Name
Abstract | ||
|---|---|---|
Microscopic traffic simulation is the most accurate tool for predictive analytics in urban environments. However, the amount of workload (i.e., cars simulated simultaneously) can be challenging for classical systems, particularly for scenarios requiring faster than real-time processing (e.g., for emergency units having to make quick decisions on traffic management). This challenge can be tackled with distributed simulations by sharing the load between simulation engines running on different computing nodes, hence balancing the processing power required. This paper studies the performance of dSUMO, i.e., a distributed microscopic traffic simulator. dSUMO is fully decentralized and can dynamically balance the workload between its computing nodes, hence showing important improvements against classical, centralized and not dynamic, solutions. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TITS.2016.2603171 | IEEE Trans. Intelligent Transportation Systems |
Keywords | Field | DocType |
Load modeling,Vehicles,Synchronization,Computational modeling,Vehicle dynamics,Heuristic algorithms,Microscopy | Dynamic programming,Synchronization,Information processing,Computer science,Workload,Simulation,Predictive analytics,Traffic simulation,Real-time computing,Vehicle dynamics,Systems architecture,Distributed computing | Journal |
Volume | Issue | ISSN |
18 | 5 | 1524-9050 |
Citations | PageRank | References |
3 | 0.39 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Quentin Bragard | 1 | 9 | 1.25 |
| Anthony Ventresque | 2 | 108 | 17.08 |
| Liam Murphy | 3 | 811 | 74.94 |