Influence of Land Use,Population,Employment,and Economic Activity on Accidents

Abstract

In this study, the relationships between land use, population, employment by sector, economic output, and motor vehicle accidents are explored. Through the use of comprehensive data from the largest county in Hawaii, the relationships are modeled in a uniform 0.1-mi² (0.259-km²) grid structure and with various linear regression models. This method has an advantage over other approaches that have typically used unevenly sized and shaped traffic analysis zones, census tracts, or block groups. Positive, statistically significant relationships among population, job counts, economic output, and accidents are identified. After some of the general effects are sorted through, a negative binomial (NB) model is used to look at the absolute and relative effects of these factors on the number of pedestrian, bicycle, vehicle-to-vehicle, and total accidents. With a multivariate model, the different effects can be compared and the specific nature of the relationships between zonal characteristics and accidents can be identified. While there is, in general, a significant relationship between all these values, the effects are more pronounced with vehicular crashes than with those involving pedestrians or bicyclists. In addition to the general effects, the influences of employment, economic development, and various activities on the level and type of accidents are investigated. Some challenges associated with modeling these relationships are described, as are implications for traffic safety research. The paper adds to the growing volume of traffic safety research integrating NB regression models and geographic information systems.