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Browsing by Author "Stephanedes, Yorgos J."

Now showing 1 - 17 of 17
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    Development and Application of Demand-Responsive Ramp Metering Control to Improve Traffic Management in Freeway Corridors
    (1992-01) Stephanedes, Yorgos J.; Kwon, Eil; Chang, Kaikuo; Yao, Ping
    A method is developed for evaluating traffic-responsive ramp metering strategies and improving freeway performance. The method emulates real-time metering and rigorously traces the interactions between automatic rate-selection metering strategies and freeway performance through time. Given a demand pattern and freeway geometrics, it provides assessment of metering strategies that change continuously at very short time intervals. Further, it explicitly treats time delays that can be caused by hardware or introduced by the traffic engineer.
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    Development and application of incident detection techniques to improve incident management in freeway corridors
    (1993-01) Stephanedes, Yorgos J.
    Responding to the need for effective and reliable detection of freeway incidents, an essential element for improved traffic management and control in freeway corridors (Stephanedes and Chang, 1991), the authors initiated this research to investigate the performance limitations of conventional automatic incident detection systems and define the specifications for a new algorithmic logic that can lead to improved detection performance. The research initially focused on assessing the ultimate detection performance that can be accomplished with existing and new incident detection systems that use traffic data from presence detectors. A new algorithm was developed and tested against the major existing ones with promising results towards the development of a more-sophisticated detection structure. All tests employed a unified system of performance assessment (Stephanedes and Chassiakos, 1991), suitable for direct algorithm evaluation. The major accomplishments of this project are: * Review of current incident detection algorithms. * Testing major existing algorithm in the Twin Cities Freeway system. * Development of data preprocessing techniques to enhance the incident signal. * Development and testing of incident detection algorithms based on the data preprocessing.
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    Development and Application of On-Line Strategies for Intersection Control Phase I: Review of Advanced Control Strategies
    (Center for Transportation Studies, 1992-12) Stephanedes, Yorgos J.; Kwon, Eil; Michalopoulos, Panos G.; Mallis, John; Roetzel, Ronald
    SCOOT, SCATS, PRODYN and OPAC represent the state-of-the-art control strategies for signalized traffic network management by employing advanced control concept such as demand-responsive, on-line timing generation with adaptive features. While there have been individual tests of the above state-of-the-art control strategies by various agencies, no comprehensive effort has been made to evaluate and quantify the performance of each strategy, especially in terms of their applicability to both loops and video detection. This research reviews the advanced intersection control strategies developed to date. Due to the lack of field evaluation that can directly compare each control strategy, this study focused on the theoretical principles and implementation issues found from the literature. Further, the existing intersection control systems in three major cities in the U.S. and Canada are analyzed and their control algorithms are introduced. Finally, the current status of the video detection development is also reviewed.
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    Development and Application of On-Line Strategies for Optimal Intersection Control (Phase III)
    (Minnesota Department of Transportation, 1996-10) Kwon, Eil; Stephanedes, Yorgos J.; Liu, Xiao; Chidambaram, Sabhari; Antoniades, Charalambos
    The previous phases of this research reviewed and tested existing intersection control algorithms in a simulated environment. Further, a machine-vision detection system with four cameras was installed at the intersection of Franklin and Lyndale Avenues in Minneapolis, Minnesota, to develop a live intersection laboratory. Phase III enhanced the live laboratory with two additional cameras covering the intersection proper and the extended approach of southbound Lyndale Ave. A comprehensive operational plan for the laboratory was developed and a new microscopic simulator for the laboratory intersection was -also developed. Two types of new intersection control strategies, i.e., one with link-wide congestion measurements and the other based on neural-network approach, were developed and evaluated in the simulated environment. Further, using the data collected from the machine-vision detection system, an automatic procedure to estimate the intersection delay was also developed and applied to compare the performance of fixed-timing control with that of the actuated control strategy.
