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Network traffic flow optimization under performance constraints
Institution:1. Institute for Computer Science and Control, Hungarian Academy of Sciences, Budapest, Hungary;2. Department of Signals and Systems, Chalmers University of Technology, Gothenburg, Sweden;3. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, Espoo, Finland;4. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA;1. Delft University of Technology, Faculty of Civil Engineering, Department of Transport and Planning, Stevinweg 1, 2628 CN, Delft, The Netherlands;2. Toyota Motor Europe, Technical Center, Hoge Wei 33, 1930 Zaventem, Belgium;1. Dynamic Systems and Simulation Laboratory, School of Production Engineering and Management, Technical University of Crete, 73100, Chania, Greece;2. Department of Civil and Infrastructure Engineering, Technological Educational Institute of Athens, 12210, Egaleo, Athens, Greece;1. Institute for Computer Science and Control, Hungarian Academy of Sciences, Kende utca 13-17, H-1111 Budapest, Hungary;2. Budapest University of Technology and Economics, Department of Control for Transportation and Vehicle Systems, Stoczek utca 2., H-1111 Budapest, Hungary;1. Institute for Computer Science and Control, Hungarian Academy of Sciences, Budapest, Hungary;2. Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
Abstract:In this paper, a model-based perimeter control policy for large-scale urban vehicular networks is proposed. Assuming a homogeneously loaded vehicle network and the existence of a well-posed Network Fundamental Diagram (NFD), we describe a protected network throughout its aggregated dynamics including nonlinear exit flow characteristics. Within this framework of constrained optimal boundary flow gating, two main performance metrics are considered: (a) first, connected to the NFD, the concept of average network travel time and delay as a performance metric is defined; (b) second, at boundaries, we take into account additional external network queue dynamics governed by uncontrolled inflow demands. External queue capacities in terms of finite-link lengths are used as the second performance metric. Hence, the corresponding performance requirement is an upper bound of external queues. While external queues represent vehicles waiting to enter the protected network, internal queue describes the protected network’s aggregated behavior.By controlling the number of vehicles joining the internal queue from the external ones, herewith a network traffic flow maximization solution subject to the internal and external dynamics and their performance constraints is developed. The originally non-convex optimization problem is transformed to a numerically efficiently convex one by relaxing the performance constraints into time-dependent state boundaries. The control solution can be interpreted as a mechanism which transforms the unknown arrival process governing the number of vehicles entering the network to a regulated process, such that prescribed performance requirements on travel time in the network and upper bound on the external queue are satisfied. Comparative numerical simulation studies on a microscopic traffic simulator are carried out to show the benefits of the proposed method.
Keywords:Traffic control  Traffic flow  Perimeter control  Network fundamental diagram  Travel time
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