Abstract
Travel time reliability is defined as the consistency or dependability in travel times during a specified period of time under stated conditions, and it can be used for evaluating the performance of traffic networks based on LOS (Level of Service) of the HCM (Highway Capacity Manual). Travel time reliability is also one of the most understood measures for road users to perceive the current traffic conditions, and help them make smart decisions on route choices, and hence avoid unnecessary delays (Liu & Ma, 2009). Therefore, travel time reliability on urban arterials has become a major concern for daily commuters, business owners, urban transportation planners, traffic engineers, MPO (Metropolitan Planning Organization) members as congestion has grown substantially over the past thirty (30) years in urban areas of every size.
Many studies have been conducted in the past on travel time reliability without a full analysis or explanation of the fundamental traffic and geometric components of the corridors. However, a generalized model which captures the different factors that influence travel time reliability such as posted speed, access density, arterial length, traffic conditions, signalized intersection spacing, roadway and intersection geometrics, and signal control settings is still lacking. Specially, there is a need that these factors be weighted according to their impacts.
This dissertation by using a linear regression model has identified 10 factors that influence travel time reliability on urban arterials. The reliability is measured in term of travel time threshold, which represents the addition of the extra time (buffer or cushion time) to average travel time when most travelers are planning trips to ensure on-time arrival. "Reliable" segments are those on which travel time threshold is equal to or lowers than the sum of buffer time and average travel time.
After validation many scenarios are developed to evaluate the influencing factors and determine appropriate travel times reliability. The linear regression model will help 1) evaluate strategies and tactics to satisfy the travel time reliability requirements of users of the roadway network--those engaged in person transport in urban areas 2) monitor the performance of road network 3) evaluate future options 4) provide guidance on transportation planning, roadway design, traffic design, and traffic operations features.
Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-5180 |
Date | 01 January 2012 |
Creators | Bonnaire Fils, Prony |
Publisher | Scholar Commons |
Source Sets | University of South Flordia |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Graduate Theses and Dissertations |
Rights | default |
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