This paper describes research with the objective of developing and validating a corridor arterial model to estimate the travel time index (TTI) for mobility analysis. The TTI is the ratio of the travel rate (minutes per mile) during the peak period to the travel rate (minutes per mile) during the off-peak period. The models are most useful for sketch planning purposes in areas where monitoring infrastructure is not in place. Practitioners in small and medium-sized communities, particularly those on the developing fringe of such communities, will benefit from the use of the models for tracking mobility along roadways of interest and prioritizing roadway improvements. This paper describes the development and validation of two models to assist transportation professionals in estimating TTI in the arterial environment during light and moderate congestion conditions. A 2.6-mi major arterial corridor in College Station, Texas, was used to develop the models, and three study corridors in Virginia were used to validate the models. To address limitations of existing models, the models presented in this paper (a) consider driveway density, (b) are corridor-based, (c) are a function of generally available or easy-to-obtain independent variables, (d) are calibrated and validated with extensive field data, and (e) explain a relatively high degree of variability. The use of TTI also makes the models more transferable. For sketch-planning applications, the models are a function of relatively available or easy-to-estimate data including traffic volume, driveway density, signal green time relative to the cycle time, and signal coordination conditions.
Developing and Applying Models for Estimating Arterial Corridor Travel Time Index for Transportation Planning in Small to Medium-Sized Communities
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2244 , 1 ; 81-90
01.01.2011
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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