Name
Abstract | ||
|---|---|---|
In this paper, we propose a self-adaptive mechanism for traffic regulation based on cooperative agents. We focus our study on the intersection behaviour, using intelligent agents to represent the infrastructure elements, which cooperate among each other in order to minimize traffic congestion. While the agents are capable of cooperating among themselves, the cooperative behaviour is not pre-defined, as it emerges from the agent interactions at a local level. We also explain our results from simulation experiments involving the proposed mechanism, comparing it with other traffic congestion regulation systems currently in use. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.procs.2019.04.061 | Procedia Computer Science |
Keywords | Field | DocType |
MAS,Self-adaptation,Traffic regulation,AVT | Intelligent agent,Traffic regulation,Computer science,Multi-agent system,Artificial intelligence,Machine learning,Traffic congestion,Distributed computing | Conference |
Volume | ISSN | Citations |
151 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Assia Belbachir | 1 | 4 | 5.17 |
| Amal El Fallah-Seghrouchni | 2 | 443 | 53.60 |
| Arthur Casals | 3 | 2 | 2.06 |
| Marcia Pasin | 4 | 0 | 3.72 |