ali karami - MSc. Grad. Department of Civil Engineering, Khajeh Nasir Toosi University of Technology, Tehran, Iran
Mansour Hadji Hosseinlou - Associate Professor, Department of Civil Engineering, Khajeh Nasir Toosi University of Technology, Tehran, Iran
mohammad hossein abbasi - PhD. Student, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran
monteiro figuerira - Professor, Department of Civil Engineering, University of Lisbon, Lisbon, Portugal

One of the most important needs of pedestrians is safety at crossing points, especially at intersections. Intersections are important parts of the urban road network because any disruption in them reduces the capacity of the entire network. The main objective of this research is to propose an appropriate method for prioritizing urban intersections with considering the important factors affecting pedestrian crashes to promote the safety level of pedestrians at intersections of the 11th district of Tehran. In this paper, after comparing different models, finally, the negative binomial model was developed to predict the effects of a set of factors expected to the frequency of pedestrian crashes. According to the proposed model, a larger volume of pedestrians and vehicles reduced the safety of intersections. Also imposing traffic restrictions in the central business district causes increasing motorcycle flows and has led to more dangerous area. Also, according to the results of prioritization using this method showed that the intersection of Imam Khomeini and Valiasr with an improvement potential of 6.93 has the most potential of improvement. Based on crash reduction factor, a method for estimating the effect of a variable on crash frequencies, one-unit increasing in natural logarithm of average pedestrian and vehicle volumes, commercial land use and number of public transport stations will increase the crash frequencies by 29.82, 83.49, 56.99 and 14.34 percents, respectively. Also, when sidewalk effective widths increased by one-unit, the probability of pedestrian crashes at intersections will reduced by 14.87 percent.

Prioritizing, pedestrian accidents, negative binomial model, Urban intersection, safety