Optimal Perimeter Control for Two Urban Regions With Macroscopic Fundamental Diagrams: A Model Predictive Approach

By Nikolaos Geroliminis, Jack Haddad, Mohsen Ramezani Ghalenoei. IEEE transactions on intelligent transportation systems (Print), 2013

512 citations recorded by the source corpus.

Recent analysis of empirical data from cities showed that a macroscopic fundamental diagram (MFD) of urban traffic provides for homogenous network regions a unimodal low-scatter relationship between network vehicle density and network space-mean flow. In this paper, the optimal perimeter control for two-region urban cities is formulated with the use of MFDs. The controllers operate on the border between the two regions and manipulate the percentages of flows that transfer between the two regions such that the number of trips that reach their destinations is maximized. The optimal perimeter control problem is solved by model predictive control, where the prediction model and the plant (reality) are formulated by MFDs. Examples are presented for different levels of congestion in the regions of the city and the robustness of the controller is tested for different sizes of error in the MFDs and different levels of noise in the traffic demand. Moreover, two methods for smoothing the control sequences are presented. Comparison results show that the performances of the model predictive control are significantly better than a “greedy” feedback control. The results in this paper can be extended to develop efficient hierarchical control strategies for heterogeneously congested cities.

Subfields: Building and Construction, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/0513ab18ada00a11eec058a246d577e969dc2070

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Citations in the corpus

Urban traffic signal control with connected and automated vehicles: A survey (2019, background): “Most current works on MFD-based traffic control focused on regional-level perimeter control (Geroliminis et al., 2013; Haddad et al., 2013).”
Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control (2015, methodology): “The control problems in previous works, e.g. Geroliminis et al. (2013) and Haddad et al. (2013), have been solved by the model predictive control (MPC) approach.”
Perimeter and boundary flow control in multi-reservoir heterogeneous networks (2013, background): “It can also be utilized to introduce simple perimeter flow control policies to improve mobility in homogeneous networks (Daganzo, 2007; Keyvan-Ekbatani et al., 2012; Geroliminis et al., 2013).”
On the spatial partitioning of urban transportation networks (2012, result): “Perimeter control is not studied in this paper, but recent results show the applicability of the MFD concept (e.g. Geroliminis et al., 2012; Keyvan-Ekbatani et al., 2012).”
Robust Constrained Control of Uncertain Macroscopic Fundamental Diagram Networks (2015, methodology): “The nonlinear model for R homogeneous regions is based on Geroliminis et al. (2013); Haddad and Mirkin (2015); Hajiahmadi et al. (2014).”
Network resilience (2020, background): “two-regions is proposed through model predictive control [761], with the controller at the border between tworegions.”