Browsing by Author "He, Xiaozheng"
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Item Development of the Next Generation Metro-Wide Simulation Models for the Twin Cities' Metropolitan Area: Mesoscopic Modeling(2011-01) Liu, Henry X.; Danczyk, Adam; He, XiaozhengThe collapse of the Interstate 35W Bridge over the Mississippi River in Minneapolis resulted in unexpected loss of life and had serious consequences on mobility and accessibility in the Twin Cities metropolitan area. In response to the network disruption caused by the bridge collapse, a number of traffic restoration projects were proposed and rapidly implemented by MnDOT. Selection and prioritization of these projects, however, was based mainly on engineering judgment and experience. The only decision-support tool available to traffic engineers was the regional transportation planning model, which is static in nature and decennial. In this work, the Twin Cities metropolitan area is simulated using a mesoscopic traffic simulator in the AIMSUN software. After establishing the mesoscopic simulation model, we attempt to utilize the calibrated mesoscopic simulation model to evaluate drivers’ perceived cost evolution to explain the traffic dynamics on the Twin Cities road network after the unexpected collapse of the I-35W Bridge over the Mississippi River. Given the observation of largely underutilized sections of network, it is proposed that the tragedy generated a perceived travel cost to discourage commuters from using these sections. Applying a mesoscopic simulation model provided by AIMSUN, the perceived costs on cordon lines after the I-35W Bridge collapse were suggested to be best described as an exponential decay cost curve. The proposed model is applicable to both practitioners and researchers in traffic-related fields by providing an understanding of how traffic dynamics will evolve after a long-term, unexpected network disruption.Item Modeling the traffic flow evolution process after a network disruption.(2010-12) He, XiaozhengMajor disruption to a transportation network can disturb traffic flow patterns significantly. To deploy effective and efficient traffic restoration projects, a good prediction of the traffic flow pattern under network disruption is vital. Although traffic flow evolution processes have been modeled in various ways in the literature, very limited attention has been paid to the traffic flow evolution process after an unexpected network disruption. In fact, due to the lack of data, none of the existing day-to-day traffic assignment models have been compared against reality, and thus their quality has not yet been verified. There clearly exists a gap between day-to-day traffic flow evolution modeling and their practical applications, especially under network disruption scenarios that are of great interest to traffic management authorities. This doctoral research is dedicated to bridging that gap by developing and validating innovative new models for deterministic day-to-day traffic assignment problem. The first innovation is the development of a link-based traffic dynamic model for studying traffic evolution. Existing deterministic day-to-day traffic assignment models were all built upon path flow variables. Most path-based models, however, suffer two essential shortcomings. One is that their application requires a given initial path flow pattern, which is typically unidentifiable, i.e., mathematically nonunique and practically unobservable. In addition, different initial path flow patterns constituting the same link flow pattern generally gives different day-to-day link flow evolutions. The second shortcoming is the path overlapping problem, whereby the interdependence of paths is ignored, leading to unreasonable results for networks with overlapping paths. The proposed link-based day-to-day traffic dynamic model avoids the two shortcomings, and captures travelers' cost-minimization behavior in their path finding as well as their inertia. The stable point of the link-based dynamical system is rigorously proven to be the classic Wardrop user equilibrium. Its asymptotic stability is guaranteed under mild conditions. Our second innovation is the establishment of a "prediction-correction" framework for modeling traffic evolution after an unexpected network disruption. By studying actual behavioral changes of drivers after the collapse of the I-35W Mississippi River Bridge in Minneapolis, we found that most existing day-to-day traffic assignment models would not be suitable for modeling traffic evolution under network disruption, because they assume that drivers' travel cost perception depends solely on their experience from previous days. They do not recognize that, when a significant network change occurs unexpectedly, travelers' past experience on a traffic network may not be entirely useful if the disturbance to traffic patterns is extensive. To remedy this, this research proposes a "prediction-correction" model to describe the traffic equilibration process, in which travelers predict traffic patterns after network changes and gradually correct their predictions according to their new travel experience. We also prove rigorously that, under mild assumptions, the proposed "prediction-correction" process has the Wardrop user equilibrium flow pattern as a globally attractive point. Most importantly, this doctoral research verifies the proposed models against a real network disruption scenario. The proposed models are calibrated and validated with field data collected after the collapse of the I-35W Bridge. This study bridges the gap between theoretical modeling and practical applications of day-to-day traffic equilibration approaches and promotes a further understanding of traffic equilibration processes after an unexpected network disruption.Item Travel Impacts and Adjustment Strategies of the Collapse and the Reopening of the I-35W Bridge(Springer, 2011) Zhu, Shanjiang; Tilahun, Nebiyou J; Levinson, David M; He, XiaozhengMajor network disruptions have significant impacts on local travelers. Understanding the behavioral reactions to such incidents is crucial for traffic management and planning. This study investigates travelers' reaction to both the collapse and reopening of the I-35W Mississippi River Bridge in Minneapolis, Minnesota. Web-based surveys conducted at residences in several communities across the metropolitan area supplement hand-out/mail-back paper-based surveys distributed to workers in areas around the bridge collapse (downtown Minneapolis and the University of Minnesota). Findings from the four surveys highlight differences in travel impacts and behavioral reactions after the unplanned bridge collapse and the planned bridge reopening.