Analysis of The Effectiveness of Queue Warning Systems in Freeway Work Zones

Abstract

Work zone safety and mobility have always been a major concern for state DOTs and transportation professionals. While roadway usage has increased substantially in recent years as the U.S. population and number of licensed drivers have grown, the capacity of the highway system has grown very slowly. Increased roadway usage has led to deteriorating quality of road infrastructure, posing a potential risk to the traveling public. Work zones are necessary components to maintain and improve the quality of the highway infrastructure. However, the presence of work zones disrupts mobility and presents motorists with unforeseen challenges and conditions, increasing the risk of vehicular crashes and traffic delays within and near work zones. Rear-end crashes were identified as the predominant crash types in freeway work zones. To minimize the impacts of work zones on safety and mobility, Intelligent Transportation Systems (ITS) technologies are being utilized to fill in the gaps of current practices. Queue Warning Systems (QWS), as an example of ITS technology in work zones, which employs queue detection systems and communication technologies, provide an opportunity to address traffic safety and mobility associated issues in work zones through queue detection and warning systems. A proper queue warning system is designed to detect traffic conditions in the work zone, such as the presence of queues or accidents, and notify motorists of slow traffic or queues ahead so that they can react in time to the upcoming traffic conditions. Currently, the application of this technology is still in its early stages in Alabama. The purpose of this study is to analyze the effectiveness of the QWS in a freeway work zone through the evaluation of the impact on traffic safety of QWS and the development of traffic simulation models to estimate the traffic effects of QWS. From the results of the safety performance evaluation, a site-specific crash modification factor specific (CMF) for QWS deployment was developed to be 1.49, and combined with the crash reduction analysis, it was found that specific in this study, the percentage of increased rear-end and sideswipe associated crashes at the control site (without QWS) is lower than that at the treatment site (with QWS). However, these findings were from a very limited study that only included one treatment and one control site making the transferability to other deployments is limited until further study with more sites can be performed. In addition, traffic simulation models were developed and successfully validated to replicate field-observed traffic operations within the work zone area. The methodology presented in this study for the development of the site-specific crash modification factor related to the QWS deployment in freeway work zones when true control conditions could not be evaluated, and for the VISSIM model development, calibration and validation can be applicable to other state highway agencies and practitioners.