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access icon free On a spatiotemporally discrete urban traffic model

  • Author(s): Shu Lin 1, 2, 3 ; Bart De Schutter 4 ; Andreas Hegyi 5 ; Yugeng Xi 2, 3 ; Hans Hellendoorn 3
    • View affiliations
    • Affiliations: 1: School of Computer and Control Engineering, University of Chinese Academy of Sciences, No. 80 ZhongGuanCunDongLu, HaiDian, Beijing 100190, People's Republic of China;
      2: Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China;
      3: Key Laboratory of System Control and Information Processing, Ministry of Education of China, No. 800 Dongchuan Road, Minhang District, Shanghai 200240, People's Republic of China;
      4: Delft Center for Systems and Control, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands;
      5: Department of Transport and Planning, Delft University of Technology, PO Box 5048, 2600 GA Delft, The Netherlands
  • Source: Volume 8, Issue 3, May 2014, p. 219 – 231
    DOI:  10.1049/iet-its.2012.0137 , Print ISSN 1751-956X, Online ISSN 1751-9578
© The Institution of Engineering and Technology
Received 08/09/2012, Accepted 18/06/2013, Revised 20/05/2013, Published 16/08/2013

In order to control urban traffic with model-based control methods, a proper traffic model is very important. This traffic control model needs to have enough descriptive power to reproduce relevant traffic phenomena, and it also has to be fast enough to be used in practice. Consequently, macroscopic urban traffic flow models are usually applied as control models. In this study, a macroscopic spatiotemporally discrete urban traffic model with a variable sampling time interval is proposed for model-based control strategies. By selecting proper sampling time intervals and sampling space distances, it allows us to balance modelling accuracy and computational complexity of the spatiotemporally discrete model. In addition, an urban traffic Courant–Friedrichs–Lewy (CFL) condition is deduced for spatiotemporally discrete urban traffic models, which is a sufficient condition to guarantee the discrete model to bear enough descriptive modelling power to reproduce necessary traffic phenomena. The model is analysed and evaluated based on the model requirements for control purposes. The simulation results are compared for the situations where the CFL condition is violated and not violated.

Inspec keywords: sampling methods; spatiotemporal phenomena; road traffic control; computational complexity

Other keywords: descriptive modelling power; CFL condition; sampling space distances; macroscopic spatiotemporally discrete urban traffic control model; urban traffic Courant-Friedrichs-Lewy condition; variable sampling time interval; modelling accuracy; computational complexity; model-based control method; sufficient condition; traffic phenomena

Subjects: Road-traffic system control; Computational complexity; Other topics in statistics

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