Design, Specification, Implementation and Evaluation of a Real-Time Queue Warning Syste

The formation and propagation of queues on urban freeways is an unavoidable result of the ever-increasing traffic demand. Traffic queues increase on-road congestions and reduce roadway network efficiency. More importantly, some of these queues can cause serious rear-end collisions, resulting in property damages and injuries. This thesis presents the design, specification, implementation and evaluation of an infrastructure based Queue Warning system (QWarn) that is capable of detecting dangerous traffic conditions, i.e. crash-prone conditions, on freeways and delivering warning messages to drivers, in order to increase their alertness and ultimately reduce the frequency of crashes. This effort approaches the topic from the quantification of traffic flow to the multi-layer system design along with different methodologies including the traffic assessment modeling and the development of control algorithms. This study utilizes measurements of individual vehicle speeds and time headways at two fixed locations on the freeway mainline, as the major type of data for the system's operation. This thesis focuses on a case study and evaluation of the proposed system implemented on a high crash frequency freeway section. The Queue Warning system was implemented at the right lane of a 1.7-mile-long freeway segment of Interstate 94 Westbound near downtown Minneapolis where the event frequency prior to the systems installation was 212.25 conflict events per million vehicles traveled. Machine Vision Detectors (MVD) are installed on a nearby rooftop capturing the Real-Time vehicle data. The data were delivered over the Minnesota Traffic Observatory's (MTO) communication network to a server running the main control algorithm. The control algorithm assesses the dangerousness of the given traffic condition and responds with a warning result based on a multi-metrics traffic evaluation model and complex control reasoning that ensures consistency and accuracy. The system translates the warning result into readable messages and delivers them to the two sets of signs located upstream of the detection zone. A three-month investigation of the operations of the QWarn system shown a reduction in conflict event frequency to 135.79 per million vehicle traveled. In conclusion, this thesis proposed the framework as well as details of a Queue Warning system is also evaluated the methodology by implementing a working prototype that delivers warning messages to road users on an urban freeway segment. The result shows a decrease of conflict event frequency and proves the feasibility of the proposed methodology.