Development of accident prediction models for pedestrian crossings

2Citations
Citations of this article
18Readers
Mendeley users who have this article in their library.

Abstract

In large Polish cities like Warsaw, pedestrians constitute almost 60% of road fatalities. Although traffic safety situation in general is improving, the numbers of pedestrians hit when crossing a road have not significantly decreased over the last six years. A negative binomial model was estimated for predicting accidents at unsignalised pedestrian crossings based on accident data from 52 crossings in Warsaw. A total of 58 pedestrian accidents were recorded at these crossings during the last seven years. The model shows that the number of accidents is less-than-proportional to both pedestrian and motorised traffic daily volumes. Other risk factors affecting pedestrian safety are: higher proportion of heavy vehicles and location in a mixed land use area. The model can be used with the Empirical Bayes method for an unbiased identification of high risk locations.

Cite

CITATION STYLE

APA

Olszewski, P., Osińska, B., Szagała, P., & Włodarek, P. (2018). Development of accident prediction models for pedestrian crossings. In MATEC Web of Conferences (Vol. 231). EDP Sciences. https://doi.org/10.1051/matecconf/201823103002

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free