Abstract
Cooperative driving using connectivity services has been a promising avenue for autonomous vehicles, with the low latency and further reliability support provided by 5th Generation Mobile Network (5G). In this paper, we present an application for lane merge coordination based on a centralised system, for connected cars. This application delivers trajectory recommendations to the connected vehicles on the road. The application comprises of a Traffic Orchestrator as the main component. We apply machine learning and data analysis to predict whether a connected vehicle can successfully complete the cooperative manoeuvre of a lane merge. Furthermore, the acceleration and heading parameters that are necessary for the completion of a safe merge are elaborated. The results demonstrate the performance of several existing algorithms and how their main parameters were selected to avoid over-fitting.
| Original language | English |
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| Title of host publication | 2019 European Conference on Networks and Communications, EuCNC 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 198-203 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728105468 |
| DOIs | |
| Publication status | Published - 1 Jun 2019 |
| Event | 28th European Conference on Networks and Communications, EuCNC 2019 - Valencia, Spain Duration: 18 Jun 2019 → 21 Jun 2019 |
Conference
| Conference | 28th European Conference on Networks and Communications, EuCNC 2019 |
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| Country/Territory | Spain |
| City | Valencia |
| Period | 18/06/2019 → 21/06/2019 |
Keywords
- edge cloud
- intelligent transport system
- Lane merge
- machine learning
- V2X communications