Conference paper Open Access

Application of Artificial Intelligence Techniques to Traffic Prediction and Route Planning, the vision of TIMON project

E. Osaba; P. Lopez-Garcia; E. Onieva; A.D. Masegosa; L. Serrano; H. Landaluce


Citation Style Language JSON Export

{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.894076", 
  "title": "Application of Artificial Intelligence Techniques to Traffic Prediction and Route Planning, the vision of TIMON project", 
  "issued": {
    "date-parts": [
      [
        2017, 
        6, 
        22
      ]
    ]
  }, 
  "abstract": "<p>TIMON is an European research project under the Horizon 2020 programme. The main objective of<br>\nthis project is to provide real-time services through a web based platform and a mobile APP for drivers,<br>\nVulnerable Road Users (VRUs) and businesses. These services will contribute to increasing drivers<br>\nand VRUs assistance and safety. To provide these services, one of the core technologies developed<br>\ninside TIMON will be the design and development of Artificial Intelligence (AI) techniques for traffic<br>\nprediction and route planning. The DeustoTech-Mobility research group is in charge of this part of the<br>\nproject. The objective of this technical paper is to describe the approach followed in TIMON to<br>\ndevelop traffic congestion prediction and route planning services based on AI techniques and the<br>\nprogress done so far. Additionally, the deployment and the result obtained in the first test done is also<br>\ndetailed in this study.</p>", 
  "author": [
    {
      "family": "E. Osaba"
    }, 
    {
      "family": "P. Lopez-Garcia"
    }, 
    {
      "family": "E. Onieva"
    }, 
    {
      "family": "A.D. Masegosa"
    }, 
    {
      "family": "L. Serrano"
    }, 
    {
      "family": "H. Landaluce"
    }
  ], 
  "id": "894076", 
  "event-place": "Strasbourg, France", 
  "type": "paper-conference", 
  "event": "12th ITS European Congress"
}
72
278
views
downloads
All versions This version
Views 7272
Downloads 278278
Data volume 92.8 MB92.8 MB
Unique views 6969
Unique downloads 249249

Share

Cite as