Enhanced Micro-Simulation Models for Accurate Safety Assessment of Traffic Management ITS Solutions
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Enhanced Micro-Simulation Models for Accurate Safety Assessment of Traffic Management ITS Solutions
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2008-11
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University of Minnesota Center for Transportation Studies
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Report
Abstract
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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Xin, Wuping; Hourdos, John; Michalopoulos, Panos. (2008). Enhanced Micro-Simulation Models for Accurate Safety Assessment of Traffic Management ITS Solutions. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/96707.
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