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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Perumalla, K.S. |
| Copyright Year | 2006 |
| Description | Author affiliation: Oak Ridge Nat. Lab., TN (Perumalla, K.S.) |
| Abstract | Emerging needs in transportation network modeling and simulation are raising new challenges with respect to scalability of network size and vehicular traffic intensity, speed of simulation for simulation-based optimization, and fidelity of vehicular behavior for accurate capture of event phenomena. Parallel execution is warranted to sustain the required detail, size and speed. However, few parallel simulators exist for such applications, partly due to the challenges underlying their development. Moreover, many simulators are based on time-stepped models, which can be computationally inefficient for the purposes of modeling evacuation traffic. Here an approach is presented to designing a simulator with memory and speed efficiency as the goals from the outset, and, specifically, scalability via parallel execution. The design makes use of discrete event modeling techniques as well as parallel simulation methods. Our simulator, called SCATTER, is being developed, incorporating such design considerations. Preliminary performance results are presented on benchmark road networks, showing scalability to one million vehicles simulated on one processor |
| Starting Page | 1500 |
| Ending Page | 1507 |
| File Size | 398214 |
| Page Count | 8 |
| File Format | |
| ISBN | 1424405009 |
| DOI | 10.1109/WSC.2006.322919 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-03 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Discrete event simulation Traffic control Computational modeling Telecommunication traffic Scattering Scalability Road vehicles Kinetic theory Road transportation Laboratories |
| Content Type | Text |
| Resource Type | Article |
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