Speed Trajectory Optimization for a Heavy-Duty Truck Traversing Multiple Signalized Intersections: A Dynamic Programming Study

Manuel Rodriguez, H. Fathy
{"title":"Speed Trajectory Optimization for a Heavy-Duty Truck Traversing Multiple Signalized Intersections: A Dynamic Programming Study","authors":"Manuel Rodriguez, H. Fathy","doi":"10.1109/CCTA.2018.8511446","DOIUrl":null,"url":null,"abstract":"This paper explores the fuel savings that can be achieved by optimizing the speed trajectory of a heavy-duty truck traversing a sequence of intersections, under the assumptions that the behavior of the leading traffic and the timing of the traffic lights is known. Specifically, we look at the impact of corridor topology (i.e. green cycle lengths, phase offsets) on the expected fuel savings of the optimized trajectories. This is an important area of research because vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technology has the potential to allow autonomous vehicles to reduce fuel consumption, especially in urban and sub-urban driving scenarios. The literature tackles the problem of arterial corridor trajectory optimization, and shows the potential fuel saving benefits. However, previous research focuses primarily on passenger vehicles, and often limits its findings to specific case studies. The main contribution of this paper is to offer an estimate of the fuel saving potential - for heavy-duty trucks and under different corridor characteristics - of optimizing trajectories in an urban arterial with V2V and V21 capabilities.","PeriodicalId":358360,"journal":{"name":"2018 IEEE Conference on Control Technology and Applications (CCTA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Conference on Control Technology and Applications (CCTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCTA.2018.8511446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

This paper explores the fuel savings that can be achieved by optimizing the speed trajectory of a heavy-duty truck traversing a sequence of intersections, under the assumptions that the behavior of the leading traffic and the timing of the traffic lights is known. Specifically, we look at the impact of corridor topology (i.e. green cycle lengths, phase offsets) on the expected fuel savings of the optimized trajectories. This is an important area of research because vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technology has the potential to allow autonomous vehicles to reduce fuel consumption, especially in urban and sub-urban driving scenarios. The literature tackles the problem of arterial corridor trajectory optimization, and shows the potential fuel saving benefits. However, previous research focuses primarily on passenger vehicles, and often limits its findings to specific case studies. The main contribution of this paper is to offer an estimate of the fuel saving potential - for heavy-duty trucks and under different corridor characteristics - of optimizing trajectories in an urban arterial with V2V and V21 capabilities.
重载卡车穿越多信号交叉口的速度轨迹优化:动态规划研究
本文探讨了通过优化重型卡车穿越一系列十字路口的速度轨迹可以实现的燃油节约,假设领先交通的行为和交通灯的时间是已知的。具体来说,我们研究了走廊拓扑(即绿色周期长度、相位偏移)对优化轨迹的预期燃油节约的影响。这是一个重要的研究领域,因为车对车(V2V)和车对基础设施(V2I)技术有可能使自动驾驶汽车降低燃料消耗,特别是在城市和郊区驾驶场景中。本文解决了动脉通道轨迹优化问题,并展示了潜在的节油效益。然而,以前的研究主要集中在乘用车上,并且往往将其研究结果限制在具体的案例研究中。本文的主要贡献是提供了在具有V2V和V21能力的城市主干道中优化轨道的节油潜力的估计-对于重型卡车和在不同走廊特征下。
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信