| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 573245 | Accident Analysis & Prevention | 2009 | 8 Pages |
Abstract
The composed dataset was analyzed and processed to develop a model that predicts the risk associated with the passing behavior. Tobit regression models were found to be more suitable, in comparison to ordinary least square models and Hazard-based Duration models. The explanatory variables tested represent road geometry, traffic conditions and drivers' characteristics. It was found that while the traffic related variables had the most important effect on the measure of risk chosen, factors related to the geometric design and the driver characteristics also had a significant contribution.
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Authors
Haneen Farah, Shlomo Bekhor, Abishai Polus,