Spatial and temporal distribution of pedestrian crashes in Melbourne Metropolitan area

About 1,100 vehicle-pedestrian crashes occur in Melbourne metropolitan area every year. Identifying the temporal and spatial patterns of pedestrian injuries is essential to enhance the safety of these vulnerable road users. In this paper, Decision Tree (DT) and interactive DT are applied to identify the influence of temporal, spatial and personal characteristics on vehicle-pedestrian crash severity. DT is a simple but powerful form of data analyses using machine learning technique. Result of DT indicates that time of crash is the most significant variable in classifying and predicting the severity of vehicle-pedestrian crashes in Melbourne metropolitan area. According to this model, accidents occurring between 19:00 PM and 6:00 AM are more severe than other times. Moreover, spatial correlation shows that there are positive correlation between time and location of crashes. Kernel Density Estimation (KDE) is applied to explore the spatial distribution of vehicle-pedestrian crashes. KDE results show that most vehicle-pedestrian crashes between 19:00 PM and 6:00 AM occur around hotels, clubs and bars. Safety measures should be applied around these areas to assist in preventing and reducing the severity of vehicle-pedestrian crashes.


  • English

Media Info

  • Pagination: 22p
  • Monograph Title: 38th Australasian Transport Research Forum (ATRF 2016), Melbourne, 16th - 18th November 2016

Subject/Index Terms

Filing Info

  • Accession Number: 01627413
  • Record Type: Publication
  • Source Agency: ARRB
  • Files: ITRD, ATRI
  • Created Date: Feb 27 2017 10:06AM