{"title":"使用配备gps的探测车辆的流旅行时间可靠性","authors":"Sharmili Banik, B. A. Kumar, L. Vanajakshi","doi":"10.18520/cs/v123/i9/1107-1116","DOIUrl":null,"url":null,"abstract":"Travel time reliability (TTR) is an important measure to quantify the variation in travel times. Currently, there is no single reliability metric appropriate across all locations, that is easily understandable and can be used to compare across facilities. Moreover, reliability analysis of facilities from developing countries is limited due to the non-availability of extensive data required for such an analysis. The present study addresses these gaps. It identifies a reliable data source for such analysis of heterogeneous, lane-less traffic, compares existing reliability measures for the data, highlights the advantages and disadvantages, proposes a measure that may be more suitable for such traffic with high variability, and finally illustrates how reliability analysis under such conditions can be done with limited data sources such as GPS-fitted transit vehicles. Using such commonly available data for traffic stream reliability analysis is the ultimate aim of this study. For valida-tion, stream travel time from Wi-Fi scanners is used. The study analyses the performance of various reliability measures and identifies the most suitable ones. Following this, a reliability measure, i.e. capacity buffer index (CBI), is developed to identify the unreliable congested regimes or periods, keeping time taken to travel at capacity conditions as the benchmark. From the results, it has been observed that CBI is in agreement with the real-field conditions in 94% of the cases, whereas it is 75% buffer time index. Finally, the feasibility of using bus probes to measure stream TTR is checked. Results show that bus probes can be an indicator of stream reliability and the developed measure can effectively capture the relationship between stream and bus TTR.","PeriodicalId":11194,"journal":{"name":"Current Science","volume":"25 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Stream travel time reliability using GPS-equipped probe vehicles\",\"authors\":\"Sharmili Banik, B. A. Kumar, L. Vanajakshi\",\"doi\":\"10.18520/cs/v123/i9/1107-1116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Travel time reliability (TTR) is an important measure to quantify the variation in travel times. Currently, there is no single reliability metric appropriate across all locations, that is easily understandable and can be used to compare across facilities. Moreover, reliability analysis of facilities from developing countries is limited due to the non-availability of extensive data required for such an analysis. The present study addresses these gaps. It identifies a reliable data source for such analysis of heterogeneous, lane-less traffic, compares existing reliability measures for the data, highlights the advantages and disadvantages, proposes a measure that may be more suitable for such traffic with high variability, and finally illustrates how reliability analysis under such conditions can be done with limited data sources such as GPS-fitted transit vehicles. Using such commonly available data for traffic stream reliability analysis is the ultimate aim of this study. For valida-tion, stream travel time from Wi-Fi scanners is used. The study analyses the performance of various reliability measures and identifies the most suitable ones. Following this, a reliability measure, i.e. capacity buffer index (CBI), is developed to identify the unreliable congested regimes or periods, keeping time taken to travel at capacity conditions as the benchmark. From the results, it has been observed that CBI is in agreement with the real-field conditions in 94% of the cases, whereas it is 75% buffer time index. Finally, the feasibility of using bus probes to measure stream TTR is checked. Results show that bus probes can be an indicator of stream reliability and the developed measure can effectively capture the relationship between stream and bus TTR.\",\"PeriodicalId\":11194,\"journal\":{\"name\":\"Current Science\",\"volume\":\"25 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2022-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Science\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.18520/cs/v123/i9/1107-1116\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Science","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.18520/cs/v123/i9/1107-1116","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Stream travel time reliability using GPS-equipped probe vehicles
Travel time reliability (TTR) is an important measure to quantify the variation in travel times. Currently, there is no single reliability metric appropriate across all locations, that is easily understandable and can be used to compare across facilities. Moreover, reliability analysis of facilities from developing countries is limited due to the non-availability of extensive data required for such an analysis. The present study addresses these gaps. It identifies a reliable data source for such analysis of heterogeneous, lane-less traffic, compares existing reliability measures for the data, highlights the advantages and disadvantages, proposes a measure that may be more suitable for such traffic with high variability, and finally illustrates how reliability analysis under such conditions can be done with limited data sources such as GPS-fitted transit vehicles. Using such commonly available data for traffic stream reliability analysis is the ultimate aim of this study. For valida-tion, stream travel time from Wi-Fi scanners is used. The study analyses the performance of various reliability measures and identifies the most suitable ones. Following this, a reliability measure, i.e. capacity buffer index (CBI), is developed to identify the unreliable congested regimes or periods, keeping time taken to travel at capacity conditions as the benchmark. From the results, it has been observed that CBI is in agreement with the real-field conditions in 94% of the cases, whereas it is 75% buffer time index. Finally, the feasibility of using bus probes to measure stream TTR is checked. Results show that bus probes can be an indicator of stream reliability and the developed measure can effectively capture the relationship between stream and bus TTR.
期刊介绍:
Current Science, published every fortnight by the Association, in collaboration with the Indian Academy of Sciences, is the leading interdisciplinary science journal from India. It was started in 1932 by the then stalwarts of Indian science such as CV Raman, Birbal Sahni, Meghnad Saha, Martin Foster and S.S. Bhatnagar. In 2011, the journal completed one hundred volumes. The journal is intended as a medium for communication and discussion of important issues that concern science and scientific activities. Besides full length research articles and shorter research communications, the journal publishes review articles, scientific correspondence and commentaries, news and views, comments on recently published research papers, opinions on scientific activity, articles on universities, Indian laboratories and institutions, interviews with scientists, personal information, book reviews, etc. It is also a forum to discuss issues and problems faced by science and scientists and an effective medium of interaction among scientists in the country and abroad. Current Science is read by a large community of scientists and the circulation has been continuously going up.
Current Science publishes special sections on diverse and topical themes of interest and this has served as a platform for the scientific fraternity to get their work acknowledged and highlighted. Some of the special sections that have been well received in the recent past include remote sensing, waves and symmetry, seismology in India, nanomaterials, AIDS, Alzheimer''s disease, molecular biology of ageing, cancer, cardiovascular diseases, Indian monsoon, water, transport, and mountain weather forecasting in India, to name a few. Contributions to these special issues ‘which receive widespread attention’ are from leading scientists in India and abroad.