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    Development and Application of On-Line Strategies for Optimal Intersection Control Phase II: Off-Line Evaluation of Control Strategies and Development of a Live Laboratory
    (Minnesota Department of Transportation, 1994-10) Stephanedes, Yorgos J.; Kwon, Eil; Liu, Xiao
    This project evaluates various intersection control strategies in a simulated environment and also helped establish a live laboratory for use in future testing of new control strategies. The report reviews major intersection control strategies, including the state-of-the-art strategies with adaptive and on-line timing generation features. In addition, it details simulation results for the OPAC control strategy. The NETSIM simulator created the simulation environment for a test network that included part of downtown Minneapolis. Comparison results indicate that OPAC performs best with low-traffic demands, and pretimed control was the most effective during peak periods when traffic demand reached capacity. In conjunction with this project, Minneapolis city traffic engineers installed a machine-vision video detection system at a live intersection laboratory. Located at Franklin and Lyndale Avenues, the test site will help researchers evaluate new control strategies before full-scale implementation in later phases of this research.
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    Development and Application of On-Line, Integrated Control Strategies for Optimal Metering, Incident Management and Driver Guidance in Freeway Networks: Phase I Final Report
    (1993-04) Stephanedes, Yorgos J.; Kwon, Eil; Chang, Kaikuo; Vairamidis, Nikos
    Managing freeway congestion requires an integrated approach involving demand-responsive ramp metering, incident management and driver guidance. While a freeway network acts as a system, i.e., conditions on any part affect other parts in the network, the state of the art in real-time freeway management has not reached the point where comprehensive, network-wide optimal control schemes are automatically generated and implemented through on-line optimization and coordination of various control actions. A major difficulty lies in the lack of efficient computational algorithms implementable for on-line optimization, and the lack of accurate on-line predictors, that can predict traffic demand and diversion in freeway networks. As a result of the above limitations, most traffic responsive metering systems, such as the Twin Cities freeway control system, employ automatic rate-selection procedures. These procedures select the most appropriate metering rates for a ramp from a pre-determined library using the information received from loop detectors on the main freeway, upstream and downstream from the ramp. Although this method provides a degree of self-adjustment to prevailing traffic conditions, the lack of an efficient analysis tool to evaluate and update the key components of the control, i.e., thresholds and rate-libraries, significantly restricts the effectiveness of control.
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    Development of On-Line Control Strategies in Freeway Networks, Phase 2: Final Report
    (Minnesota Department of Transportation, 1998-05) Stephanedes, Yorgos J.; Liu, Xiao; Liu, Lu; Michel, Bernard R.
    Most traffic-responsive freeway ramp metering systems select metering rates from predetermined rate libraries. The efficiency of such systems is impaired by the lack of an efficient analysis tool that can evaluate and update the thresholds and rate libraries used by the meter controllers. In this project, a control-emulation method is developed to evaluate various automatic rateselection strategies; the new modeling features of this system are described in detail. Various rate selection strategies (based on neural network processing, exit ramp volume, and real time bottleneck/dynamic zone determination) are described and evaluated in comparison with the current Minneapolis-St. Paul strategy. An online traffic volume predictor based on Kalman filtering is developed, and integrated into the control-emulation module. A simulated annealing optimization algorithm, previously implemented on a supercomputer, is re-implemented on a personal computer and integrated into the simulation module.
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    Minnesota transit laboratory: phase 1 conclusions: improving transit service
    (1989) Stephanedes, Yorgos J.; Doumbia, Bangali
    The desire to increase the attractiveness and use of transit has led the Minnesota Department of Transportation, the Center for Transportation Studies, and the Department of Civil and Mineral Engineering at the University of Minnesota to set up a Laboratory for developing improved service and encouraging innovation in transit. Prior to seeking improvement of transit operations and the attractiveness of public travel, the problems of the transit industry had to be clearly defined. To that effect, an initial set of eight problem areas was defined and prioritized on the basis of short- and long-term by a group of local experts. However, as seeking solution to all the problems hence defined would be a most demanding task, it was desirable to reduce the set to a more manageable size that included the problems that were well defined, important, feasible and desirable for analysis and solution in Minnesota and elsewhere. To conduct this analysis, a well known and proven methodology, the Delphi Technique, was used. The findings of the Delphi procedure indicate a prioritization that is, in principle, different from what was initially suggested by the group of local experts. Both groups - the Delphi participants and the local experts ? did concur on the ratings of a few problems (e.g., EFFECT OF COLD CLIMATE). The results of the Delphi procedure and the suggested prioritization of the local experts are exhibited on the following page.
