Spatial and Temporal Visualisation Techniques for Crash Analysis
Faculty of Computing, Health and Science
School of Computer and Security Science
Understanding the underlying structure of single vehicle crashes (SVCs) is essential for improving safety on the roads. Past research has found that SVCs tend to cluster both spatially and temporally. However, limited research has been conducted to investigate the interaction between the location of SVCs and the time they occur, especially at different levels of scales or spatial extents. This paper applied spatial, temporal and spatio-temporal techniques to investigate patterns of SVCs in Western Australia between 1999 and 2008, at different levels of scale. Spider graphs were adapted to identify temporal patterns of vehicle crashes at two different levels of scales: daily and weekly with respect to their causes. The spatial structures of vehicle crashes were analysed using Kernel Density Estimation analysis at three different scales: West Australia, Metropolitan area, and Perth Local Government Area (LGA). These are illustrated using spatial zooming theory. Comap was then used to demonstrate the spatio-temporal interaction effect on vehicle crashes. The results show significant differences in spatiotemporal patterns of SVCs for various crash causes. The techniques used here have the potential to help decision makers in developing effective road safety strategies.