| Roadway crashes claim more than 30,000 lives each year in the United States, and they continue to affect the lives of people adversely. This problem becomes even more challenging when aging populations are considered due to their vulnerability and fragility to crashes. This is especially a major concern in Florida since the crash risk for the aging populations is increasing day by day proportional to the population growth of aging Floridians. This study investigates the spatial and temporal patterns of aging-involved crashes using Geographical Information Systems (GIS)-based methods with a case study on three urban counties in Florida. These counties are selected based on the high aging-involved crash rates, as identified by the Safe Mobility for Life Coalition of Florida. Among the methods studied, a network distance-based kernel density estimation method, namely SANET, is identified as a very effective tool since it provides an unbiased distribution of the crashes by calculating the actual distances between the crashes over the roadway network. GIS-based results are also supported with a binary logistic regression analysis in order to identify the significant factors affecting the aging-involved crashes. Results indicate that high risk locations for aging-involved crashes show different spatial and temporal patterns than those for other age groups. These pattern specific differences include the following: (a) Intersections have an adverse effect on the 65+ populations more than other adult age groups, (b) Aging-involved population crashes occur during the mid-day rather than the peak hours, which is not a similar pattern for other adult age groups, especially for the working populations, and (c) Weekdays have more aging-involved crashes than the weekends contrary to the other age group crashes. Investigating these distinct patterns thoroughly can lead to better aging-focused transportation plans and policies. |
