Browsing by Subject "Aimsun"

Now showing 1 - 3 of 3
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    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, Xiaozheng
    The 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.
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    Integration of Microsimulation and Optimized Autonomous Intersection Management
    (2018-12) Olsson, Jack
    Autonomous intersection management (AIM) is a type of intersection control for autonomous vehicles which eliminates the need for a traffic signal by using vehicle-to-infrastructure communication. Vehicles communicate information to an intersection manager which determines vehicle ordering and spacing such that vehicles can pass safely through the intersection. Reservation-based AIM, which give vehicles space-time path reservations through an intersection, has the potential to greatly increase the capacity of intersections by allowing an intersection controller to optimize all vehicle paths. A mixed-integer linear program is proposed which gives more flexibility in optimizing vehicle acceleration. This model was integrated with the microsimulation software Aimsun and scenarios were simulated which included fluctuating vehicle demands, altering vehicle speeds, and modifying spacing between vehicles. The results indicate that the model proposed in this study can reduce delay and increase average speed experienced by vehicles compared to the existing reservation-based intersection control formulations and conventional signal controls.
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    MnPASS Modeling and Pricing Algorithm Enhancement
    (Center for Transportation Studies, University of Minnesota, 2015-05) Hourdos, John; Janson, Michael; Levinson, David; Parikh, Gordon
    While High Occupancy Vehicle (HOV) lanes have been used for decades as a strategy for mitigating congestion, research has shown that they are not always effective. A 2001 study of the I-394 and I-35W HOV lanes in Minnesota found that the HOV lanes were on average underutilized, moving fewer people than the General-Purpose Lanes (GPL) even with the increased number of passengers per vehicle. To address the issue of underuse, in 2003 the Minnesota Legislature authorized the conversion of the I-394 HOV lanes into High-Occupancy Toll (HOT) lanes, named the MnPASS Express Lanes. The MnPASS lanes operate using a fully dynamic pricing schedule, where pricing is dictated by the level of congestion in the HOT lane. To better understand the nature of HOT lanes and the decisions of their users, this study explored the possibilities for a microscopic traffic simulation-based model of HOT lanes. Based on a series of field studies where the price of the toll was changed while observing changes in demand in the HOT lane, models describing the lane choice behavior of MnPASS users were developed and calibrated. These models interfaced with the traffic simulation software Aimsun through a number of extension modules and tested on the two MnPASS corridors of I-394 and I35W corridors in the west and south suburbs of Minneapolis, Minnesota. The integrated HOT simulation tool was also used to develop and test a number of alternative pricing strategies including a more efficient version of the current strategy.