TY - GEN
T1 - Speedup of DTA-Based Simulation of Large Metropolises for Quasi Real-Time ITS Applications
AU - Koulakezian, Agop
AU - Graydon, Billy
AU - Abdelgawad, Hossam
AU - Abdulhai, Baher
AU - Chiu, Yi Chang
AU - Leon-Garcia, Alberto
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/30
Y1 - 2015/10/30
N2 - 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 we 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.
AB - 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 we 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.
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U2 - 10.1109/ITSC.2015.86
DO - 10.1109/ITSC.2015.86
M3 - Conference contribution
AN - SCOPUS:84950296980
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 483
EP - 490
BT - Proceedings - 2015 IEEE 18th International Conference on Intelligent Transportation Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Conference on Intelligent Transportation Systems, ITSC 2015
Y2 - 15 September 2015 through 18 September 2015
ER -