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.
Kwon, Eil; Stephanedes, Yorgos J.; Liu, Xiao; Chidambaram, Sabhari; Antoniades, Charalambos.
Development and Application of On-Line Strategies for Optimal Intersection Control (Phase III).
Minnesota Department of Transportation.
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