Development and Application of On-line Strategies for Optimal Intersection Control: Phase III
Minnesota Department of Transportation, Office of Research Administration, 1996 - Cellular automata - 112 pages
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 Avenue. 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.
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DEVELOPMENT OF INTERSECTION LABORATORY
DEVELOPMENT OF MICROSCOPIC INTERSECTION
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actuated control algorithm allowable gap AM-Peak period ASCII average delay Backpropagation neural network carmot CARS cellular automata changes City of Minneapolis class network classiﬁers congestion index controller unit data collected data ﬁles database deﬁned Delay calculations delay per vehicle demand pattem demand responsive detection system developed eastbound approach evaluate ﬁ'om ﬁeld ﬁrst ﬁxed ﬂoat ﬂow headway Hopﬁeld incident detection installed InterLab intersection control strategy intersection laboratory isolated intersections LabView lane machine vision machine-vision detection machine-vision system machine-vision unit maximum green minimum Minneapolis NETSIM neural network neuron nodes number of vehicles ObjectPAL Off-Peak optimization output PACKSIM parameters performance Phase sequence pretimed control queue length SCOOT segment signal simulated annealing simulation slice source code Southbound approaches speciﬁc speed traps stop-line sub-network supervisor computer Table testing trafﬁc conditions trafﬁc control trafﬁc data trafﬁc demand updating upstream intersection veh hr veh sec vehicle actuations vehicle arrivals