Modeling rear-end collisions including the role of driver's visibility and light truck vehicles using a nested logit structure.
This paper presents an analysis of the effect of the geometric incompatibility of light truck vehicles (LTV)--light-duty trucks, vans, and sport utility vehicles--on drivers' visibility of other passenger cars involved in rear-end collisions. The geometric incompatibility arises from the fact that most LTVs ride higher and are wider than regular passenger cars. The objective of this paper is to explore the effect of the lead vehicle's size on the rear-end crash configuration. Four rear-end crash configurations are defined based on the type of the two involved vehicles (lead and following vehicles). Nested logit models were calibrated to estimate the probabilities of the four rear-end crash configurations as a function of driver's age, gender, vehicle type, vehicle maneuver, light conditions, driver's visibility and speed. Results showed that driver's visibility and inattention in the following (striker) vehicle have the largest effect on being involved in a rear-end collision of configuration CarTrk (a regular passenger car striking an LTV). Possibly, indicating a sight distance problem. A driver of a smaller car following an LTV, have a problem seeing the roadway beyond the LTV, and therefore would not be able to adjust his/her speed accordingly, increasing the probability of a rear-end collision. Also, the probability of a CarTrk rear-end crash increases in the case that the lead vehicle stops suddenly.
Abdel-Aty
Mohamed
M
Department of Civil and Environmental Engineering, University of Central Florida, Orlando, FL 32816-2450, USA. mabdel@mail.ucf.edu
Abdelwahab
Hassan
H
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D001334:Automobile Driving / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D018986:Motor Vehicles / Q000706:statistics & numerical data*; D012449:Safety; D012737:Sex Factors; D014796:Visual Perception