Developing and Simulating a Communication Plan for Mitigation of Secondary Crashes: Leveraging Connected Vehicle Technologies

The Federal Highway Administration (FHWA) has identified secondary crashes (SCs) on United States (US) highways as one of the core transportation issues that needs to be addressed. These crashes contribute to increased property damage, injuries, and fatalities and a decline in traffic flow conditions on freeways and adjacent arterials. The purpose of this study was to 1) propose a communication plan that leverages connected vehicle (CV) technologies to increase awareness to road users to target the mitigation of SCs, and 2) to evaluate the potential benefits of the proposed communication plan with CV technologies in alleviating SCs. This study used VISSIM microscopic software to model a freeway road segment on Florida’s Turnpike system and Lyons Road, a parallel arterial. The software was used to replicate the proposed communication plan and CV applications to issue advisories, such as speed, lane-change, or detour advisory to drivers during an incident. A safety evaluation was performed using the Surrogate Safety Assessment Model (SSAM) software by importing trajectory files from VISSIM to analyze generated traffic conflicts. The change in the number of simulated conflicts was used to evaluate the mitigation of SCs. The results showed significant safety benefits using the proposed communication plan with CV technologies. A conflict reduction of up to 98% was observed with full penetration of CVs at low traffic volume. Statistical analysis indicated that different penetration rates of CVs were required to achieve significant safety benefits depending on the analyzed scenario, i.e., traffic volume, number of lanes closed, side of the road the lane is closed, and dissemination of detour advisory

Are older drivers safe on interchanges? Analyzing driving errors causing crashes

Older drivers are prone to driving errors that can lead to crashes. The risk of older drivers making errors increases in locations with complex roadway features and higher traffic conflicts. Interchanges are freeway locations with more driving challenges than other basic segments. Because of the growing population of older drivers, it is vital to understand driving errors that can lead to crashes on interchanges. This knowledge can assist in developing countermeasures that will ensure safety for all road users when navigating through interchanges. The goal of this study was to determine driver, environmental, roadway, and traffic characteristics that influence older drivers’ errors resulting in crashes along interchanges. The analysis was based on three years (2016–2018) of crash data from Florida. A two-step approach involving a latent class clustering analysis and the penalized logistic regression was used to investigate factors that influence driving errors made by older drivers on interchanges. This approach accounted for heterogeneity that exists in the crash data and enhanced the identification of contributing factors. The results revealed patterns that are not obvious without a two-step approach, including variables that were not significant in all crashes, but were significant in specific clusters. These factors included driver gender and interchange type. Results also showed that all other factors, including distracted driving, lighting condition, area type, speed limit, time of day, and horizontal alignment, were significant in all crashes and few specific clusters