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| Content Provider | IET Digital Library |
|---|---|
| Author | Perez, Antonio Guillen Cano, Maria Dolores |
| Abstract | The incorporation of Artificial Intelligence algorithms in Intelligent Transportation Systems gives rise to new opportunities for a more sustainable urban mobility. However, one of the main challenges is to decide when and where these techniques should be applied; several options appear, such as cloud computing, fog computing, edge computing, or even edge devices. In this paper, an Internet of Things‐based solution for smart traffic management is presented. Using the lightweight Random Early Detection for Vehicles Dynamic mechanism as a basis, we optimize using evolutionary algorithms. Random Early Detection for Vehicles Dynamic can be applied in signaled intersections to proactively detect incipient congestion and set the best cycle and phases of traffic lights. Then, the authors demonstrate that once Random Early Detection for Vehicles Dynamic has been appropriately optimised offline, it can be later used in unknown traffic scenarios without the burden of applying Artificial Intelligence in constrained Internet of Things devices. The performance of this mechanism is widely tested with the SUMO simulation tool. Results show that this improved version, called iREDVD, notably reduces the vehicles’ waiting time, average trip time, fuel consumption, and emission of particles and gaseous pollutants compared with other proposals. This work was supported by the AEI/FEDER, UE project grant TEC2016‐76465‐C2‐1‐R (AIM), by DGT‐Ministerio del Interior, project grant SPIP2017‐02230 (STREET), and by a pre‐doctoral contract for the formation of the research personnel financed by Consejería de Empleo, Universidades, Empresa y Medio Ambiente of the CARM, through the Fundación Séneca ‐ Agencia de Ciencia y Tecnología of the Region of Murcia, Spain. |
| Starting Page | 273 |
| Ending Page | 285 |
| Page Count | 13 |
| Volume Number | 15 |
| e-ISSN | 17519578 |
| Issue Number | Issue 2, Feb (2021) |
| Alternate Webpage(s) | https://ietresearch.onlinelibrary.wiley.com/toc/17519578/2021/15/2 |
| Alternate Webpage(s) | https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/itr2.12021 |
| Journal | IET Intelligent Transport Systems |
| Publisher Date | 2021-01-05 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Content Type | Text |
| Resource Type | Article |
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