Yiran Zhao, Shuochao Yao, Huajie Shao, T. Abdelzaher
{"title":"CoDrive:城市信号交叉口车辆协同驾驶方案","authors":"Yiran Zhao, Shuochao Yao, Huajie Shao, T. Abdelzaher","doi":"10.1109/ICCPS.2018.00037","DOIUrl":null,"url":null,"abstract":"This paper presents the design and evaluation of CoDrive, a cooperative speed advice system aiming at vehicular fuel savings by reconciling speeds of different vehicles with the timing of signalized intersections. Existing systems for speed coordination and platoon management primarily focus on safety, stability, and security issues. In the authors' own prior work, speed optimizations are discussed for minimizing fuel consumption by exploiting signalized intersection timing. In this paper, we recognize that vehicles whose paths diverge after the next intersection have different fuel-optimal speeds. Since slower vehicles will block faster ones from meeting their optimal speed in heavy traffic or on single-lane roads, we develop an algorithm for speed re-negotiation that arrives at a compromise speed for all vehicles involved. The resulting cooperative speed advice scheme minimizes the total fuel consumption of the involved vehicles, leading to a global optimum. An accounting scheme offers incentives that compensate for resulting inequity in savings distribution across individual vehicles. For evaluation, we use the SUMO simulator. We show that our cooperative scheme saves up to 38.2% in fuel over the baseline where no speed advice is provided, and saves up to 7.9% over prior work GreenDrive.","PeriodicalId":199062,"journal":{"name":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"CoDrive: Cooperative Driving Scheme for Vehicles in Urban Signalized Intersections\",\"authors\":\"Yiran Zhao, Shuochao Yao, Huajie Shao, T. Abdelzaher\",\"doi\":\"10.1109/ICCPS.2018.00037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the design and evaluation of CoDrive, a cooperative speed advice system aiming at vehicular fuel savings by reconciling speeds of different vehicles with the timing of signalized intersections. Existing systems for speed coordination and platoon management primarily focus on safety, stability, and security issues. In the authors' own prior work, speed optimizations are discussed for minimizing fuel consumption by exploiting signalized intersection timing. In this paper, we recognize that vehicles whose paths diverge after the next intersection have different fuel-optimal speeds. Since slower vehicles will block faster ones from meeting their optimal speed in heavy traffic or on single-lane roads, we develop an algorithm for speed re-negotiation that arrives at a compromise speed for all vehicles involved. The resulting cooperative speed advice scheme minimizes the total fuel consumption of the involved vehicles, leading to a global optimum. An accounting scheme offers incentives that compensate for resulting inequity in savings distribution across individual vehicles. For evaluation, we use the SUMO simulator. We show that our cooperative scheme saves up to 38.2% in fuel over the baseline where no speed advice is provided, and saves up to 7.9% over prior work GreenDrive.\",\"PeriodicalId\":199062,\"journal\":{\"name\":\"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPS.2018.00037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPS.2018.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
CoDrive: Cooperative Driving Scheme for Vehicles in Urban Signalized Intersections
This paper presents the design and evaluation of CoDrive, a cooperative speed advice system aiming at vehicular fuel savings by reconciling speeds of different vehicles with the timing of signalized intersections. Existing systems for speed coordination and platoon management primarily focus on safety, stability, and security issues. In the authors' own prior work, speed optimizations are discussed for minimizing fuel consumption by exploiting signalized intersection timing. In this paper, we recognize that vehicles whose paths diverge after the next intersection have different fuel-optimal speeds. Since slower vehicles will block faster ones from meeting their optimal speed in heavy traffic or on single-lane roads, we develop an algorithm for speed re-negotiation that arrives at a compromise speed for all vehicles involved. The resulting cooperative speed advice scheme minimizes the total fuel consumption of the involved vehicles, leading to a global optimum. An accounting scheme offers incentives that compensate for resulting inequity in savings distribution across individual vehicles. For evaluation, we use the SUMO simulator. We show that our cooperative scheme saves up to 38.2% in fuel over the baseline where no speed advice is provided, and saves up to 7.9% over prior work GreenDrive.