Browsing by Subject "Rear end crashes"

Now showing 1 - 4 of 4
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    Development of Real-Time Traffic Adaptive Crash Reduction Measures for the Westbound I-94/35W Commons Section
    (University of Minnesota Center for Transportation Studies, 2008-12) Hourdos, John; Xin, Wuping; Michalopoulos, Panos
    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.
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    Enhanced Micro-Simulation Models for Accurate Safety Assessment of Traffic Management ITS Solutions
    (University of Minnesota Center for Transportation Studies, 2008-11) Xin, Wuping; Hourdos, John; Michalopoulos, Panos
    Much research has been conducted in the development, implementation, and evaluation of innovative ITS technologies aiming to improve traffic operations and driving safety. Existing micro-simulation modeling only describes normative car-following behaviors devoid of weakness and risks associated with real-life everyday driving. This research aims to develop a new behavioral car-following model that is pertinent to the true nature of everyday human driving. Unlike traditional car-following models that deliberately prohibit vehicle collisions, this new model builds upon multi-disciplinary findings explicitly taking into account perceptual thresholds, judgment errors, anisotropy of reaction times and driver inattention, in order to replicate “less-than-perfect” driving behavior with all its weakness and risks. Most importantly, all parameters of this model have direct physical meaning; this ensures vehicle collisions are replicated as a result of behavioral patterns rather than simply being numerical artifacts of the model. Meanwhile, vehicle trajectories were extracted from real-life crashes collected from a freeway section of I-94WB This is by far the first data collection efforts that aim to collect vehicle trajectories from real-life crashes to aid car-following modeling. These data were employed in this study to test, calibrate and validate the model. This new model is successful in replicating these vehicle trajectories as well as crashes.
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    Evaluation of the Smart Work Zone Speed Notification System
    (Minnesota Department of Transportation., 2019-06) Hourdos, John; Parikh, Gordon; Dirks, Peter; Lehrke, Derek; Lukashin, Pavel
    The Smart Work Zone Speed Notification (SWZSN) system aims to alleviate congestion, queuing, and rear end crashes in work zones by informing drivers of the speed of the downstream segment using a type of portable Intelligent Lane Control System (ILCS), Portable Changeable Message Signs (PCMS). The hypothesis was that drivers, knowing the speed up to 1 mile downstream, will slow down early or at least be alert and perform smoother decelerations. Video of the SWZSN was analyzed over two years of operation by the Minnesota Traffic Observatory. Overall, the system resulted in beneficial reductions of selected decelerations by the drivers. In situations where the messages communicated to the drivers were consistent and accurate, reductions of more than 30% in the selected deceleration rates were observed. Unfortunately, there were several cases where counterproductive or misleading messages were communicated to the drivers, prompting relative increases to the selected deceleration rates. The most important observation, stemming from both positive and negative influences, was that the speed notification system was noticed by drivers and resulted in a statistically significant influence on driving behavior, unlike other driver alert systems.
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    Safety Impacts of the I-35W Improvements Done Under Minnesota’s Urban Partnership Agreement (UPA) Project
    (Minnesota Department of Transportation, 2017-06) Davis, Gary A.; Gao, Jingru; Hourdos, John
    As part of an Urban Partnership Agreement project, the Minnesota Department of Transportation added lanes and began operating a priced dynamic shoulder lane (PDSL) on parts of Interstate 35W. Following the opening of these improvements, the frequency of rear-end crashes increased in certain sections, especially in the PDSL region. The object of this study was to determine if these increases were direct effects of the improvements or were due to changes in traffic conditions. Logistic regression analyses which controlled for changes in traffic conditions indicated no direct effect on the likelihood of rear-end crashes due to operation of the PDSL; the observed change in crash frequency was explained by the change in traffic conditions. This study also found evidence for a nonlinear relationship between a proxy for traffic density, lane occupancy, and the probability of a rear-end crash occurring during an hour. In several sections crashes were most likely when lane occupancies were approximately 20%–30%, and crash likelihood tended to decrease for lane occupancies below and above this range.