Connecting tradition with modernity: Safety literature review

Road safety has long been considered as one of the most important issues.Numerous studies have been conducted to investigate crashes with significant progress,whereas most of the work concentrates on the lifespan period of roadways and safety influencing factors.This paper undertakes a systematic literature review from the crash procedure to identify the state-of-the-art knowledge,advantages and disadvantages of crash risk,crash prediction,crash prevention and safety of connected and autonomous vehicles(CAVs).As a result of this literature review,substantive issues in general,data source and modeling selection are discussed,and the outcome of this study aims to provide the summary of crash knowledge with potential insight into both traditional and emerging aspects,and guide the future research direction in safety.

Test a Queue Detection System for Special Events in Nevada

Queue detection systems have been used in traffic management in work zones and have also been recommended for traffic control for special events like sports and conventions. However, they have not been tested in the field. This paper presents the results of tests for a queue detection system at two special events in Las Vegas, Nevada. The system consisted of two vision detectors, radio frequency communications and one changeable message sign. Two aspects of the system were evaluated: the effectiveness of the system in reducing speeds and the cost and effectiveness of its deployment. In the tests, traffic data such as queue length and vehicle operating speeds were collected and analyzed to see whether motorists respond congestion related message on the changeable message sign when they did not perceive the congestion. By this approach, the motorists’ true responses to the system were identified. The results indicated that motorists did make positive responses to the messages provided by the system. However, it was found that the system may not be cost-effective because significant costs would be incurred in purchasing, installation and maintenance of the system. Recommendations were provided to utilize existing message signs and detectors to provide the same information to motorists as a queue detection system does.

Inaugural Editorial:Digital Transportation and Safety

Transportation is essential to human life and a significant component of a modern economy and societal development.Since its first emergence approximately 5,000 years ago,transportation has experienced evolutionary changes from ancient horse-pulled wagons and dog-pulled sleds to modern airplane and high-speed trains,to future supersonic jets and space shuttles.Since the late 20th century,intelligent transportation systems(ITS)have been developed for improving transportation efficiency,alleviating traffic congestion,increasing roadway,air and sea transportation capacity,reducing energy consumption,and mitigating environmental pollution.

Investigating safety and liability of autonomous vehicles:Bayesian random parameter ordered probit model analysis

Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Design/methodology/approach–The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations.The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs,respectively,as well as accommodating the heterogeneity issue simultaneously.Findings–The findings show that day,location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.Originality/value–The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.

Exploring traffic safety climate with driving condition and driving behaviour:a random parameter structural equation model approach

This study aimed to explore traffic safety climate by quantifying driving conditions and driving behaviour.To achieve the objective,the random parameter structural equation model was proposed so that driver action and driving condition can address the safety climate by integrating crash features,vehicle profiles,roadway conditions and environment conditions.The geo-localized crash open data of Las Vegas metropolitan area were collected from 2014 to 2016,including 27 arterials with 16827 injury samples.By quantifying the driving conditions and driving actions,the random parameter structural equation model was built up with measurement variables and latent variables.Results revealed that the random parameter structural equation model can address traffic safety climate quantitatively,while driving conditions and driving actions were quantified and reflected by vehicles,road environment and crash features correspondingly.The findings provide potential insights for practitioners and policy makers to improve the driving environment and traffic safety culture.