In 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.

A new ramp metering strategy implemented on the Twin Cities freeway system to reduce ramp waiting times was evaluated through microsimulation of freeway activity. The study compared Stratified Ramp Metering strategy with the previous Zone Metering Strategy and with no control strategy. Comparison with Zone, which was designed to favor freeway flow, showed the new strategy succeeded in greatly reducing ramp delays and lines. When compared to the results of no control strategy, it reduces freeway travel time, increases freeway speed, smoothes the flow of traffic, and reduces the number of stops. However, travel time, fuel consumption and pollutant emissions are unpredictable under the newer system. Compared to no control strategy, such measures of effectiveness may improve or worsen depending on the freeway patterns and demand. Based on these findings, the researchers will seek improvements to the design of the Stratified Ramp Metering algorithm so as to factor in disruptive traffic patterns.

Freeway ramp metering systems have been used to improve urban freeway flow. However, control strategies must be properly adjusted to account for ramp queues overflowing onto surface streets and provide equitable on-ramp control during various operating periods. An improved solution can be obtained by optimizing this problem simultaneously for a group of time slices. This study identifies and examines a microcomputer-based optimization scheme that can assist in developing efficient freeway control strategies for on-line freeway surveillance and control. A multi-level freeway control structure is employed for which ramp metering control algorithms are developed for each level of control. Flow-based and lane occupancy-based system algorithms are presented. Detailed data file requirements are provided for each control level. A microcomputer prototype, or laboratory test version of the system level, will be described in a companion project report.

The main objectives of Task Order 4136 are (1) the design of improved freeway on-ramp metering strategies that make use of recent developments in traffic data collection, traffic simulation, and control theory, and (2) the testing of these methods on a 14-mile segment of Interstate 210 Westbound in southern California. To date, the major accomplishments of this project include (i) the development of a complete procedure for constructing and calibrating a microscopic freeway traffic model using the Vissim microsimulator, which was applied successfully to the full I-210 test site, (ii) a simulation study, using the calibrated Vissim I-210 model, comparing the fixed-rate, Percent Occupancy, and Alinea local ramp metering schemes, which showed that Alinea can improve freeway conditions when mainline occupancies are measured upstream of the on-ramp (as on I-210 and most California freeways), as well as when occupancy sensors are downstream of the on-ramp, (iii) development of computationally efficient macroscopic freeway traffic models, the Modified Cell Transmission Model (MCTM) and Switching-Mode Model (SMM), validation of these models on a 2-mile segment of I-210, and determination of observability and controllability properties of the SMM modes, (iv) design of a semi-automated method for calibrating the parameters of the MCTM and SMM, which, when applied to an MCTM representation of the full I-210 segment, was able to reproduce the approximate behavior of traffic congestion, yielding about 2% average error in the predicted Total Travel Time (TTT), and (v) development of a new technique for generating optimal coordinated ramp metering plans, which minimizes a TTT-like objective function. Simulation results for a macroscopic model of the 14-mile I-210 segment have shown that the optimal plan predicts an 8.4% savings in TTT, with queue constraints, over the 5-hour peak period.