Efficient calibration techniques for large-scale traffic simulators

Road transportation simulators are increasingly used by transportation stakeholders around the world for the analysis of intricate transportation systems. Model calibration is a crucial prerequisite for transportation simulators to reliably reproduce and predict traffic conditions. This paper considers the calibration of transportation simulators. The methodology is suitable for a broad family of simulators. Its use is illustrated with stochastic and computationally costly simulators. The calibration problem is formulated as a simulation-based optimization (SO) problem. The authors propose a metamodel approach. The analytical metamodel combines information from the simulator with information from an analytical differentiable and tractable network model that relates the calibration parameters to the simulation-based objective function. The proposed algorithm is validated by considering synthetic experiments on a toy network. It is then used to address a calibration problem with real data for a large-scale network: the Berlin metropolitan network with over 24300 links and 11300 nodes. The performance of the proposed approach is compared to a traditional benchmark method. The proposed approach significantly improves the computational efficiency of the calibration algorithm with an average reduction in simulation runtime until convergence of more than 80%. The results illustrate the scalability of the approach and its suitability for the calibration of large-scale computationally inefficient network simulators.

• Record URL:
  https://doi.org/10.1016/j.trb.2016.12.005
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0191261516302831
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhang, Chao
  • Osorio, Carolina
  • Flötteröd, Gunnar
• Publication Date: 2017-3

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: pp 214-239
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 97
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Calibration; Networks; Optimization; Traffic simulation
• Uncontrolled Terms: Computational efficiency
• Geographic Terms: Berlin (Germany)
• Subject Areas: Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01633915
• Record Type: Publication
• Files: TRIS
• Created Date: May 1 2017 9:36AM