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Journal Article

Citation

Tarko A, Hall T, Romero M, Jiménez CG. Accid. Anal. Prev. 2016; 91: 127-134.

Affiliation

Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall Dr., West Lafayette, IN 47907, United States. Electronic address: clizaraz@purdue.edu.

Copyright

(Copyright © 2016, Elsevier Publishing)

DOI

10.1016/j.aap.2016.02.032

PMID

26974029

Abstract

The rollover propensity of SUVs and trucks has long been recognized as a potential safety issue. The propensity may increase with the growing number of roundabouts that are being built on high-speed roadways designed for 50mi/h or higher. This paper presents a research methodology developed to evaluate the rollover propensity of trucks on existing roundabouts and other roads with tight curves and high-speed traffic. The research objective was accomplished by developing an advanced 3D model of rollover that is applicable to field observations of the undisturbed behavior of multiple vehicles. This model was supplemented with a nonintrusive method of data collection based on recording video from a remote location and a novel method of extracting the data from the video material and processing it to generate the input required by the rollover model. The method is demonstrated in this paper on an example roundabout by evaluating the rollover propensity of semi-trailers in daytime and nighttime conditions. The results indicate that the drivers observed in nighttime conditions compensated well for the challenging conditions by driving more cautiously, which led to their rollover propensity at night being lower than during the day. The method was found useful for timely detection of the potential rollover problem without waiting for crashes.

Copyright © 2016 Elsevier Ltd. All rights reserved.


Language: en

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