The current study examined the interplay between demographic, land use, and roadway accessibility variables and types of accidents in Honolulu, Hawaii. A uniform 0.1-mi² grid was used as the basis for analysis and was combined with binomial logistic regression. Eight models were constructed to consider the relationship between total accidents, injury, fatality, pedestrian, bicycle, moped, motorcycle, and motor vehicle to motor vehicle crashes as a function of population, land use, and accessibility measures such as road length, bus stops, length of bus route, number of intersections, and dead ends. The results indicate that demographic variables such as job count and number of people living below the poverty level are significantly associated with injury crashes and pedestrian and bike crashes. Business and commercial areas are strongly associated with increased total as well as injury and fatal crashes. Accessibility measures such as the number of bus stops and the number of intersections are associated with increases in all types of accidents. The implications for safety research and other programs are summarized.

At first glance, the relationship between crashes and land use appears obvious. Various types of land uses tend to generate and attract different types of trips, and trip-making behavior affects the nature and volume of traffic. As the use of land intensifies, it does not seem unreasonable to expect that the potential exposure to crashes would also increase. Yet upon closer inspection, it is evident that crashes are more a function of the characteristics of drivers and travelers than the underlying uses of land. Using comprehensive police crash data linked to a land use database, the relationships between land use and automobile crashes in Hawaii are investigated. Recent developments in geographic information system technology and the availability of spatial databases provide a rich source of information with which to investigate the relationships between crashes and the environments in which they occur. Although the patterns in terms of crashes and the underlying use of land are difficult to describe, the implications of these findings for planners, developers, and those interested in traffic safety are apparent.