SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Ahangari S, Jeihani M, Rahman MM, Dehzangi A. Int. J. Traffic Transp. Eng. (Belgrade) 2021; 11(1): e6.

Copyright

(Copyright © 2021, City Net Scientific Research Center, Faculty of Transport and Traffic Engineering, University of Belgrade)

DOI

10.7708/ijtte.2021.11(1).06

PMID

unavailable

Abstract

This study investigates driving behavior under distraction on four different road classes - freeway, urban arterial, rural, and local road in a school zone - using a high-fidelity driving simulator. Some 92 younger participants from a reasonably diverse sociodemographic background drove a realistic midsize network in the Baltimore metropolitan area and were exposed to different distractions. A total of 1,952 simulation runs were conducted. An ANOVA and Tukey Post Hoc analysis showed that distracted driving behavior demonstrates different patterns on various roads. This research developed a support vector machine model that achieved distraction prediction ability among different routes with an accuracy of 94.24%, which to the best of our knowledge, is the best for such a task. The results indicate that driver distraction prediction models probably would be more accurate if developed separately for each road class.


Language: en

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print