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    Real-Time Traffic Prediction for Advanced Traffic Management Systems: Phase I
    (Intelligent Transportation Systems Institute, University of Minnesota, 1995-10) Davis, Gary A.; Stephanedes, Yorgos J.; Kang, Jeong-Gyu
    It has been recommended that Advanced Traffic Management Systems (ATMS) must work in real-time, must respond to and predict changes in traffic conditions, and must included areawide detection surveillance. To support such ATMS, this project developed a tractable, stochastic model of freeway traffic flow and travel demand which satisfies three primary objectives. First, the model should generate real-time estimates of traffic state variables from loop detector data, which can in turn be used as time-varying initial conditions for more comprehensive simulation models, such as KRONOS or FREESIM. Second, the model should generate its own predictions of mainline and off-ramp traffic volumes, as well as calculate the expected error associated with these predictions, thus supporting the use of both deterministic and stochastic optimization for determining traffic management actions. Third, the model should be capable of full on-line implementation, in that it should be capable of estimating required parameters from traffic detector data. The basic model was developed by combining ideas from the theory of Markov population processes with a new for the relationship between traffic flow and density, producing a stochastic version of a simple-continuum model. Kalman filtering was then applied to the basic model to develop algorithms for (1) estimating from loop detector counts the traffic density in freeway sections broken down by destination off-ramp, (2) predicting main-line and off-ramp traffic volumes from given on-ramp volumes and, (3) computing adaptive estimates of the freeway's origin destination matrix from loop detector counts. Monte Carlo simulation tests were used to evaluate three different methods for off-line estimation of model parameters, as well as to assess the accuracy of the density estimates and volume predictions. The results indicated that the estimation and prediction model tends to be robust with respect to the parameter estimation scheme, and that the model generates a reasonable characterization of estimation and prediction uncertainty. Limited tests with field data tended to confirm the simulation results, and to emphasize the importance of real-time estimation of freeway origin-destination matrices in generating accurate predictions.
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    Real-Time Traffic Prediction for Advanced Traffic Management Systems: Phase II
    (2006-04-01) Davis, Gary A.; Stephanedes, Yorgos J.; Lan, Chang-Jen
    This project focuses on systems of signalized intersections, with the goals of: 1) conducting a detailed empirical evaluation of the traffic flow model used to predict evolution of traffic conditions, and 2) posing and solving an optimization problem that determines those traffic detector configurations containing enough information to generate state and parameter estimates of sufficient precision. The empirical evaluation also involves comparing the output of several methods for estimating intersection turning movement proportions to manual turning movement counts.
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    Real-Time Traffic Prediction for Advanced Traffic Management Systems: Phase III
    (2006-05-01) Davis, Gary A.; Stephanedes, Yorgos J.; Lan, Chang-Jen
    Building on the research performed in Phases I and II of this study, the authors develop in Phase III an algorithm for estimating vehicle turning proportions at signalized intersections using partial detector information. This report demonstrates the efficiency of a maximum likelihood estimator approach to estimate turning proportions over a prediction error minimization principle. This phase enhances the traffic flow models to provide more detail on short-term instability and left-turning behavior at intersections. Finally, the authors develop two types of estimation algorithms using Nonlinear Least Squares and Quasi Maximum Likelihood to estimate the turning proportion parameters. These algorithms are useful tools to generate real-time applications in traffic control.
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    Techniques for Detection of Incidents and Traffic Disturbances
    (1994-04) Stephanedes, Yorgos J.; Vasilakis, George
    The increasing contribution of incidents to freeway congestion has generated strong interest in the development of incident detection algorithms in the last two decades. According to Federal Highway Administration estimates (Lindley, 1986), incidents currently account for up to 60% of the vehicle-hours lost to freeway congestion; projection for the year 2005 indicates a 70% contribution of incidents to total delay. Fast and accurate detection of incidents can, therefore, substantially reduce the impact of incident congestion on freeway traffic. In particular, when an incident alarm is promptly signaled, traffic management plans can be adjusted in real time to produce the best control and guidance actions in freeway corridors. In addition, the incident management process (detection, response, and clearance) is initiated as emergency vehicles can be promptly dispatched to clear the incident. Existing techniques for the detection of freeway incidents do not provide the necessary reliability for freeway operations. Conventional automated techniques, based on computerized algorithms, are less effective than is desirable for operational use because they generate a high level of false alarms. Operator-assisted methods minimize the false alarm risk, but suffer from missed or delayed detections, are labor intensive, and restrict the potential benefits from advanced, integrated traffic management schemes. The initial phase of this research focused in assessing the performance limitations of conventional automatic incident detection systems. That research was directed towards two objectives, the performance evaluation of major existing algorithms and the development of an improved algorithm. This part of the research pointed out that the existing techniques for the automatic detection of freeway incidents are not reliable as they are seriously handicapped by excessive, operationally unacceptable false alarm rates. The new algorithm proposed by the authors was developed for identifying capacityreducing incidents in freeway traffic. That algorithm aims to minimize the number of false alarms that the existing algorithms generate when temporal random oscillations in the traffic measurements, frequently observed in congested flows, occur. The proposed structure involved preprocessing the traffic data with average, median, or exponential smoothers over data windows of approximately five minute length to eliminate or reduce the size of traffic fluctuations. Although the new algorithm showed an improved and satisfactory performance relative to the conventional algorithms, the initial stage of this research pointed out the need of more research in finding ways and methods for distinguishing between the incident and the non-incident alarms and highlighted the issues that had to be addressed by the second stage of this project.
