Citation

Aiash A, Robusté F. Transp. Res. Proc. 2023; 71: 235-243.

Copyright

(Copyright © 2023, Elsevier Publications)

DOI

10.1016/j.trpro.2023.11.080

PMID

unavailable

Abstract

Pedestrian crashes can be affected by different factors that can increase or decrease their possibilities of occurring and other consequences related to them, including the level of injury. In Barcelona, in particular, and in Spain, in general, several events happened during both the years 2020 and 2021. The first year had the pandemic and different events that affected the number of traffic crashes, similar to the following year, which had the introduction of applying the speed limit of 30 km/h inside the cities. Therefore, this study analyzes several risk factors related to pedestrian crashes during both the 2020 and 2021 years. A Bayesian network model is employed for this reason to determine the impact of those risk factors through these different years. This is done by calculating the conditional probabilities for the risk factors based on the applied model with determining the accuracy of the employed model in predicting the utilized data. The results show that elderly pedestrians are more likely to have severe or fatal injuries. The evening period shows higher probabilities of having pedestrian crash injuries compared to other periods of the day. Passage for pedestrians that are regulated by traffic lights is found to have a high probability of having severe and fatal injuries.

Language: en

Keywords

Barcelona; Bayesian network; Injury; Pedestrian; Risk factors