Abstract: This paper investigates the classification of road accidents using neural networks and fuzzy classification techniques. Accident correctability by road improvements has been advocated as an important criterion in the ...

Abstract: In traditional black-spot programs aimed at improving highway safety, locations are identified as accident prone based on the total number of accidents. This criteria provides no consideration of whether the accidents were ...

Abstract: The main objective of this paper is to introduce a systematic approach to determine the need for and location of truck escape ramps (TERs). The approach utilizes variables concerning the design vehicle, the road, and the ...

Abstract: This paper presents a slow‐moving‐vehicle (SMV) model for estimating vehicular delays and queuing. The model is a simplified version of a shock‐wave model for the case where passing is restricted. The main inputs of the ...

Abstract: The ability to accurately evaluate roadside hazards is very important to highway safety officials and researchers, who are concerned with reducing the frequency, severity, and ultimately, the cost of “run‐off‐the‐road” ...

Abstract: This paper describes a method to identify accident-prone locations (APLs) based on an assessment of factors that contribute to accidents. Current methods to identify APLs make no distinction between accidents that result ...