Measuring and comparing the spatiotemporal evolution of accident hot spots

Abstract

[EMBARGOED UNTIL 6/1/2023] One reality of transportation systems is that vehicular accidents can happen practically anywhere and at any time. An increasing body of research suggests though that spatial and/or temporal dependencies (i.e., clusters or hot spots) among accidents likely exist. Along with understanding where and when such spatiotemporal dependencies may occur, another important facet to consider is the geographic extent or area associated with the hot spots. For example, an accident hot spot may involve a small, isolated portion of the transportation system or a much more expansive geographic area. Better delineation and quantification of the morphological characteristics of accident hot spots can provide valuable decision support for planning for accident hot spot mitigation and prevention. As the size and shape of accident hot spots may evolve over time, the capability to track such dynamics is vital, especially with respect to the identification of effecting processes of hot spot occurrence as well as assessments of the efficacy of efforts to mitigate factors underlying hot spot development. For example, a hot spot that is increasing in size over time may indicate areas that are started with a small cluster size then become a part of a larger cluster size during the next periods. Likewise, a cluster that is decreasing in size may signify that some areas may participate with a big cluster size then decrease to a smaller cluster size later. Besides understanding the trend of cluster size evolution during multiple time periods, another important aspect to consider is the percentage or amount of similarity/dissimilarity of cluster morphological characteristics between different urban areas. Better understanding and quantification of morphological characteristics of accident hot spots' similarity characteristics over different urban area levels can also provide valuable decision support for accident safety planning and improve accident alleviation and prevention. To this end, a Geographical Information Systems (GIS) based framework is outlined to facilitate the analysis and comparison of the morphological characteristics of hot spots over time. The analysis framework is applied to a case study of vehicular accidents reported over a two-year period for Morphological analysis and a three-year period for statistical comparison computing to demonstrate its practical utility. The application results of the morphological analysis indicate that patterns of change in hot spot morphology can be effectively quantified, and a variety of informative spatial and temporal patterns can be detected. In addition, the results of cluster statistical comparison computing revealed that the level or percentage of cluster characteristics similarity between urban areas decreases with the increment of the urban city size and road levels complexity.