Complementary parametric probit regression and nonparametric classi?cation tree modeling approaches to analyze factors affecting severity of work zone weather-related crashes

Identifying risk factors for road traffic injuries can be considered one of the main priorities of transportation agencies. More than 12,000 fatal work zone crashes were reported between 2000 and 2013. Despite recent efforts to improve work zone safety, the frequency and severity of work zone crashes are still a big concern for transportation agencies. Although many studies have been conducted on different work zone safety-related issues, there is a lack of studies that investigate the effect of adverse weather conditions on work zone crash severity. This paper utilizes probit–classification tree, a relatively recent and promising combination of machine learning technique and conventional parametric model, to identify factors affecting work zone crash severity in adverse weather conditions using 8 years of work zone weatherrelated crashes (2006–2013) in Washington State. The key strength of this technique lies in its capability to alleviate the shortcomings of both parametric and nonparametric models. The results showed that both presence of traffic control device and lighting conditions are significant interacting variables in the developed complementary crash severity model for work zone weather-related crashes. Therefore, transportation agencies and contractors need to invest more in lighting equipment and better traffic control strategies at work zones, specifically during adverse weather conditions.

Performance evaluation framework of Wyoming connected vehicle pilot deployment program: summary of Phase 2 pre-deployment efforts and lessons learned

Purpose–This paper aims to present a summary of the performance measurement and evaluation plan of the Wyoming connected vehicle(CV)Pilot Deployment Program(WYDOT Pilot).Design/methodology/approach–This paper identified 21 specific performance measures as well as approaches to measure the benefits of the WYDOT Pilot.An overview of the expected challenges that might introduce confounding factors to the evaluation effort was outlined in the performance management plan to guide the collection of system performance data.Findings–This paper presented the data collection approaches and analytical methods that have been established for the real-life deployment of the WYDOT CV applications.Five methodologies for assessing 21 specific performance measures contained within eight performance categories for the operational and safety-related aspects.Analyses were conducted on data collected during the baseline period,and pre-deployment conditions were established for 1 performance measures.Additionally,microsimulation modeling was recommended to aid in evaluating the mobility and safety benefits of the WYDOT CV system,particularly when evaluating system performance under various CV penetration rates and/or CV strategies.Practical implications–The proposed performance evaluation framework can guide other researchers and practitioners identifying the best performance measures and evaluation methodologies when conducting similar research activities.Originality/value–To the best of the authors’knowledge,this is thefirst research that develops performance measures and evaluation plan for low-volume rural freeway CV system under adverse weather conditions.This paper raised some early insights into how CV technology might achieve the goal of improving safety and mobility and has the potential to guide similar research activities conducted by other agencies.