Browsing by Subject "Ramp metering"
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Item Development of Active Traffic Management Strategies for Minnesota Freeway Corridors(Minnesota Department of Transportation, 2015-06) Kwon, Eil; Park, ChongmyungIn this study, the effectiveness of the I-35W variable advisory speed limit system on the improvement of the traffic flow was evaluated with the real traffic data. The analysis results indicate there was significant reduction in the average maximum deceleration and also the traffic time reliability was substantially improved during a peak hour period. Based on the assessment results, an enhanced version was developed to be able to reflect more effectively the time-variant road traffic conditions in determining the variable speed limits in real time. The coordinated adaptive metering strategy, developed in the previous phase of this research, is also enhanced and implemented in the field in this research. The field test results of the new metering system with the 100 NB corridor indicate substantial improvements in both the mainline and ramp traffic performance compared with those from the old stratified algorithm.Item Development of Freeway Operational Strategies with IRIS-in-Loop Simulation(Minnesota Department of Transportation, 2012-01) Kwon, Eil; Park, ChongmyungThis research produced several important tools that are essential in managing and operating freeway corridors. First, a computer-based off-line process was developed to automatically estimate a set of traffic measures for a given freeway corridor using the historical detector data. Secondly, a prototype on-line estimation procedure was designed to calculate selected traffic measures in real time to assist operators in identifying abnormal traffic patterns. Third, the IRIS-in-loop simulation system was developed by linking IRIS, the freeway control system developed by MnDOT, to a microscopic simulation software through a data communication module, so that new operational strategies can be directly coded into IRIS and evaluated under the realistic simulation environment. Finally, two new freeway operational strategies, variable speed limit control and a density-based adaptive ramp metering strategy, were developed and evaluated with the IRSI-in-Loop simulation system.Item Development of the Next Generation Stratified Ramp Metering Algorithm Based on Freeway Density(Center for Transportation Studies, 2011-03) Geroliminis, Nikolas; Srivastava, Anupam; Michalopoulos, PanosA new coordinated, traffic-responsive ramp metering algorithm has been designed for Minnesota’s freeways based on density measurements, rather than flows. This is motivated in view of recent research indicating that the critical value of density at which capacity is observed is less sensitive and more stable than the value of capacity, thereby resulting in m ore effective control. Firstly, we develop a methodology to estimate densities with space and time based on data from loop detectors. The methodology is based on solving a flow conservation differential equation (using LWR theory) with intermediate (internal) freeway mainline boundaries, which is fast er and more accurate from previous resear ch using only external boundaries. To capture the capacity drop phenomenon into the first-order model we utilize a fundamental diagram with two values of capacity and we provide a memory-based methodology to choose the appropriate value in the numerical solution of the problem. Secondly, with respect to ramp metering, the main goals of the algorithm are to delay the onset of the breakdown and to accelerate system recovery when ramp metering is unable due to the violation of maximum allowable ramp waiting time. The effectiveness of the new control strategy is being assessed by comparison with the currently deployed version of the Stratified Zone Algorithm (SZM) through microscopic simulation of a real 12-mile, 17 ramp freeway section. Simulations show a decrease in the delays of mainline and ramp traffic, an improvement 8% in the overall delays and avoidance of the maximum ramp delay violations.Item Dynamic Estimation of Origin-Destination Patterns in Freeways(Minnesota Department of Transportation, 1994-05) Davis, Gary A.Any proposed traffic management action is essentially a forecast that the action will result in certain traffic conditions, but uncertainty concerning the amount and distribution of traffic demand will introduce random error between what is expected and what actually occurs. This report treats the problem of forecasting whether or not a given set of freeway on-ramp volumes are likely to cause over-capacity demand at some point in the freeway mainline. The main source of uncertainty in these forecasts concerns the freeway's origin-destination matrix, and four different methods for estimating this matrix from loop detector data are evaluated using Monte Carlo simulation. Only the method which explicitly modeled freeway traffic flow produced reasonably unbiased and efficient estimates, and it was concluded that successful estimation must be coupled with a good model of freeway traffic flow.Item Employment of the Traffic Management Lab for the Evaluation and Improvement of Stratified Metering Algorithm - Phase III(Minnesota Department of Transportation, Research Services Section, 2007-05) Liu, Henry; Wu, Xinkai; Michalopoulos, Panos; Hourdos, JohnThe evaluation results (done in Phase II) demonstrated that the SZM strategy was generally beneficial. However, they also revealed that freeway performance degraded by reducing the ramp delays. Therefore, it is desired to improve the effectiveness of the current SZM control. There are two objectives in this study. One objective is to improve the control logic of current SZM strategy. This is accomplished through an estimation algorithm for the refined minimum release rate. The simulation results indicate that the improved SZM strategy is very effective in postponing and decreasing freeway congestion while resulting in smoother freeway traffic flow compared to the SZM strategy. The second objective of this project is to