Spatio-Temporal Analysis of Pedestrian Accidents Using Kernel Density Estimation and Radar Graph, Case Study: Mashhad, Iran

Pedestrians are regarded as one of the most vulnerable road users and the source of large number of fatalities or injuries in case of road accidents. Accordingly, in recent years efforts have been carried out to present the methods in order to investigate whether there is and organized pattern among accidents. When dealing with spatio-temporal data such as traffic accidents, the effects of events locating in the neighboring of others cannot be ignored. In this research, pedestrian accidents in Mashhad, Iran over five years of study, 2012-2016 have been considered. By aggregating traffic data over 253 traffic analyses zone (TAZ), spatio-temporal relationships have been conducted using Kernel Density Estimation and radar graphs. In the next step, the meaningful factors affecting the pedestrian accident occurrence have been investigated and inattention and speeding have found to be as the most leading cause of pedestrian occurrence respectively. The results of this paper can provide the traffic engineers with an insight into regions with the clustering of pedestrian accident that need more attention and assigning budget and time from transportation authorities.