Speedup of DTA-Based Simulation of Large Metropolises for Quasi Real-Time ITS Applications

The assessment of real-time intelligent transportation system (ITS) applications, such as traffic management and adaptive route guidance systems, requires the use of fast and near real-time dynamic traffic simulation models. Even off-line applications, used for testing planning scenarios, often require fast-enough traffic simulation models that enable the required repetitive simulations. This is even more critical for large-scale networks with millions of vehicles. This paper investigates the speedup of DTA simulation models, using compiler optimizations and parallelism. DynusT as a widely used DTA model was evaluated as a test case, while its results could be generalized because the authors have used real-networks and calibrated them using real data sets in the Greater Toronto and Hamilton Area (GTHA). Extensive testing is performed to evaluate various dimensions for speed-up including: network size, number of processors, various optimization levels and operating systems. The performance results show that compiler optimizations and parallelism allow to: 1) double the speed required for a 4-hour simulation after 12 iterations to reach equilibrium, and 2) bring down the initial simulation time (required for network loading) by 2.5 times, enabling the testing of various real-time ITS applications.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 483-490
  • Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

Filing Info

  • Accession Number: 01601039
  • Record Type: Publication
  • ISBN: 9781467365956
  • Files: TRIS
  • Created Date: May 2 2016 3:21PM