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Purpose This study aims to investigate the safety effects of work zone advisory systems. The traditional system includes a dynamic message sign (DMS), whereas the advanced system includes an in-vehicle work zone warning application under the connected vehicle (CV) environment. Design/methodology/approach A comparative analysis was conducted based on the microsimulation experiments. Findings The results indicate that the CV-based warning system outperforms the DMS. From this study, the optimal distances of placing a DMS varies according to different traffic conditions. Nevertheless, negative influence of excessive distance DMS placed from the work zone would be more obvious when there is heavier traffic volume. Thus, it is recommended that the optimal distance DMS placed from the work zone should be shortened if there is a traffic congestion. It was also revealed that higher market penetration rate of CVs will lead to safer network under good traffic conditions. Research limitations/implications Because this study used only microsimulation, the results do not reflect the real-world drivers’ reactions to DMS and CV warning messages. A series of driving simulator experiments need to be conducted to capture the real driving behaviors so as to investigate the unresolved-related issues. Human machine interface needs be used to simulate the process of in-vehicle warning information delivery. The validation of the simulation model was not conducted because of the data limitation. Practical implications It suggests for the optimal DMS placement for improving the overall efficiency and safety under the CV environment. Originality/value A traffic network evaluation method considering both efficiency and safety is proposed by applying traffic simulation.

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Traffic safety has been a serious public health issue. According to the World Health Organization, annual traffic fatalities and non-fatal injuries are 1.35 million and 20 to 50 million, respectively, worldwide. Vehicle crashes, in particular, are the leading cause of the death of children in the world. This study aims to analyze the injury severity level of drivers and school-age passengers and to identify contributing factors, focusing on the effects of driver characteristics on the severity of injuries to the driver and child passenger. A bivariate model is adopted to capture unobserved shared factors between the driver’s and child’s injury severity levels. The results indicate that the factors contributing to the injury severity level of drivers and school-age passengers are quite different, and some driver characteristics significantly affect the injury severity of the child passenger. The findings from this study can contribute to an efficient strategic plan to reduce the injury severity of vehicle occupants.

This study investigates contributing factors to traffic violations by seriousness. The traffic violations are divided into four categories by seriousness (unintentional violation, minor violation, serious violation, and crash with violation). The results of the random parameter multinomial logit model indicate that various factors potentially affect the severity of traffic violations. The key findings include the following: (1) female drivers are more likely to commit minor violations; (2) drivers from an area with a longer travel time to work and a higher proportion of driving to work are more likely to have minor violations and serious violations, while those from the high-income area are less likely; (3) drivers are more likely to be associated with a more minor infraction during the afternoon peak (4 p.m.–6 p.m.). The results from this study are expected to be beneficial for policymakers and traffic police to comprehend the factors affecting violations and implement effective strategies to minimize the number and seriousness of traffic violations.

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There have been efforts to restrict older trucks in many jurisdictions all over the world. The primary goal of the restrictions is to minimize greenhouse gas emissions. In addition to the environmental benefits, it is also possible that the truck age restriction could contribute to the enhancement of traffic safety. Older trucks are subject to longer travel-miles than newer trucks and tend to have higher mechanical failure rates. Extremely few studies have been done to explore the impact of trucks’ age on their crash occurrence due to mechanical problems. This study aims to investigate the association between the truck crashes due to mechanical issues and the truck age. Two approaches are adopted to achieve the objective. First, a chi-square test reveals that the proportions of the mechanical failures among older trucks are higher than those among newer ones ( χ 2  = 256.199, p < 0.0001 ). Second, the modeling results indicate that the number of truck crashes due to mechanical failures is significantly increased by the truck age. The findings suggest that policies restricting older trucks should consider not only environmental effects but also traffic safety benefits.