improve the current queue size estimation. Depending on the counting error of queue and passage detectors, freeway ramps are classified into three different categories, and different methods are applied respectively for improved queue size estimation. The surveillance video data were recorded and used to verify the improvement of the proposed methods. The results indicate that the proposed methods can greatly improve the accuracy of queue size estimation compared with the current methodology. Also, the proposed method was evaluated by the micro-simulation. The simulation results indicate the performance of freeway mainline is significantly improved. And the total system performance is better than the original SZM control.Item Employment of the Traffic Management Lab for the Evaluation and Improvement of Stratified Metering Algorithm - Phase IV(Minnesota Department of Transportation, 2007-12) Liu, Henry; Wu, Xinkai; Michalopoulos, Panos; Hourdos, JohnFreeway ramp control has been successfully implemented since mid 60's, as an efficient and viable freeway management strategy. However, the effectiveness of any ramp control strategy is largely dependent on optimum parameter values which are preferably determined prior to deployment. This is certainly the case happening to the current Stratified Zone Metering (SZM) strategy deployed in the 260 miles freeway network of Minneapolis - St. Paul metropolitan area. In order to improve the performance of the SZM, which highly depends on the values of more than 20 parameters, this research first proposed a general methodology for site-specific performance optimization of ramp control strategies using a microscopic simulation environment, as an alternative to trial and error field experimentation, and implemented the methodology to the SZM. The testing results show that the new SZM control with site-specific optimum parameter values significantly improves the performance of freeway system compared with the original SZM strategy. Secondly, this research proposed a methodology to explore the common optimum parameter values for the current SZM strategy for the whole Twin Cities freeway system, in order to replace the site-specific optimum values which have minor practical value because of the difficulties in implementation and numerous time-consumption to search the site-specific optimum values for all the freeway sections. The common parameter values are identified applying the Response Surface Methodology (RSM) based on 4 specifically selected freeway sections which can represent all types of freeway sections in Minneapolis-St. Paul metropolitan area.Item Field Implementation, Testing, and Refinement of Density Based Coordinated Ramp Control Strategy(Center for Transportation Studies, University of Minnesota, 2015-06) Hourdos, John; Geroliminis, Nikolas; Zitzow, Stephen; Limniati, Ypatia StefaniaIn the Twin Cities metropolitan area, freeway ramp metering goes back as early as 1969, when the Minnesota Department of Transportation (MnDOT) first tested ramp metering in an I-35E pilot project. To date, the Twin Cities ramp metering system has grown to include more than 433 ramp meters. Research on better, improved ramp control strategies has continued over the years and MnDOT has implemented minor and major changes in the control logic. Two independent studies both aimed at developing the next generation in ramp metering by focusing on density. Based on these efforts, two new algorithms were developed: the UMN Density and the UMD KAdaptive, named based on the campus at which they were developed. The goal of this project was to implement both algorithms and test them under real conditions. Priorities and technical problems prevented the evaluation of the UMN algorithms, so this report focuses on the evaluation of the UMD KAdaptive algorithm on two freeway corridors in the Twin Cities, MN. The first site, a section of TH-100 northbound between 50th Street and I-394, was selected to compare the then current logic, the Stratified Zone algorithm, with the new one. During the course of this project, the UMD algorithm eventually replaced the Stratified Zone algorithm and was implemented in the entire system. This full deployment also included corridors that were not controlled before. The second evaluation site on eastbound TH-212 was a site that allowed for a with/without control evaluation of the UMD algorithm. This report describes the experiments conducted at both sites and includes a comprehensive review of the state of ramp metering strategies around the world to date.Item Real-Time Prediction of Freeway Occupancy for Congestion Control(Center for Transportation Studies, University of Minnesota, 1997-09) Cherkassky, Vladimir; Yi, SangkugAccurate traffic prediction is critical for effective control of on-ramp traffic (ramp metering). During congestion, traffic shock waves propagate back and forth between the detectors, and traffic becomes inherently non-stationary and difficult to predict. Recently, several adaptive non-linear time series prediction methods have been developed in statistics and in artificial neural networks. We applied these methods to develop real-time prediction of freeway occupancy during congestion periods, from current and time-lagged observations of occupancy at several (neighboring) detector stations. This study used the following function estimation methodologies for real-time occupancy prediction: two statistical techniques, multivariate adaptive regression splines (MARS) and projection pursuit regression; two neural network methods, multi-layer perceptrons (MLP) and constrained topological mapping (CTM). All these methods were applied to freeway occupancy data collected on I-35W during morning rush hours. Data collected on one day was used for training (model estimation), whereas the data collected on a different day was used for testing, i.e., estimating the quality of prediction (generalization). Results for this study indicate that the proposed methodology provides 10-15% more accurate prediction of traffic during congestion periods than the approach currently used by Minnesota DOT.