Citation

Ahmed MM, Ghasemzadeh A. Transp. Res. C Emerg. Technol. 2018; 91: 371-384.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.trc.2018.04.012

PMID

unavailable

Abstract

Adverse weather conditions can significantly impact roadways by influencing roadway conditions, vehicle performance and driver behavior. Vehicle user characteristics and behavior can be considered as the most important factors affecting the driving task. The ability to see objects in motion, so called "dynamic visual acuity", and the proper reaction process, such as headway and speed selection, are imperative factors for safe driving. In this study, data from the SHRP2 naturalistic driving study (NDS) are used to provide better understanding of driver speed and headway selection behaviors in clear and rainy weather conditions. A unique procedure to identify rain-related trips from the massive SHRP2 database was introduced in this study. In addition, roadway information database (RID) and NDS were utilized to compare driver behavior in clear and heavy rain conditions using matching trips. Matching trips were defined as trips with same driver, same vehicle, and same traversed routes. Preliminary descriptive statistics, partial proportional odds model, as well as geographical information system analyses showed significant differences between driver behavior and performance in clear and rainy weather conditions. One interesting finding of this research is that drivers were less likely to drive above the speed limits on road segments with higher posted speed limits. In addition, it was found that the probability of reducing speed more than 5 kph below the speed limits were 23% and 29% higher in light rain and heavy rain, respectively. Not only will the findings of the study help in providing better insights on drivers' behavior and performance in rainy weather conditions, but it will also serve as a foundation for further studies to investigate driver behavioral factors in other weather conditions using naturalistic driving data.

Language: en

Keywords

Adverse weather conditions; Headway selection; Naturalistic driving study; Partial proportional odds model; SHRP2; Speed selection; Surrogates measures of safety