Sharif Digital Repository

Contraflow or lane reversal is an efficient way for increasing the outbound capacity of a network by reversing the direction of in-bound roads during evacuations. Hence, it can be considered as a potential remedy for solving congestion problems during evacuation in the context of homeland security, natural disasters and urban evacuations, especially in response to an expected disaster. Most of the contraflow studies are performed offline, thus strategies are generated beforehand for future implementation. Online contraflow models, however, would be often computationally demanding and time-consuming. This study contributes to the state of the art of contraflow modelling in two regards. First,... 

Truck accidents are an issue of concern due to their severity. Logit modeling and Neural Network modeling are performed to investigate factors such as vehicle, roadway, environment and driver characteristics that can potentially contribute to the severity of truck accidents. The objective of this study is to present models that can predict the severity of truck accidents and to identify the important factors causing these accidents. Comparison between neural networks and logit modeling are made using vehicle crash data on two-lane rural highways in Iran. A variety of variables related to roadways, vehicles, environment and drivers, such as, driver fatigue, head-on collision and lack of...