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.

Structural equation modeling (SEM) is a confirmatory, multivariate technique used to examine causal relationships between variables. Related to path analysis with a goal of selecting a model that best explains underlying relationships between variables, SEM is a useful tool for traffic safety research. This study examined the severity of crashes in terms of factors commonly attributed to accidents. These factors included human, vehicle, and roadway factors, along with accessibility measures that were considered relevant in previous studies. In this study, SEM was used to test an a priori model of crash severity. The analysis was carried out in a two-step process. The measurement model was first tested with a confirmatory factor analysis. After the validity of the measurement model was established, a four-latent-factor structural model was run. With an acceptable model fit, the magnitude of standardized path coefficients from the exogenous latent variables provided a means to assess the relative importance of the latent factors on crash severity. The results showed that the human latent factor was the most influential. Although a positive statistical relationship existed between roadway factors and crash severity, accessibility factors had the opposite effect on crash severity, that is, increased accessibility was shown to reduce crash severity.

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The purpose of this paper is to describe, analyze, and compare disruptions to the transportation system from two recent disasters in Hawai’i. While they occurred on different islands (Kaua`i and Hawai’i) and resulted from different hazards (flooding and volcanic eruption), there are important commonalities due to the disruption of surface transportation and the consequences for evacuation and emergency services as well as response and recovery. On Kaua`i, the physical impacts were fewer, with a 2 mile stretch of highway damaged by flooding and landslides as compared with 31.1 miles of roads covered by lava on Hawai`i island. Both disasters had similar population impacts, with 5,566 people impacted for Kaua`i and 5,563 for Hawai`i. Another difference is a shorter duration of disruption and a quicker restoration of transportation services for Kaua`i compared with the slower, continuous, and permanent loss of transportation services in Hawai`i. The two cases provide learning opportunities for emergency managers, transportation planners, and engineers. Both demonstrate the need for redundancy in transportation infrastructure for rescue and recovery operations. While the evacuation from a flooding event is different than from a slower-moving volcanic crisis, the importance of staging areas, route planning, alternative travel modes, and training cannot be overemphasized. These disasters focus attention on the critical role of transportation systems in response and recovery. In addition to short-term operational actions, longer-term mitigation, adaptation, and risk reduction strategies are needed to support transportation resilience.