Decomposition of Travel Time Reliability into Various Sources Incidents, Weather, Work Zones, Special Events, and Base Capacity

An empirical, corridor-level method is proposed to divide the travel time unreliability or variability over a freeway section into the following components: incidents, weather, work zones, special events, and inadequate base capacity or bottlenecks. The method consists of three steps: (a) corridor-l...

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Published inTransportation research record Vol. 2229; no. 1; pp. 28 - 33
Main Authors Kwon, Jaimyoung, Barkley, Tiffany, Hranac, Rob, Petty, Karl, Compin, Nick
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.01.2011
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Abstract An empirical, corridor-level method is proposed to divide the travel time unreliability or variability over a freeway section into the following components: incidents, weather, work zones, special events, and inadequate base capacity or bottlenecks. The method consists of three steps: (a) corridor-level aggregation of travel time and source data, (b) quantile regression to fit the 95th percentile of travel time on the source variables, and (c) calculation of the contribution of individual sources to the buffer time. It could be applied to other percentile-based travel time reliability measures such as planning time and 90th and 95th percentiles. Once the source data are defined, the method can be automatically applied to any site with minimum calibration. When applied to a 30.5-mi section of northbound I-880 in the San Francisco Bay Area, California, the method revealed that traffic accidents contributed 15.1% during the morning and 25.5% during the afternoon, among others, and most of the remaining reliability came from recurrent bottlenecks. Quantifying the components of travel time variability at individual freeway sites is essential in developing effective strategies to mitigate congestion.
AbstractList An empirical, corridor-level method is proposed to divide the travel time unreliability or variability over a freeway section into the following components: incidents, weather, work zones, special events, and inadequate base capacity or bottlenecks. The method consists of three steps: (a) corridor-level aggregation of travel time and source data, (b) quantile regression to fit the 95th percentile of travel time on the source variables, and (c) calculation of the contribution of individual sources to the buffer time. It could be applied to other percentile-based travel time reliability measures such as planning time and 90th and 95th percentiles. Once the source data are defined, the method can be automatically applied to any site with minimum calibration. When applied to a 30.5-mi section of northbound 1-880 in the San Francisco Bay Area, California, the method revealed that traffic accidents contributed 15.1 % during the morning and 25.5% during the afternoon, among others, and most of the remaining reliability came from recurrent bottlenecks. Quantifying the components of travel time variability at individual freeway sites is essential in developing effective strategies to mitigate congestion.
An empirical, corridor-level method is proposed to divide the travel time unreliability or variability over a freeway section into the following components: incidents, weather, work zones, special events, and inadequate base capacity or bottlenecks. The method consists of three steps: (a) corridor-level aggregation of travel time and source data, (b) quantile regression to fit the 95th percentile of travel time on the source variables, and (c) calculation of the contribution of individual sources to the buffer time. It could be applied to other percentile-based travel time reliability measures such as planning time and 90th and 95th percentiles. Once the source data are defined, the method can be automatically applied to any site with minimum calibration. When applied to a 30.5-mi section of northbound I-880 in the San Francisco Bay Area, California, the method revealed that traffic accidents contributed 15.1% during the morning and 25.5% during the afternoon, among others, and most of the remaining reliability came from recurrent bottlenecks. Quantifying the components of travel time variability at individual freeway sites is essential in developing effective strategies to mitigate congestion.
Author Compin, Nick
Petty, Karl
Barkley, Tiffany
Kwon, Jaimyoung
Hranac, Rob
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StartPage 28
SubjectTerms Calibration
Climatology
Freeways
Regression
Strategy
Traffic accidents
Transportation
Weather
Subtitle Incidents, Weather, Work Zones, Special Events, and Base Capacity
Title Decomposition of Travel Time Reliability into Various Sources
URI https://journals.sagepub.com/doi/full/10.3141/2229-04
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