Simulating Adaptive Control Strategies in Large Urban Networks
Abstract
This paper describes a scalable approach to simulation of decentralized adaptive signal control systems, motivated by our interest to provide a basis for assessing the benefit of the Surtrac adaptive signal control system at a potential deployment site in advance of installation. The approach centers around a simulation controller interface called VISCO, which links the VISSIM microscopic traffic simulator to a set of externally hosted local intersection control processes. Local control processes are free to communicate with each other and exchange control information in the same manner that they would in a field implementation. VISCO coordinates all interaction with the simulator process to create a distributed software-in-the-loop simulation architecture. To illustrate and analyze the efficacy of the approach, we summarize a simulation analysis that was conducted of the downtown triangle area of Pittsburgh PA. A 63-intersection VISSIM model of this site is described and analyses are presented to characterize both the efficiency of the distributed architecture and the potential utility of Surtrac adaptive control. With respect to the former, the distributed simulation of local Surtrac control processes is found to run in roughly 4.4 times faster than real-time, in comparison to the 14.4 times faster than real- time speed that a conventional VISSIM simulation of this model with fixed timing plans performed. Experiments also show that the VISCO distributed architecture is effective in significantly reducing the cost associated with VISSIM’s external COM interface. With respect expected improvement of adaptive signal control in the downtown triangle area of Pittsburgh, the simulation analysis shows strong benefit of Surtrac over both the existing timing plans in use in this area and Synchro optimized plans that were generated with perfect knowledge of traffic volumes and turning counts.
BibTeX
@techreport{Isukapati-2015-6022,author = {Isaac Isukapati and Achal Arvind and Gregory Barlow and Pranav Shah and Stephen Smith and Zack Rubinstein},
title = {Simulating Adaptive Control Strategies in Large Urban Networks},
year = {2015},
month = {September},
institute = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-15-26},
}