Speed and Lateral Vehicle Position Models from Controlled Nighttime Driving Experiment
Publication: Journal of Transportation Engineering
Volume 134, Issue 11
Abstract
Data from a controlled nighttime driving experiment along a complex, two-lane rural highway in Pennsylvania were used to investigate participant speed and lateral vehicle position. Additionally, the association of pavement marking visibility and the roadway geometry on speed and lateral vehicle position was investigated. The modeling methodology employed considered a variety of single equation and systems methods to estimate models for speed and lateral vehicle position. These include ordinary least-squares regression models, random effects panel data models, a three-stage least-squares technique, and seemingly unrelated regression. These methods were used to determine if there was an endogenous relationship between the speed and lateral vehicle position metrics, and to account for the repeat observations on the research participants in the experiment. The results suggest that endogeneity did not exist in the speed and lateral vehicle position measures in the present experiment. A single-equation random effects panel regression model was an improvement over the ordinary least-squares regression model for the change in speed metric. However, the ordinary least-squares regression model was appropriate for the lateral vehicle position metric. A seemingly unrelated regression model was also specified to account for contemporaneous correlation across the change in speed and lateral vehicle position models. It was found that the roadside hazard rating, horizontal curve direction, vertical grade, horizontal curve radius, upstream horizontal curve radius, and approach tangent length all were associated with vehicle speed on the complex, two-lane rural highway. The horizontal curve direction, roadside hazard rating, vertical grade, horizontal curve radius, and approach tangent length all were associated with lateral vehicle position in the present experiment.
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Acknowledgments
The writers wish to express their gratitude to both the FHwA and PennDOT for jointly sponsoring the research reported herein. Research staff from Science Applications International Corporation (SAIC) collected the experimental data used in this study. The writers would like to acknowledge the SAIC team, managed by Dr. John Molino. The writers also wish to acknowledge the review comments provided by Dr. Richard J. Porter and those provided by three anonymous reviewers of the paper. Mr. Vishesh Karwa provided data analysis assistance.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 134 • Issue 11 • November 2008
Pages: 439 - 449
Copyright
© 2008 ASCE.
History
Received: Aug 23, 2007
Accepted: Jun 6, 2008
Published online: Nov 1, 2008
Published in print: Nov 2008
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