• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.1-17
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• 2018

Over the past five years (2010-2014), the total number of traffic accidents has decreased from 226,878 to 223,552 with decrease of 0.37 percent each year. The death toll has also decreased from 5,505 to 4,762. However, the number of rental car accidents and fatalities has been steadily increased. Despite of its growth, no previous study has been conducted on rental car accident severity. This study analyzed data of 18,050 rental car accidents in South Korea collected from 2010 to 2014 and then processed in order to identify which factors could affect the accident severity. Seventeen factors related to rental car accident severity were grouped into four categories: driver, vehicle, roadways and environment. As a result of the ordered probit model analysis, fourteen variables excluding age, intersection, and day of week were found to affect the severity of rental car accidents. The results of the study summarized as follows. First of all, violation of traffic regulations such as speeding increase the severity of rental car accidents. Secondly, rental accident severity is higher at curved sections of complicated roadway, which the driver's field of view is impaired. The results of this study can be used to reduce the severity of rental car accidents in transportation safety.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.105-115
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• 2017

Each year, a number of tourists visit Jeju Island, a popular tourist destination in the Republic of Korea. A large portion of the tourists (about 61%) use a rental car as a means of transportation. With this reason, the number of rental cars registered in Jeju was 15,517 in 2011, while the total number of the rental car has rapidly increased to 26,338 in 2015. For the same period, the number of rental car involved traffic accidents has been doubled. Thus, this study aims to analyze the rental car accidents' characteristics, clarifying primary factors related to rental car accidents in Jeju Island. To do this, 918 rental car accidents and 4,201 non-commercial passenger car accidents that occurred in Jeju island over the two years (2014-2015) were compared, using statistical methods such as chi-square test and z-test. The results show that the characteristics of rental car involved accidents are different from those caused by the passenger cars. Most of the rental car accidents in Jeju were caused by young drivers and drivers who had just obtained their driver's licenses. This study finds that driver immaturity, unfamiliar geography, and driving an unfamiliar vehicle are the main causes of the rental car accidents. Statistical analysis confirms that the characteristics of these accidents appeared significantly different from the passenger cars in terms of human and environmental factors. On the other hand, there is no clear evidence that vehicle-related characteristics are different between rental car and non-commercial passenger car accidents. The implications on transportation safety analysis and effective solutions to prevent rental car traffic accidents are discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.1-12
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• 2017

Traffic accidents are caused by a combination of human factors, vehicle factors, and environmental factors. In the case of traffic accidents where rental cars are involved, the possibility and the severity of traffic accidents are expected to be different from those of other traffic accidents due to the unfamiliar environment of the driver. In this study, we developed a model to forecast the severity of rental car accidents by using Naive Bayes classifier for Busan, Gangneung, and Jeju city. In addition, we compared the prediction accuracy performance of two models where one model uses the variables of which statistical significance were verified in a prior study and another model uses the entire available variables. As a result of the comparison, it is shown that the prediction accuracy is higher when using the variables with statistical significance.

• Transportation Technology and Policy
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• v.9 no.3
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• pp.19-31
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• 2012