Original scientific paper
https://doi.org/10.7307/ptt.v30i6.2638
Hazard Detection Prediction Model for Rural Roads Based on Hazard and Environment Properties
Morteza Asadamraji
; PHD candidate, Roadway design and transportation, Tarbiat Modares University, Iran
Mahmoud Saffarzadeh
; Professor of Highway and Transportation Engineering Tarbiat Modares University , Iran
Aminmirza Borujerdian
; Assistant Professor of Highway and Transportation Engineering Tarbiat Modares University, Iran
Tayebeh Ferdousi
; Assistant Professor, Institute of Psychology, Tehran University, Iran
Abstract
A driver’s reaction time encountering hazards on roads involves different sections, and each section must occur at the right time to prevent a crash. An appropriate reaction starts with hazard detection. A hazard can be detected on time if it is completely visible to the driver. It is assumed in this paper that hazard properties such as size and color, the contrast between the environment and a hazard, whether the hazard is moving or fixed, and the presence of a warning are effective in improving driver hazard detection. A driving simulator and different scenarios on a two-lane rural road are used for assessing novice and experienced drivers’ hazard detection, and a Sugeno fuzzy model is used to analyze the data. The results show that the hazard detection ability of novice and experienced drivers decreases by 35% and 64%, respectively, during nighttime compared to daytime. Also, moving hazards increase hazard detection ability by 9% and 180% for experienced and novice drivers, respectively, compared to fixed hazards. Moreover, increasing size, contrast, and color difference affect hazard detection under nonlinear functions. The results could be helpful in safety improvement solution prioritization and in preventing vehicle-pedestrian, vehicle-animal, and vehicle-object crashes, especially for novice drivers.
Keywords
Hrčak ID:
214140
URI
Publication date:
22.12.2018.
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