A Comprehensive Analysis of Multi-Vehicle Crashes on Expressways: A Double Hurdle Approach

Abstract

To maintain safe expressways, it is necessary to investigate the causes of severe traffic accidents and establish a strategy. This study aims to analyze crashes and identify the influence of crash-risk factors on multi-vehicle (MV) crashes. Crashes involving three types of vehicles namely passenger cars, buses, and freight trucks were analyzed using a seven-year data spanning 2011 to 2017 which consists of crashes that occurred on expressways in South Korea. We applied a double hurdle approach in which a model consists of two estimators: The first estimation, which is a binary logit model selects MV crashes from the dataset; and the second estimation which is a truncated regression model estimates the number of vehicles involved in the MV crash. We found that driver traffic violations such as the improper distance between vehicles, reversing and passing increases the probability of MV crashes occurring. MV crashes in tunnels and mainlines were found to be positively correlated with the number of vehicles involved in the crash, whereas fewer vehicles were involved in MV crashes at ramps and toll-booths. Further, we found that the hurdle model with an exponential form of conditional mean of the latent variable provides better estimation parameters.

Discovering Insightful Rules among Truck Crash Characteristics using Apriori Algorithm

“…As the mainline segment of expressways is always busy, drivers of heavy trucks who overspeed on rainy days are highly likely to have single-vehicle crashes. is observation is consistent with previous research on truck safety [18,35].…”

“…As illustrated in previous rules, the high frequency of antecedents like {Segment: TG}, {Cause: vehicle-facility}, {Cause: negligence}, and {Number of vehicles: single} shows that many of these crashes are likely to be SV crashes at the toll gate section, which is as a result of the features of the Gyeongbu expressway line. According to Hong et al [35], many SV truck-involved crashes are expected to occur at toll gate sections, reflecting the results of our study. us, decision-makers and planners should pay more attention when designing toll gate sections to accommodate the heavy trucks better.…”

“…Level B shows severe injury (represents all crashes where 1 < number of deaths ≤ 3, 5 < injured persons ≤ 20 or 2.5 million KRW < property damage cost ≤ 1 billion KRW). Level C stands for evident injury (1 < injured persons ≤ 5 or 300 thousand won < property damage cost ≤ 2.5 million KRW), and Level D denotes property damage only (PDO) (damage cost ≤ 300 thousand KRW) [35].…”

“…e Gyeongbu line is the longest expressway line in South Korea with a speed limit of 100-110 km/h. Due to its importance, it currently stands as the most used line with an annual average daily traffic (AADT) of 1,335,770 [35]. It also has the highest number of toll booths compared to all the other expressway lines in South Korea.…”

Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network

“…It is clear that as the number of vehicles involved increases, there is a greater probability of a crash, resulting in a fatality. Earlier studies also suggest that multi-vehicle collisions are usually more prone to severe crashes [ 95 , 98 , 99 ].…”