An ad hoc distributed dynamic data-driven simulation is a collection of autonomous online simulations brought together to model an operational system. They offer the potential of increased accuracy, responsiveness, and robustness compared to centralized approaches. They differ from conventional distributed simulations in that they are created bottom-up rather than top-down. They combine concepts from conventional distributed simulations and replicated trials, raising new issues in data management and synchronization. In this article, the ad hoc simulation approach and an optimistic synchronization algorithm are proposed. A prototype coupling in-vehicle transportation simulation is evaluated and shown to yield results comparable to a traditional replicated experiment for the tested scenarios. Experiences applying this concept to a commercial transportation simulator in an emergency scenario are described.
Werner, J.2005. Details of the VII Initiative `Work in Progress' Provided at Public Meeting. www.ntoctalks.com/icdn/vii_pubmtg_v1.php (accessed April 15 2005).
2.
Broadhurst, A., S. Baker, and T. Kanade.2005. Monte Carlo Road Safety Reasoning. In IEEE Intelligent Vehicles Symposium2005, 319-324.
3.
Innamaa, S. , and I. Kosonen.2004. Online Traffic Models - A Learning Experience. Traffic Engineering & Control , 45(9), 338-343.
4.
Wang, H.L. , and R.L. Cheu.2004. Dynamic Routing Decisions For Commercial Vehicle Operations in Real-Time Traffic Conditions . Transportation Research Record, 1882, 201-209.
5.
Hafstein, S., R. Chrobok, A. Pottmeier, M. Schreckenberg, and F.C. Mazur.2004. A High-Resolution Cellular Automata Traffic Simulation Model with Application in a Freeway Traffic Information System. Computer-Aided Civil and Infrastructure Engineering, 19(5), 338-350.
6.
Nishikawa, I., S. Nakazawa, and H. Kita.2003. Area-Wide Control of Traffic Signals by a Phase Model. Transactions of the Society of Instrument & Control Engineers, 39(2), 199-208.
7.
Darema, F.2004. Dynamic Data Driven Applications Systems: A New Paradigm for Application Simulations and Measurements. In International Conference on Computational Science, 662- 669.
8.
Plale, B., D. Gannon, and D. Reed.2005. Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD. In International Conference on Computational Science, 624-631.
9.
Mandel, J., L.S. Bennethum, and M. Chen.2005. Towards a Dynamic Data Driven Application System for Wildfire Simulation. In International Conference on Computational Science, 632-639.
10.
Golubchik, L. , D. Caron, and A. Das .2006. A Generic Multi-scale Modeling Framework for Reactive Observing Systems: An Overview. In International Conference on Computational Science, 514-521.
11.
Kennedy, C., and G. Theodoropoulos .2006. Intelligent Management of Data Driven Simulations to Support Model Building in the Social Sciences. In International Conference on Computational Science, 562-569.
12.
Brogan, D., P. Reynolds, Jr., and R. Bartholet.2005. Semi-Automated Simulation Transformation for DDDAS. In International Conference on Computational Science, 721-728.
13.
Lendermann, P. , M.Y.H. Low , B.P. Gan , N. Julka, L.P. Chan, S.J.E. Taylor, S.J. Turner, W. Cai , X. Wang, T. Hung, L.F. McGinnis, and S. Buckley.2005. An Integrated and Adaptive DecisionSupport Framework for High-Tech Manufacturing and Service Networks. In Proceedings of the 2005 Winter Simulation Conference, 2052-2062.
14.
Mahmassani, H.2007. Development and Testing of a Real-Time Traffic Estimation and Prediction System. www.mti.umd.edu/people/mahmassani/research/Research_descriptions_HSM_website_10%2004.pdf (accessed September 15 2007).
15.
MIT, 2007, M.I.T.S.P. DynaMIT . MIT.
16.
Park, B., J. Lee, D.M. Pampati, and B.L. Smith.2007. Online Implementation of DynaMIT: A Prototype Traffic Estimation and Prediction Program. In 86th TRB Annual Meeting.
Song, H., and Y. Lin.2007. DynaCHINA: A Specially-Built Real-Time Traffic Prediction System for China. In 86th TRB Annual Meeting.
19.
Jefferson, J.1985. Virtual Time. ACM Transactions on Programming Languages and Systems, 7(3), 404-425.
20.
Rao, D.M. , N.V. Thondugulam, R. Radhakrishnan, and P.A. Wilsey.1998. Unsynchronized Parallel Discrete Event Simulation. In Proceedings of the Winter Simulation Conference, 1563-1570.
21.
Fujimoto, R.M.1999. Exploiting Temporal Uncertainty in Parallel and Distributed Simulations. In Proceedings of the Workshop on Parallel and Distributed Simulation, 46-53.
22.
Fujimoto, R.M.1989. The Virtual Time Machine . In International Symposium on Parallel Algorithms and Architectures, 199- 208.
23.
Esser, J. , and M. Schreckenberg.1997. Microscopic Simulation of Urban Traffic Based on Cellular Automata. International Journal of Modern Physics C, 8(5), 1025-1036.
24.
PTV.2005 . VISSIM User Manual 4.10. PTV Planung Transport Verkehr AG: Karlsruhe, Germany.
25.
PTV.2006 . User Manual for the VISSIM COM Interface, VISSIM 4.10-12. PTV Planung Transport Verkehr AG: Karlsruhe, Germany.
