John Hourdakis

PRACTICAL PROCEDURE FOR CALIBRATING MICROSCOPIC TRAFFIC SIMULATION MODELS

Since the use of simulation is becoming widespread in traffic engineering practice, questions about the accuracy and reliability of its results need to be addressed convincingly. A major criticism related to this issue is proper calibration of the simulation parameters as well as validation, which is often not done or dealt with in an ad hoc fashion. A complete, systematic, and general calibration methodology is presented for obtaining the accuracy needed in high-performance situations. A technique for automating a significant part of the calibration process through an optimization process is also presented. The methodology is general and is implemented on a selected simulator to demonstrate its applicability. The results of the implementation in two freeway sections of reasonable size and complexity, in which detailed data were collected and compared with simulated results, demonstrate the effectiveness of the manual calibration methodology. For instance, through calibration the average volume correlation coefficient on 21 detecting stations improved from 0.78 to 0.96. Comparable results were obtained with the automated calibration procedure with significant time savings and reduced effort.

EVALUATION OF RAMP CONTROL EFFECTIVENESS IN TWO TWIN CITIES FREEWAYS

Recent public opposition threatened to eliminate ramp control as a traffic management option in the Twin Cities of Minneapolis and St. Paul, which have one of the most extensive ramp control systems in the nation. In response to this, the Minnesota Department of Transportation had to produce tangible independent evidence that ramp metering is effective, to avoid turning off the meters. Simulation is the most widely accepted technique for achieving the stated objectives without turning the metering system off, and therefore it was used in this study. Two freeway sections were selected for detailed testing, and the results along with the methodology are presented here. The results confirm that ramp metering is effective on the ramp and freeway system (not just the freeway), but they also revealed excessive delays on certain ramps that appear to support the concerns raised by the users. Real-life issues related to the simulation implementation process (data collection and filtering, calibration, and interpreting and summarizing results) are also presented. Through the course of this work, simulation reliability was established by defining a successful calibration and validation methodology and by identifying, in the process, certain operational problems related to the deployed surveillance and control system that had been unknown. Finally, a general methodology was developed for evaluation that can easily be adapted to any user-specified control strategy or used to improve an already existing one without field disruptions.

MINNESOTA'S NEW RAMP CONTROL STRATEGY: DESIGN OVERVIEW AND PRELIMINARY ASSESSMENT

Freeway ramp control has been successfully implemented in the Minneapolis-St. Paul area since the early 1970s. However, the recent ramp metering controversy highlighted the need for a less restrictive ramp control strategy that maximizes freeway capacity utilization while limiting ramp wait times. As a result, a new multilayer ramp control strategy called stratified ramp control was recently developed and deployed systemwide in the Twin Cities metropolitan area. This strategy determines the metering rates from freeway conditions as well as from real-time ramp demand and ramp queue size, indicating a shift of emphasis away from freeway flow toward the balance between both freeway efficiency and reduced ramp delays. Minnesotas new ramp control strategy is detailed along with a preliminary assessment of its effectiveness. The evaluation is accomplished by comparing the new strategy to its predecessor, ZONE metering, through rigorous micro-simulation. The preliminary results suggest that the stratified ramp control strategy is effective in reducing ramp delays and limiting ramp wait times below the prescribed value. However, peak-hour freeway congestion is extended in both time and space as opposed to that with the ZONE metering strategy and reveals a compromised freeway performance in favor of virtually reducing ramp delays.

TRANSFERABILITY OF FREEWAY INCIDENT DETECTION ALGORITHMS

This research seeks to evaluate the potential for transferability of new freeway incident detection algorithms that can be used in automatic incident detection. An incident detection logic is evaluated that distinguishes incidents from recurrent congestion and other traffic disturbances using exponential smoothing. The algorithm is tested with loop detector data from test sites on I-35W in Minnesota and I-880 in California with promising results. Test results indicate that, at the Minnesota test site, algorithm performance improves over earlier findings with a limited data set, without requiring recalibration. At a detection rate of approximately 60 percent, the algorithm produces one false alarm per hour in the total (southbound and northbound) 40-km (25-mi) test section, which includes 54 detector stations. When the algorithm is recalibrated and tested at the California site, its performance further improves. The performance of the algorithm is compared with that of major algorithms of comparative type ...

