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In our previous research, the SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic and Signals) system that can collect event-based traffic data and generate comprehensive performance measures has been successfully developed by the University of Minnesota. In this research, a new set of interfaces are developed for SMART-SIGNAL system including new prototypes of data collection unit (DCU) and refined web-based user interface. To collect high resolution event-based traffic data including both vehicle detector actuation event and signal phase change event, two types of DCUs are designed, the TS-1 DCU and TS-2 DCU for corresponding traffic signal cabinet. TS-1 DCU connects with TS-1 cabinet using pin to pin interface, and the TS-2 DCU interfaces directly with SDLC bus within TS-2 cabinet. The DCUs uses high performance microcontroller modules, and are compact and easy to install. Both DCUs are designed to be vender independent add-on module for traffic cabinet, and can be used as flexible solution to enhance data collection by agencies. The refined web-based user interface features various performance measures to public users, such as Level of Service (LOS), queue length, travel time and intersection delays. The new set of interfaces have been deployed with the SMART-SIGNAL system at 13 intersections along Trunk Highway (TH) 13 in Burnsville, MN.

The Integrated Corridor Management (ICM) approach has drawn increasingly more attention in recent years because it is believed to be a promising tool to mitigate urban traffic congestion. In this project, a maximum flow based control model was first developed to handle oversaturated traffic conditions at signalized arterials. Based on the arterial control model, an integrated control model was proposed to manage network congestion. Through diversion control, the model aims to fully utilize the available capacity along parallel routes. The impact of the diversion traffic is considered, especially for signalized arterials, so that traffic congestion on the diversion route can be reduced or eliminated by proper adjustment of signal timings. This model does not rely on time-dependent traffic demand as model inputs and it is ready to be implemented at typical parallel traffic corridors where the standard detection system is available. The performance of the proposed model was tested using microscopic traffic simulation in the I-394 and TH 55 corridor in Minneapolis, Minnesota. The results indicate that the proposed model can significantly reduce network congestion.

Starting from 1993, MnDOT annually prepares a Metro Freeway System Congestion Report to document congested segments of the freeway system. However, a similar congestion report for the arterial system has not been developed, mainly due to lack of ability for automatic traffic signal data collection and performance measurement. In this project, based on the archived high-resolution traffic data from four major arterials equipped with the SMART-Signal system in the metro area, i.e., Trunk Highway 13, Trunk Highway 55, Trunk Highway 7 and Trunk Highway 10, we developed an innovative approach to generate an arterial traffic congestion report for the MnDOT Metro District. Results show that the main approaches of the four signalized corridors operate very efficiently during AM and PM peaks, but larger delays happen at side streets in general.

Data collection and performance measurement for signalized arterial roads is an area of emerging focus in the United States. As indicated by the results of the 2005 Traffic Signal Operation Self-Assessment Survey, a majority of agencies involved in the operation and maintenance of traffic signal systems do not monitor or archive traffic system performance and thus have limited means to improve their operation. With support from the Transportation Department of Hennepin County, Minneapolis, MN, a system for high resolution traffic signal data collection and arterial performance measurement has been successfully built. The system, named SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic Signals), is able to collect and archive event-based traffic signal data simultaneously at multiple intersections. Using the event-based traffic data, SMART-SIGNAL can generate timedependent performance measures for both individual intersections and arterials including intersection queue length and arterial travel time. The SMART-SIGNAL system has been deployed at an 11-intersection corridor along France Avenue in south Minneapolis and the estimated performance measures for both intersection queue length and arterial travel times are highly consistent with the observed data.