Identification of Factors Leading to High Severity of Crashes in Rural Areas

This study made an effort to identify critical factors contributing to increased crash severities on rural highways. Crash data from the Kansas Accident Reporting System (KARS) database was analyzed and crash severity was modeled using ordered choice models. Many driver-related factors, such as alcohol involvement, lack of seat belt usage, excessive speed, and driver ejections because of the crash contribute to the increased severity of crashes in rural areas. Also, severities of single-vehicle crashes are higher than two-vehicle and animal-vehicle crashes. Factors related to roadway geometry such as sharp curves and steep grades are also found to contribute to the increased crash severity in rural areas

A space-time multivariate Bayesian model to analyse road traffic accidents by severity

The paper investigates the dependences between levels of severity of road traffic accidents, accounting at the same time for spatial and temporal correlations. The study analyses road traffic accidents data at ward level in England over the period 2005–2013. We include in our model multivariate spatially structured and unstructured effects to capture the dependences between severities, within a Bayesian hierarchical formulation. We also include a temporal component to capture the time effects and we carry out an extensive model comparison. The results show important associations in both spatially structured and unstructured effects between severities, and a downward temporal trend is observed for low and high levels of severity. Maps of posterior accident rates indicate elevated risk within big cities for accidents of low severity and in suburban areas in the north and on the southern coast of England for accidents of high severity. The posterior probability of extreme rates is used to suggest the presence of hot spots in a public health perspective.Areti Boulieri acknowledges support from the National Institute for Health Research and the Medical Research Council Doctoral Training Partnership. Marta Blangiardo acknowledges support from the National Institute for Health Research and the Medical Research Council–Public Health England Centre for Environment and Health. Silvia Liverani acknowledges support from the Leverhulme Trust (grant ECF-2011-576)

Exploratory Spatial Data Analysis in Traffic Safety

This paper presents an exploratory spatial data analysis (ESDA) of road traffic crashes at different severity levels in West Virginia (WV). Although ESDA can support transportation safety decision-making by helping planners understand and summarize crash data, it is underutilized in practice. This paper describes the application of five representative easy-to-use method to identify crash patterns and high crash-risk counties in WV. Analysis of crash data from 2010 to 2015 indicated that traffic crashes in WV were not spatially correlated. However, crash severities were found to be positively correlated

Analysis of Potential Co-Benefits for Bicyclist Crash Imminent Braking Systems

In the US, the number of traffic fatalities has had a long term downward trend as a result of advances in the crash worthiness of vehicles. However, these improvements in crash worthiness do little to protect other vulnerable road users such as pedestrians or bicyclists. Several manufacturers have developed a new generation of crash avoidance systems that attempt to recognize and mitigate imminent crashes with non-motorists. While the focus of these systems has been on pedestrians where they can make meaningful contributions to improved safety [1], recent designs of these systems have recognized mitigating bicyclist crashes as a potential co-benefit. This paper evaluates the performance of one system that is currently available for consumer purchase. Because the vehicle manufacturer does not claim effectiveness for their system under all crash geometries, we focus our attention on the crash scenario that has the highest social cost in the US: the cyclist and vehicle on parallel paths being struck from behind. Our analysis of co benefits examines the ability to reduce three measures: number of crashes, fatalities, and a comprehensive measure for social cost that incorporates morbidity and mortality. Test track simulations under realistic circumstances with a realistic surrogate bicyclist target are conducted. Empirical models are developed for system performance and potential benefits for injury and fatality reduction. These models identify three key variables in the analysis: vehicle speed, cyclist speed and cyclist age as key determinants of potential co-benefits. We find that the evaluated system offers only limited benefits for any but the oldest bicycle riders for our tested scenario

New research opportunities for roadside safety barriers improvement

Among the major topics regarding the protection of roads, restraint systems still represent a big opportunity in order to increase safety performances. When accidents happen, in fact, the infrastructure can substantially contribute to the reduction of consequences if its marginal spaces are well designed and/or effective restraint systems are installed there. Nevertheless, basic concepts and technology of road safety barriers have not significantly changed for the last two decades. The paper proposes a new approach to the study aimed to define possible enhancements of restraint safety systems performances, by using new materials and defining innovative design principles. In particular, roadside systems can be developed with regard to vehicle-barrier interaction, vehicle-oriented design (included low-mass and extremely low-mass vehicles), traffic suitability, user protection, working width reduction. In addition, thanks to sensors embedded into the barriers, it is also expected to deal with new challenges related to the guidance of automatic vehicles and I2V communication