Methodology for Performance Optimization of Ramp Control Strategies Through Microsimulation

Freeway ramp control has been successfully implemented since the mid-1960s as an efficient and viable freeway management strategy. However, the effectiveness of any ramp control strategy is largely dependent on site-specific customization and calibration, preferably before its deployment. A general methodology for such performance optimization of ramp control strategies is proposed in a microscopic simulation environment as an alternative to trial-and-error field experimentation. The applicability of the methodology is demonstrated by implementation on Minnesotas new stratified zone metering (SZM). Further, the effect of external factors, such as traffic demand variation and incidents, on SZM control and optimization results was also studied. Results show that the optimization methodology is highly effective depending on the optimization objective, test site characteristics, and demand levels.

Deployment of Wireless Mobile Detection and Surveillance for Data-Intensive Applications

Real-time information about traffic conditions is vital in construction, advanced traffic management systems, advanced traffic information systems, and other operational or design activities. Traditionally, at most permanent installations, such information is captured by in-pavement sensors and transmitted through land-based communications. However, temporary detection and surveillance are often needed as alternatives to the permanent sensor and camera systems at construction sites, during special events, or during communication or sensor failures. In such cases, temporary detection and surveillance must be reliable and low cost. Recent advances in wireless technologies have enabled development of portable detection and surveillance systems that can detect traffic, collect measurements, capture live video, and transmit this information wire-lessly back to the supervising station to facilitate rapid, inexpensive, and efficient deployment. However, to make widespread use practical, further improvements are needed in robustness, ease of use, functionality, and cost reduction. A low-cost, easily deployable detection and surveillance system is presented. The system integrates machine vision sensors for data collection, compressed digital video for surveillance, and wireless communications for information retrieval and remote control. It can be placed on existing or mobile structures and assembled with off-the-shelf components to serve department of transportation needs for both temporary traffic monitoring and planning and research data collection. Four of these advanced detection systems were deployed at a 1.7-mi site for wireless, continuous coverage, allowing detailed real-time data collection and surveillance. This data- and video-intensive deployment serves as a live laboratory for applications ranging from evaluation of new technologies (such as sensors, video, wireless communications) to testing of advanced traffic-simulation models or refinement of accident-prevention studies.

Computer aided testing and evaluation of adaptive ramp control strategies

In this paper a practical methodology is presented for selecting, testing and calibrating the most suitable adaptive ramp control strategy for freeway corridors. This methodology is part of a Traffic Management Laboratory (TRAMLAB) and can also be used for improving or fine tuning existing control strategies or developing new ones. The simulation part TRAMLAB is based on automating the use of simulation to the extent possible through the integration with a user defined external traffic management system and simplifying data entry through computer aided design. A simple application of the use of TRAMLAB is presented by implementing afield proven real time ramp control strategy and comparing it with the no-control alternative. Plans for using TRAMLAB for developing the next generation of the control strategy and other applications or enhancements are also presented.

Requirements and procedures for employing simulation in ITS applications

The need to simulate a number of advanced ITS concepts prior to deployment necessitated development of high performance microscopic simulators for heuristic dynamic traffic assignment, freeway corridor diversion, driver information systems including variable message signs and vehicle guidance systems, real-time adaptive traffic control and other traffic management concepts. In spite of recent progress in developing sophisticated simulators for ITS applications their employment in real life projects requires substantial data collection, testing, validation and calibration. The latter is often ignored in practice where for convenience simulators are often used without sufficient validation and calibration, resulting in unreliable and/or inaccurate results. The objective of this paper is to demonstrate the issues and lessons learned in the employment of a sophisticated simulator for evaluating the effectiveness of adaptive ramp control in the Twin cities of Minneapolis and St. Paul, which is one of the earliest and most extensive worldwide (210 miles of freeway, 430 ramp meters).

AIDDS: A System for Developing and Testing Incident Detection Algorithms

Abstract Incident management is a major problem in traffic control. Traffic incidents are the cause for more than half of all traffic delays. The research undertaken by the University of Minnesota has reached a point where good knowledge on different incident detection techniques has been achieved. The computer program presented in this paper is designed to assist researchers in testing incident detection algorithms. The primary gains by using this program are the reduction of time needed for algorithm testing and the flexibility on designing the test site. With this program the user can assign individual threshold sets in every section, and use multiple algorithms simultaneously. The algorithms included in the version presented in this paper are DELOS(3,3), CALIFORNIA, Alg. #7, and Alg. #8. Some of the features that make this program unique are its ability to combine measurements on the field to create “pseudo” detectors, its capability to automatically judge if a detection is valid, and its ability to combine incident detection algorithms to improve detection performance.