SAMoD-PT 集成系统中网络建设和客流分配的优化框架,以实现可持续性和效率之间的最佳平衡。具体而言,我们首先采用分层加权 K-means 聚类算法对多来源出行需求进行聚类,并使用 Voronoi 分区算法进行区域划分。其次,使用贪婪三角算法确定多模式交通网络中的潜在连接。随后,采用生命周期评估和连续逼近算法分别量化环境成本(包括温室气体排放和能源消耗)以及乘客和运营商成本。最后,我们构建了一个多目标优化模型,并使用加权求和法进行求解,得到了帕累托前沿,以平衡 SAMoD-PT 集成系统的可持续性和效率。结果表明,优化后的 SAMoD-PT 综合系统能显著降低社会成本,缓解模式间竞争效应,并确保公共交通的核心作用。这凸显了 SAMoD 与 PT 之间合作的巨大潜力。这些发现为发展中国家未来如何规划更高效、更环保的多模式城市交通系统提供了宝贵的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Eco-friendly integration of shared autonomous mobility on demand and public transit based on multi-source data
Shared Autonomous Mobility on Demand (SAMoD) is considered one of the most efficient modes of transportation for future cities and has thus gained significant attention. However, it may attract the ridership of public transportation (PT) systems, leading to negative externalities such as traffic congestion and environmental pollution. Greater social benefits can only be realized by seamlessly integrating SAMoD with PT systems, leveraging SAMoD’s flexibility and PT’s large-scale transport capacity. Therefore, this study considers the various complex potential interactions between SAMoD and PT (such as subways, BRT, and buses), including first and last-mile services and alternatives, and aims to investigate an optimization framework for network construction and passenger flow allocation in a SAMoD-PT integrated system to achieve an optimal balance between sustainability and efficiency. Specifically, we first applied a hierarchical weighted K-means clustering algorithm to cluster multi-source travel demands and used the Voronoi partition algorithm for regional division. Secondly, potential connections in the multi-modal transportation network were determined using a greedy triangulation algorithm. Subsequently, life cycle assessment and continuous approximation algorithms were employed to quantify environmental costs (including greenhouse gas emissions and energy consumption) as well as passenger and operator costs, respectively. Finally, we constructed a multi-objective optimization model and solved it using the weighted sum method, obtaining the Pareto frontier to balance sustainability and efficiency in the SAMoD-PT integrated system. The results show that the optimized SAMoD-PT integrated system can significantly reduce social costs, mitigate inter-modal competition effects, and ensure the central role of PT. This highlights the great potential of cooperation between SAMoD and PT. These findings provide valuable insights for developing countries on how to plan more efficient and environmentally friendly multi-modal urban transportation systems in the future.
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来源期刊
Information Fusion
Information Fusion 工程技术-计算机:理论方法
CiteScore
33.20
自引率
4.30%
发文量
161
审稿时长
7.9 months
期刊介绍: Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.
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