Adaptive perimeter control for multi-region accumulation-based models with state delays. (July 2020)

• Record Type: Journal Article
• Authors: Haddad, Jack; Zheng, Zhengfei
• Is Part Of: Transportation research. Volume 137(2020)
• Page Start: 133
• Page End: 153
• Publication Date: 2020-07
• Subjects: Accumulation-based models -- Macroscopic fundamental diagram -- State delay -- Adaptive perimeter control; Transportation -- Research -- Periodicals; Transportation -- Mathematical models -- Periodicals
• DOI: 10.1016/j.trb.2018.05.019
• Languages: English
• ISSNs: 0191-2615

Abstract

Abstract: Enhancing macroscopic fundamental diagram (MFD) dynamic models and improving perimeter control algorithms are the current main research challenges in the MFD research area. Over the last decade, different accumulation-based dynamic models, describing the traffic flow dynamics of one or multi-region systems, have been developed in different forms relying on vehicle conservation equations. In this research, two enhanced accumulation-based models are developed by incorporating into model structure the time-delay (time-lag) effects as an important factor. The first model incorporates state delay in the MFD output to improve the dynamics, to better represent wave propagation and travel time evolution within the region, especially when the change in demand is fast. While in the second model delayed interconnections are introduced in the dynamic equations to model data processing and communication delays between interconnected regions. The two linearized models are formulated in interconnected forms. Then, the reference model adaptive control approach has been implemented to allow us designing distributed adaptive perimeter control laws. The developed adaptive control scheme postulates one controller structure, however, the controllers' gains vary with time to adapt themselves against the model parameter uncertainties and state delays. The numerical results demonstrate the flexibility of the distributed adaptive perimeter controllers in handling different cases and various traffic situations with state delays.