According to the National Highway Traffic Safety Administration (NHTSA) Fatality Analysis Reporting System database, approximately 360 fatalities occur every year due to wrong-way driving (WWD) crashes on controlled-access highways (1). WWD crashes occur when a motorist either inadvertently or deliberately drives in the opposite direction of travel on a divided roadway. Even though WWD crashes are infrequent, they remain a serious problem because the resulting crashes often result in fatalities or serious injury to the persons involved. Since the mid-1960s, agencies around the country have deployed combinations of traffic control devices (e.g., DO NOT ENTER and WRONG WAY signs, pavement markings, and directional route markers) to prevent drivers from entering freeway facilities in the wrong direction. More recently, agencies have leveraged traditional intelligent transportation system (ITS) infrastructure (e.g., cameras, radar, or loop detectors) to detect wrong-way drivers and notify traffic management centers (TMCs). However, most of these systems lack the ability to provide specific vehicle location information and real-time warnings to right-way drivers. In addition, the process still relies on manual inputs from operators and traditional methods of information exchange between TMC and law enforcement personnel. Connected vehicles (CVs) and their integration with transportation infrastructure provide new approaches to WWD detection, warning, verification, and intervention that will help practitioners further reduce the occurrence and severity of WWD crashes. The goal of this project was to develop a concept of operations, functional requirements, and high-level system design for a Connected Vehicle WWD Detection and Management System. This system will detect wrong-way vehicles, notify the Texas Department of Transportation (TxDOT) and law enforcement personnel, and alert affected travellers. For this project, the system boundaries were identified as high-speed, controlled-access, freeway-type facilities. These included the main lanes of TxDOT freeways and major toll facilities, as well as their entrance and exit ramps. System boundaries do not include frontage roads, cross-street approaches of frontage road intersections or the intersection itself, or urban roadways operated by municipalities. The system was also not designed for multi-lane, divided highways without access control. Chapter 2 documents the state of the practice regarding ITS and CV technologies being applied as WWD countermeasures. Chapter 3 contains information about the WWD crash trends in Texas from 2010 to 2014. Chapter 4 details the user needs associated with a CV WWD Detection and Management System, and Chapter 5 documents the concept of operations for such a system. Chapter 6 and the appendix detail the development of the system’s functional requirements. Chapter 7 explores the need for emergency service provider integration and preliminary connectivity concepts for emergency service providers. Chapter 8 contains the high-level system design. Chapter 9 documents the findings from one-on-one surveys to assess motorist understanding of wrong-way driver warning messages that were designed to be displayed on dynamic message signs (DMSs). Chapter 9 also contains information on the use of roadside alert (RSA) messages to provide warning to CVs about approaching wrong-way drivers. Chapter 10 summarizes all research tasks and provides recommendations for the next steps toward the implementation of a CV WWD Detection and Management System in Texas. (Author/publisher)
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