考虑动态需求的两阶段需求响应式公交调度优化模型

IF 2.3 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Intelligent Transport Systems Pub Date : 2023-12-22 DOI:10.1049/itr2.12473
Cui-Ying Song, He-Ling Wang, Lu Chen, Xue-Qin Niu
{"title":"考虑动态需求的两阶段需求响应式公交调度优化模型","authors":"Cui-Ying Song,&nbsp;He-Ling Wang,&nbsp;Lu Chen,&nbsp;Xue-Qin Niu","doi":"10.1049/itr2.12473","DOIUrl":null,"url":null,"abstract":"<p>Demand-responsive transit has gradually attracted attention in recent years for its flexibility, efficiency, and ability to meet the diverse travel demands of passengers. To improve the operational efficiency of demand-responsive transit (DRT) with dynamic demand, this study innovatively investigates the DRT scheduling problem from multiple perspectives, such as multi-vehicle, non-fixed stop, and dynamic demand, and constructs a two-phase DRT vehicle scheduling model. In the first phase, a static scheduling model is established with the objective of minimizing vehicle setup cost, operation cost, and CO<sub>2</sub> emission cost according to passenger travel satisfaction. In the second phase, a dynamic scheduling model is constructed with the objective of minimizing the increased vehicle operation cost in response to dynamic demand and the penalty cost of violating the time window and rejecting passengers. In addition, in the first static phase, an improved heuristic algorithm is used to obtain optimal routes based on passengers’ subscriptions, while in the second phase, an insertion algorithm is designed to solve the dynamic scheduling model based on the previous schedule. Finally, cases are applied to a realistic network in Chaoyang District, Beijing, China, to verify the effectiveness of the proposed scheduling model. The results demonstrate that dynamic scheduling can enable more passengers to be served with a slight increase in total vehicle operating costs. Besides, the introduction of the non-fixed stop service model can significantly reduce total travel time by up to 8.8% compared with the fixed stop service. The proposed models and solution algorithms in this study are practical for real-world applications.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12473","citationCount":"0","resultStr":"{\"title\":\"An optimized two-phase demand-responsive transit scheduling model considering dynamic demand\",\"authors\":\"Cui-Ying Song,&nbsp;He-Ling Wang,&nbsp;Lu Chen,&nbsp;Xue-Qin Niu\",\"doi\":\"10.1049/itr2.12473\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Demand-responsive transit has gradually attracted attention in recent years for its flexibility, efficiency, and ability to meet the diverse travel demands of passengers. To improve the operational efficiency of demand-responsive transit (DRT) with dynamic demand, this study innovatively investigates the DRT scheduling problem from multiple perspectives, such as multi-vehicle, non-fixed stop, and dynamic demand, and constructs a two-phase DRT vehicle scheduling model. In the first phase, a static scheduling model is established with the objective of minimizing vehicle setup cost, operation cost, and CO<sub>2</sub> emission cost according to passenger travel satisfaction. In the second phase, a dynamic scheduling model is constructed with the objective of minimizing the increased vehicle operation cost in response to dynamic demand and the penalty cost of violating the time window and rejecting passengers. In addition, in the first static phase, an improved heuristic algorithm is used to obtain optimal routes based on passengers’ subscriptions, while in the second phase, an insertion algorithm is designed to solve the dynamic scheduling model based on the previous schedule. Finally, cases are applied to a realistic network in Chaoyang District, Beijing, China, to verify the effectiveness of the proposed scheduling model. The results demonstrate that dynamic scheduling can enable more passengers to be served with a slight increase in total vehicle operating costs. Besides, the introduction of the non-fixed stop service model can significantly reduce total travel time by up to 8.8% compared with the fixed stop service. The proposed models and solution algorithms in this study are practical for real-world applications.</p>\",\"PeriodicalId\":50381,\"journal\":{\"name\":\"IET Intelligent Transport Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12473\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Intelligent Transport Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/itr2.12473\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Intelligent Transport Systems","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/itr2.12473","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

近年来,需求响应式公交因其灵活性、高效性和满足乘客多样化出行需求的能力而逐渐受到关注。为提高动态需求响应式公交(DRT)的运营效率,本研究创新性地从多车辆、非固定站点、动态需求等多个角度研究了动态需求响应式公交的调度问题,并构建了两阶段的动态需求响应式公交车辆调度模型。在第一阶段,建立静态调度模型,目标是根据乘客出行满意度使车辆设置成本、运营成本和二氧化碳排放成本最小化。在第二阶段,建立动态调度模型,目标是最大限度地降低因动态需求而增加的车辆运营成本以及违反时间窗口和拒载乘客的惩罚成本。此外,在第一静态阶段,使用改进的启发式算法,根据乘客的订购情况获得最佳路线;在第二阶段,设计了一种插入算法,根据先前的时间表求解动态调度模型。最后,将案例应用于中国北京市朝阳区的现实网络,以验证所提出的调度模型的有效性。结果表明,动态调度能在车辆总运营成本略有增加的情况下为更多乘客提供服务。此外,与固定停靠站服务相比,非固定停靠站服务模式的引入可大幅减少总运行时间,最多可减少 8.8%。本研究提出的模型和解决算法在实际应用中是切实可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An optimized two-phase demand-responsive transit scheduling model considering dynamic demand

Demand-responsive transit has gradually attracted attention in recent years for its flexibility, efficiency, and ability to meet the diverse travel demands of passengers. To improve the operational efficiency of demand-responsive transit (DRT) with dynamic demand, this study innovatively investigates the DRT scheduling problem from multiple perspectives, such as multi-vehicle, non-fixed stop, and dynamic demand, and constructs a two-phase DRT vehicle scheduling model. In the first phase, a static scheduling model is established with the objective of minimizing vehicle setup cost, operation cost, and CO2 emission cost according to passenger travel satisfaction. In the second phase, a dynamic scheduling model is constructed with the objective of minimizing the increased vehicle operation cost in response to dynamic demand and the penalty cost of violating the time window and rejecting passengers. In addition, in the first static phase, an improved heuristic algorithm is used to obtain optimal routes based on passengers’ subscriptions, while in the second phase, an insertion algorithm is designed to solve the dynamic scheduling model based on the previous schedule. Finally, cases are applied to a realistic network in Chaoyang District, Beijing, China, to verify the effectiveness of the proposed scheduling model. The results demonstrate that dynamic scheduling can enable more passengers to be served with a slight increase in total vehicle operating costs. Besides, the introduction of the non-fixed stop service model can significantly reduce total travel time by up to 8.8% compared with the fixed stop service. The proposed models and solution algorithms in this study are practical for real-world applications.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
期刊最新文献
Exploring changes in residents' daily activity patterns through sequence visualization analysis ADWNet: An improved detector based on YOLOv8 for application in adverse weather for autonomous driving Creep slope estimation for assessing adhesion in the wheel/rail contact Evaluation of large-scale cycling environment by using the trajectory data of dockless shared bicycles: A data-driven approach Driver distraction and fatigue detection in images using ME-YOLOv8 algorithm
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1