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    Techniques for Rural Transit Service Design
    (1991-08) Stephanedes, Yorgos J.; Vairamidis, Nikos
    Transit service is playing an increasingly vital role in maintaining and improving the mobility and economic well-being of rural populations in the North Central region. This has been particularly important as the decline in several small towns has led to a dependency on regional centers or metropolitan areas for services formerly provided locally. While rural transit systems have become more important, higher operating expenses and reduced federal subsidies have made state transit management, design and funding decisions more complex. This project has developed methods and tools to aid these important decisions.
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    Transit System Monitoring and Design
    (1990-01) Stephanedes, Yorgos J.
    Statistical techniques were developed for extracting the most significant features (indicators) from a transit system data base, and classifying proposed and existing transit systems according to the selected features. The data base was constructed by using information from all previous years available by the Mn/DOT, the Census and other sources to be used in classifying transit systems. The data base emphasized the use of raw characteristics of the operating system and the area socioeconomics. The feature extraction was done so that the minimum number of features were extracted that can be used for classifying the transit systems with maximum accuracy. The classification method was designed around the data base and is flexible so that it can use future data to update the data base at minimum cost. The transit system patterns, resulting from the classification method, were identified according to need and performance, and the main characteristics were specified for each pattern. These characteristics and descriptions identifying each pattern determines whether it should be modified. A controlled experiment was required to test the classification method. A randomly selected part of the data was classified by the method, and then the unselected data was treated as a control group for the experiment. After the experiment a percent of misclassifications was calculated.
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    Transportation and Economic Development
    (1988-07) Stephanedes, Yorgos J.
    This report summarizes the results of a project undertaken by a University of Minnesota team for the Minnesota Department of Transportation (Minnesota DOT) to determine the existence and extent of relationships between transportation and economic development (in particular, employment) in Minnesota. The interdisciplinary team was directed by the Department of Civil & Mineral Engineering and included experts from Civil & Mineral Engineering, Geography, Economics (both Twin Cities and Duluth campuses), Applied & Agricultural Economics, Industrial Engineering & Operations Research, and Regional Economics.
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    Urban Congestion Reduction for Energy Conservation: Control Strategies for Urban Street Systems: A State of the Art: Final Report
    (1988-01) Hajjiri, Samir A.; Stephanedes, Yorgos J.
    The primary objective of this study is to acquire an understanding of the current state-of-the-art of traffic signal control strategies at urban street systems. Control of traffic signals is by far the most common type of control at heavily trafficked intersections in urban areas. Inefficient use of the transportation system results when traffic signals are set without the aim of optimizing them. The byproducts of such situations include greater fuel consumption, increased vehicle emissions, increased travel time, higher accident rate, and less reliable services.
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    Urban Traffic Monitoring, Navigation, and Guidance to Alleviate Urban Traffic Congestion
    (1988-03) Chang, Kui-Kuo; Stephanedes, Yorgos J.
    Traffic congestion in urban area seems to be rapidly spreading in space and in time. A few years ago, roads surrounded the central business district of any metropolitan areas had hardly any traffic at all. But now, thousands of commuters crowd in there and try to find shortcuts from their suburban homes to their suburban office destinations. Traffic congestion is spreading to the entire highway network instead of the main radial corridors from downtown. Similarly, the traditional rush hours during the morning and afternoon in the urban area disappeared and have been replaced by a high plateau rush hour which continues from early morning to evening.