Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data

Travel time distribution (TTD) has been widely used to represent the traffic conditions on freeways and help to analyze travel time reliability (TTR). The goal of this study is to develop a systematic approach to analyzing TTD on different types of roadway segments along a corridor. By examining the...

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Main Authors: Zhen Chen, Wei David Fan
Format: Article
Language:English
Published: Elsevier 2020-03-01
Series:International Journal of Transportation Science and Technology
Online Access:http://www.sciencedirect.com/science/article/pii/S2046043019301121
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spelling doaj-b2bc1a6de52c4027a309b6622a31e08d2020-11-25T03:09:21ZengElsevierInternational Journal of Transportation Science and Technology2046-04302020-03-01916475Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle dataZhen Chen0Wei David Fan1USDOT Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE), Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, United StatesCorresponding author.; USDOT Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE), Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, United StatesTravel time distribution (TTD) has been widely used to represent the traffic conditions on freeways and help to analyze travel time reliability (TTR). The goal of this study is to develop a systematic approach to analyzing TTD on different types of roadway segments along a corridor. By examining the historical TTR pattern using planning time index (PTI), four typical segments are identified and selected first. The distributions of travel time are then analyzed under different time of day, day of week, segment location and weather. The goodness-of-fit tests of different distributions are then conducted, and the results indicate that Burr distribution can provide highest acceptance rate with the consideration of different times of day (TOD) and days of week (DOW). The results also indicate that Burr distribution can provide highest acceptance rate with the consideration of different weather conditions. This study can provide the insightful information about TTD characteristics under different scenarios, and the results can also help transportation planners make informed decisions. Keywords: Travel time distribution, Travel time reliability, Probe vehicle datahttp://www.sciencedirect.com/science/article/pii/S2046043019301121
collection DOAJ
language English
format Article
sources DOAJ
author Zhen Chen
Wei David Fan
spellingShingle Zhen Chen
Wei David Fan
Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data
International Journal of Transportation Science and Technology
author_facet Zhen Chen
Wei David Fan
author_sort Zhen Chen
title Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data
title_short Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data
title_full Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data
title_fullStr Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data
title_full_unstemmed Analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data
title_sort analyzing travel time distribution based on different travel time reliability patterns using probe vehicle data
publisher Elsevier
series International Journal of Transportation Science and Technology
issn 2046-0430
publishDate 2020-03-01
description Travel time distribution (TTD) has been widely used to represent the traffic conditions on freeways and help to analyze travel time reliability (TTR). The goal of this study is to develop a systematic approach to analyzing TTD on different types of roadway segments along a corridor. By examining the historical TTR pattern using planning time index (PTI), four typical segments are identified and selected first. The distributions of travel time are then analyzed under different time of day, day of week, segment location and weather. The goodness-of-fit tests of different distributions are then conducted, and the results indicate that Burr distribution can provide highest acceptance rate with the consideration of different times of day (TOD) and days of week (DOW). The results also indicate that Burr distribution can provide highest acceptance rate with the consideration of different weather conditions. This study can provide the insightful information about TTD characteristics under different scenarios, and the results can also help transportation planners make informed decisions. Keywords: Travel time distribution, Travel time reliability, Probe vehicle data
url http://www.sciencedirect.com/science/article/pii/S2046043019301121
work_keys_str_mv AT zhenchen analyzingtraveltimedistributionbasedondifferenttraveltimereliabilitypatternsusingprobevehicledata
AT weidavidfan analyzingtraveltimedistributionbasedondifferenttraveltimereliabilitypatternsusingprobevehicledata
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