Soyoung Jung

Evaluation of motorcycle safety strategies using the severity of injuries

The growth of motorcycle fatalities in California has been especially prominent, specifically with regard to the 24 and under age group and those aged 45-54. This research quantitatively examined factors associated with motorcyclist fatalities and assessed strategies that could improve motorcyclist safety, specifically focusing on the two age groups mentioned above. Severity of injury was estimated separately for both age groups with multinomial logit models and pseudo-elasticity using motorcycle-related collision data that was collected between 2005 and 2009. The results were compared with motorcyclists aged 35-44, a group that shows a consistent trend of fatalities. This research found that lack or improper use of helmets, victim ejection, alcohol/drug effects, collisions (head-on, broadside, hit-object), and truck involvement were more likely to result in fatal injuries regardless of age group. Weekend and non-peak hour activity was found to have a strong effect in both the younger and older age groups. Two factors, movement of running off the road preceding a collision and multi-vehicle involvement, were found to be statistically significant factors in increasing older motorcyclist fatalities. Use of street lights in the dark was found to decrease the probability of severe injury for older motorcyclists. Driver type of victim, at-fault driver, local road, and speed violation were significant factors in increasing the fatalities of younger motorcyclists. Road conditions and collision location factors were not found to be statistically significant to motorcyclist fatalities. Based on the statistically significant factors identified in this research, the following safety strategies appear to be effective methods of reducing motorcyclist fatalities: public education of alcohol use, promoting helmet use, enforcing heavy vehicle and speed violations, improving roadway facilities, clearer roadway guidance and street lighting systems, and motorcyclist training.

Evaluating the effects of supplemental rest areas on freeway crashes caused by drowsy driving

To prevent crashes caused by drowsy driving, supplemental rest areas have been installed in the South Korean freeway system to allow road users to rest. These supplemental rest areas are very small-sized resting facilities located between the larger regular rest areas, which is a unique design. This study aimed to evaluate the effects of the supplemental rest areas on reducing crashes caused by drowsy driving. Between 2011 and 2012, supplemental rest areas were first installed in the Gyeongbu Freeway, which was selected as the study area for this study. The first 160km and 178km stretches of the southbound and northbound lanes, respectively, of the Gyeongbu Freeway were considered the reference areas. For both the southbound and northbound lanes, the downstream stretch of the Gyeongbu Freeway was considered the treatment area where the supplemental rest areas were installed. Based on a negative binomial regression of the crashes estimated in the reference and treatment areas, an empirical Bayes approach was employed to quantitatively validate the effects of the supplemental rest areas on reducing crashes caused by drowsy driving. The results showed that the supplemental rest areas reduced freeway crashes caused by drowsy driving by 14%. The supplemental rest areas were most effective in reducing drowsy driving related crashes particularly in freeway sections with 2 or 3 travel lanes or with ramps. As the first data-driven study evaluating the effects of these supplemental rest areas, the results imply that supplemental rest areas provide more opportunities to avoid drowsy driving, and, therefore they should be encouraged for freeways as cost-effective safety improvement facilities.

Systemwide Impacts of Emergency Medical Services Resources on Freeway Crash Severity

The objective of a study was to examine the systemwide effects of prehospital emergency medical services (EMS) resources quantitatively on crash outcomes throughout the entire South Korean freeway system. Latent class cluster and binomial probit regression models were combined to achieve this objective. In the cluster-based binomial probit regression, surrogate measures for prehospital EMS resources were obtained by combining medical service portals, freeway heliport maps, and freeway network log data in the crash data set. As a result, eight latent class clusters of crashes were determined on the basis of features associated with EMS resources, province, roadway, and traffic conditions at the scene of the crash. On-scene and recovery times were commonly significant in increasing the probability of fatal crashes in both entire groups and in each group of crashes, while the nearest ramp location and number of nearby EMS facilities significantly affected fatal crashes for a certain group of crashes. The findings provide meaningful insights that can enhance EMS training programs for initial medical aid and postcrash traffic management on all provincial freeways. Supplemental nearby EMS facilities and access points to them are needed particularly in South Korea’s southeastern and central province freeway sections, respectively. This research is the first data-driven study to assess systemwide EMS resources for the entire South Korean freeway system by using multiple data sources. It would contribute to informed decision making for future EMS provision.