Hirsh Majid

Distributed model predictive control of freeway traffic networks: A serial partially cooperative approach

In this paper, a new distributed model predictive control (MPC) scheme for freeway traffic control is proposed. It is aimed at reducing the communication efforts and the computation times in a large network. This new algorithm can coordinate a large number of on-ramps throughout a freeway network in a partially cooperative scheme. The communication is performed between neighboring on-ramps in a special serial fashion and with three different proposed cooperative schemes. The computation time is much less than that of existing distributed MPC approaches in the literature, while achieving a performance close to the one of the centralized MPC method. To evaluate the performance of the proposed partially cooperative schemes, a freeway network case study is selected and the problem of coordination between several on-ramps is solved using different methods from a centralized approach to a fully decentralized one. The obtained results show a significant decrease in the total computation time with respect to the centralized and fully cooperative schemes, while maintaining a close distance to the optimal objective function obtained from the centralized case. Furthermore, the performance of the proposed partially cooperative MPC method is evaluated in the case of incidents in the network.

State reconstructor for real-time freeway ramp metering

The work presented in this paper aims to solve the problem of isolated ramp metering in the case of unavailable (not measured) traffic state variables (density and mean speed). A state reconstructor is then proposed and a systematic approach is developed for real time freeway ramp metering. The state reconstructor is developed using a second order sliding mode observer, while the control algorithm is based on the concept of differential flatness. Numerical simulations demonstrate the relevance of the provided algorithm for both state reconstructor and control of freeway networks.

Real-time dynamic traffic routing using variable structure control

In this paper, we present a new algorithm to deal with the real-time dynamic traffic routing (DTR) problem using a second order traffic flow model (METANET). We investigate variable structure control (VSC) as a high-speed switched feedback control resulting in sliding mode. The control objective is to minimize the difference of the travel times on alternate routes in a network setting. Accordingly, the congestion could be reduced/eliminated. The relevance of the proposed algorithm is demonstrated via a set of numerical simulations in the case of the same as well as different geometric conditions.

Macroscopic Traffic Flow Control Via State Estimation

Abstract The studies presented in this paper deal with traffic control in case of missing data and/or when the loop detectors are faulty. We show that the traffic state estimation plays an important role in traffic prediction and control. Two approaches are presented for the estimation of the main traffic variables (traffic density and mean speed). The state constructors obtained are then used for traffic flow control. Several numerical simulations show very promising results for both traffic state estimation and control.