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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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 |
_version_ |
1724663131606614016 |