Centralized and Decentralized Signal Control with Short-Term Origin-Destination Demand for Network Traffic. (28th April 2022)

• Record Type: Journal Article
• Authors: Zhang, Can; Qiu, Tony Z.; Kim, Amy
• Other Names: Dong Jing Academic Editor.
• Is Part Of: Journal of advanced transportation. Volume 2022(2022)
• Publication Date: 2022-04-28
• Subjects: Transportation -- Periodicals; 388.05
• DOI: 10.1155/2022/5806160
• Languages: English
• ISSNs: 0197-6729

Abstract

Abstract : We develop and assess centralized and decentralized signal control systems with short-term origin-destination (OD) demands as inputs. Considering each intersection turning movement as a virtual link, we assign traffic demand to paths based on minimal instantaneous travel time. Then, the optimal control is formulated using a G/G/n/FIFO open queueing network model (QNM). We also solve the issue of optimal control using a three-step naïve method for the centralized system with the new inputs. Because the optimization of large-scale network traffic signals can involve sizeable numbers of decision variables and nonlinear constraints, making it a nondeterministic polynomial time (NP) complete problem, we further decompose the centralized system into a decentralized system where the network is divided into subnetworks. Each subnetwork has a dedicated agent that optimizes signals within it. Furthermore, traffic demand for the entire network is decomposed into demands for subnetworks via path decomposition index (PDI). The proposed control systems are applied to test scenarios constructed using different demand profiles in grid networks. We also investigate the impact of network decomposition strategy on signal control system performance. Results show that network decomposition with smaller subnetworks results in less computational time (CT) but increased average travel time (ATT) and total travel delay (TTD).