Hotspots and social background of urban traffic crashes: A case study in Cluj-Napoca (Romania)

Accid Anal Prev. 2016 Feb:87:117-26. doi: 10.1016/j.aap.2015.11.026. Epub 2015 Dec 9.


Mobility practices have changed dramatically in Romanian towns over the last 25 years, following the collapse of socialist mobility restrictions. Urban areas like Cluj-Napoca are facing both increasing immigration and car mobility, and therefore increasing levels of road traffic crashes. The analysis of traffic crashes is one of the most important elements for improving the road safety policy. This paper is divided in two parts. In the first one, the authors focus on identifying the traffic crash hotspots along the street network, while in the second part they discuss the social background of road traffic crash occurrence. The first step in analyzing traffic crashes is to determine crash hotspots. A four-year record (2010-2013) provided by the Traffic Department of the General Inspectorate of Romanian Police (GIRPTD) was used. As a method of hotspot determination, the Kernel Density Estimation tool was employed, in the frame of the spatial analysis along network (SANET). The outcome was the hotspot map of traffic crashes in Cluj-Napoca. The results have revealed 4 categories of street segments: not-dangerous, low-dangerous, medium-dangerous and high-dangerous. Based on this classification, at least 4 dangerous areas were identified, located at the city entrances-exits (in the West, North-West and East) and the city center (the most dangerous zone). The second part of the paper focuses on social groups involved in car crashes. The following are considered: age, gender and blood alcohol concentration of the person (driver or pedestrian) found guilty for every individual crash.

Keywords: Hotspots; Kernel Density Estimation; SANET; Social vulnerability; Traffic crashes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic / statistics & numerical data*
  • Adolescent
  • Age Factors
  • Causality
  • Environment Design*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Models, Theoretical
  • Pedestrians / statistics & numerical data
  • Risk Assessment / statistics & numerical data
  • Romania
  • Safety
  • Sex Factors
  • Social Environment*
  • Urban Population / statistics & numerical data*