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Development and Application of On-Line Strategies for Optimal Intersection Control Phase II

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Date Created
1994-10
Report Number
95-05
Description
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. The Phase I report is available at https://hdl.handle.net/11299/155938.

Development and Application of On-Line Strategies for Optimal Intersection Control (Phase Ill)

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Date Created
1996-10
Report Number
96-33
Description
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. The Phase I report is available at https://hdl.handle.net/11299/155938.