University of Minnesota Center for Transportation Studies
Much research has been conducted in the development, implementation, and evaluation of innovative ITS technologies aiming to improve traffic operations and driving safety. An earlier project succeeded in supporting the hypothesis that certain traffic conditions are favorable to crashes and in developing real-time algorithms for the estimation of crash probability from detector measurements. Following this accomplishment a natural question is “how can this help prevent crashes?” This project has the ambitious plan of not only answering this question but also providing a multifaceted approach that can offer different types of solutions to an agency aimed at reducing crashes in this and other similar locations. This project has two major objectives; first it aimed at utilizing a cutting edge 3D virtual reality system to design and visualize different driver warning systems specifically for the I-94 westbound high crash location in Minneapolis, MN. Second, in view of the desire of local engineers for a more traditional approach, this project explored the use of existing micro-simulation models in the evaluation of safety improvements for the aforementioned high crash area. This report describes the results of these investigations but more importantly describes the lessons learned in the process of the research. These lessons are important because they highlight gaps of technology and knowledge that hampered this and other research projects with similar objectives.
Hourdos, John; Xin, Wuping; Michalopoulos, Panos.
Development of Real-Time Traffic Adaptive Crash Reduction Measures for the Westbound I-94/35W Commons Section.
University of Minnesota Center for Transportation Studies.
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