Technical Papers
Feb 24, 2017

Predicting the Distribution of Vehicle Travel Paths along Horizontal Curves

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 143, Issue 7

Abstract

Horizontal curves tend to be associated with a disproportionate number of severe crashes. Roadway departure crashes are the most frequent crash types on horizontal curves and are highly influenced by driver behavior in conjunction with roadway and environmental factors. Failure to maintain proper lane position along the curve is one of the reasons for an increase in roadway departure crashes. The primary aim of any curve-related treatment is to influence vehicle travel paths by reducing the undesirable paths and thus assist in improving vehicular safety along horizontal curves. To date, an analysis of vehicle travel paths as a function of various factors that influence travel path behavior has not been conducted. The objective of this study is to develop models to predict vehicle travel paths along horizontal curves as a function of curve geometric, pavement, and traffic control characteristics. Lane width, curve sharpness, and speed differential have been identified as key geometric variables. Skid number, which describes the skid resistance of a pavement, was found to significantly influence vehicle travel paths.

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Information

Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 143Issue 7July 2017

History

Received: Feb 16, 2016
Accepted: Dec 7, 2016
Published online: Feb 24, 2017
Published in print: Jul 1, 2017
Discussion open until: Jul 24, 2017

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Authors

Affiliations

Srinivas Reddy Geedipally, Ph.D. [email protected]
P.E.
Associate Research Engineer, Texas A&M Transportation Institute, 110 N. Davis Dr., Suite 101 Arlington, TX 76013 (corresponding author). E-mail: [email protected]
Michael P. Pratt [email protected]
P.E.
Assistant Research Engineer, Texas A&M Transportation Institute, 3135 TAMU, College Station, TX 77843-3135. E-mail: [email protected]

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