Yu Han , Xiaolei Ma , Bin Yu , Qianwen Li , Ronghui Zhang , Xiaopeng Li
{"title":"模块化总线途中对接的二维轨迹规划","authors":"Yu Han , Xiaolei Ma , Bin Yu , Qianwen Li , Ronghui Zhang , Xiaopeng Li","doi":"10.1016/j.tre.2024.103769","DOIUrl":null,"url":null,"abstract":"<div><p>Modular buses (MBs), which can physically dock and separate, offer enhanced flexibility and potential cost savings in urban transportation. Despite advances in scheduling, trajectory planning for the docking process of MBs is less developed. This paper addresses the two-dimensional trajectory planning for MB docking. We introduce a hierarchical docking planning model based on Nonlinear Model Predictive Control (NMPC). The upper-level model optimizes docking time and speed, while the lower-level dynamically updates trajectories. Our models integrate Frenet and Cartesian coordinates with a precise obstacle avoidance model to ensure safety and smoothness under diverse traffic conditions. We employ segmented Lagrange interpolation for discretizing the continuous NMPC model, enhancing planning accuracy with fewer points and improving solving efficiency. Additionally, a multi-task network adaptively adjusts discretization orders based on environmental data. Extensive testing demonstrates our method’s superior accuracy and efficiency in real-time performance, offering marked improvements in safety and operational smoothness compared to existing approaches.</p></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Planning two-dimensional trajectories for modular bus enroute docking\",\"authors\":\"Yu Han , Xiaolei Ma , Bin Yu , Qianwen Li , Ronghui Zhang , Xiaopeng Li\",\"doi\":\"10.1016/j.tre.2024.103769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Modular buses (MBs), which can physically dock and separate, offer enhanced flexibility and potential cost savings in urban transportation. Despite advances in scheduling, trajectory planning for the docking process of MBs is less developed. This paper addresses the two-dimensional trajectory planning for MB docking. We introduce a hierarchical docking planning model based on Nonlinear Model Predictive Control (NMPC). The upper-level model optimizes docking time and speed, while the lower-level dynamically updates trajectories. Our models integrate Frenet and Cartesian coordinates with a precise obstacle avoidance model to ensure safety and smoothness under diverse traffic conditions. We employ segmented Lagrange interpolation for discretizing the continuous NMPC model, enhancing planning accuracy with fewer points and improving solving efficiency. Additionally, a multi-task network adaptively adjusts discretization orders based on environmental data. Extensive testing demonstrates our method’s superior accuracy and efficiency in real-time performance, offering marked improvements in safety and operational smoothness compared to existing approaches.</p></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part E-Logistics and Transportation Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554524003600\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554524003600","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Planning two-dimensional trajectories for modular bus enroute docking
Modular buses (MBs), which can physically dock and separate, offer enhanced flexibility and potential cost savings in urban transportation. Despite advances in scheduling, trajectory planning for the docking process of MBs is less developed. This paper addresses the two-dimensional trajectory planning for MB docking. We introduce a hierarchical docking planning model based on Nonlinear Model Predictive Control (NMPC). The upper-level model optimizes docking time and speed, while the lower-level dynamically updates trajectories. Our models integrate Frenet and Cartesian coordinates with a precise obstacle avoidance model to ensure safety and smoothness under diverse traffic conditions. We employ segmented Lagrange interpolation for discretizing the continuous NMPC model, enhancing planning accuracy with fewer points and improving solving efficiency. Additionally, a multi-task network adaptively adjusts discretization orders based on environmental data. Extensive testing demonstrates our method’s superior accuracy and efficiency in real-time performance, offering marked improvements in safety and operational smoothness compared to existing approaches.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.