TY - GEN
T1 - Multi-Thread State Update Schemes for Microscopic Traffic Simulation
AU - Tan, Wen Jun
AU - Andelfinger, Philipp
AU - Cai, Wentong
AU - Knoll, Alois
AU - Xu, Yadong
AU - Eckhoff, David
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/14
Y1 - 2020/12/14
N2 - Microscopic traffic simulation is an essential tool for the evaluation of intelligent transportation systems (ITS). With the increasing complexity of ITS applications, higher-detail simulation models, and the need to analyze large-scale scenarios, simulation run-times can grow exceedingly large. One way to counter this problem is the use of parallel computing techniques, such as shared-memory multi-thread parallelism. While the foundations of parallel traffic simulation are well-known, the effects of different synchronization and agent-update mechanisms on simulation performance have not been explored systematically. In this paper, we first analyze the common properties of models used in microscopic traffic simulation to understand the impact of their data dependencies. We discuss synchronous and asynchronous agent update schemes and compare them in terms of performance and requirements. We conclude that although it requires more memory and additional conflict handling, the synchronous agent-state updating approach is favourable in terms of scalability.
AB - Microscopic traffic simulation is an essential tool for the evaluation of intelligent transportation systems (ITS). With the increasing complexity of ITS applications, higher-detail simulation models, and the need to analyze large-scale scenarios, simulation run-times can grow exceedingly large. One way to counter this problem is the use of parallel computing techniques, such as shared-memory multi-thread parallelism. While the foundations of parallel traffic simulation are well-known, the effects of different synchronization and agent-update mechanisms on simulation performance have not been explored systematically. In this paper, we first analyze the common properties of models used in microscopic traffic simulation to understand the impact of their data dependencies. We discuss synchronous and asynchronous agent update schemes and compare them in terms of performance and requirements. We conclude that although it requires more memory and additional conflict handling, the synchronous agent-state updating approach is favourable in terms of scalability.
UR - https://www.scopus.com/pages/publications/85103908787
U2 - 10.1109/WSC48552.2020.9383962
DO - 10.1109/WSC48552.2020.9383962
M3 - Conference contribution
AN - SCOPUS:85103908787
T3 - Proceedings - Winter Simulation Conference
SP - 182
EP - 193
BT - Proceedings of the 2020 Winter Simulation Conference, WSC 2020
A2 - Bae, K.-H.
A2 - Feng, B.
A2 - Kim, S.
A2 - Lazarova-Molnar, S.
A2 - Zheng, Z.
A2 - Roeder, T.
A2 - Thiesing, R.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Winter Simulation Conference, WSC 2020
Y2 - 14 December 2020 through 18 December 2020
ER -