Publication: Research - peer-review › Journal article – Annual report year: 2011
This study intends to provide insight into pedestrian accidents by uncovering their patterns in order to design preventive measures and to allocate resources for identified problems. Kohonen neural networks are applied to a database of pedestrian fatal accidents occurred during the four-year period between 2003 and 2006. Results show the existence of five pedestrian accident patterns: (i) elderly pedestrians crossing on crosswalks mostly far from intersections in metropolitan areas; (ii) pedestrians crossing suddenly or from hidden places and colliding with two-wheel vehicles on urban road sections; (iii) male pedestrians crossing at night and being hit by four-wheel vehicles on rural road sections; (iv) young male pedestrians crossing at night wide road sections in both urban and rural areas; (v) children and teenagers crossing road sections in small rural communities. From the perspective of preventive measures, results suggest the necessity of designing education and information campaigns for road users as well as allocating resources for infrastructural interventions and law enforcement in order to address the identified major problems.
|Citations||Web of Science® Times Cited: No match on DOI|
- Kohonen networks, Pedestrian fatalities, Cluster analysis, Accident patterns