Name
Abstract | ||
|---|---|---|
Traffic distribution over highways affects several applications and functionalities of traveling vehicles. The level of traffic congestion has been scaled over road networks based on the traffic density, traveling speed or estimated traveling time of the investigated road scenario. These measurements have been used individually or combined with other parameters to indicate the level of the traffic congestion on certain road scenario. In this paper, we propose a context-aware traffic prediction technique. It predicts the context of the highway scenarios in terms of the existence of obstacles, broken vehicles, or entrance/exit points based on the distribution of vehicles' traveling speed. From the experimental study, we can see that the proposed protocol have succeeded to predict the context of the highway. Our results indicate that our propose scheme exhibit good performance based upon an extensive set of simulation experiments. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICC42927.2021.9500986 | IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021) |
Keywords | DocType | ISSN |
Context-Aware, Traffic Prediction, Traffic Distribution, VANETs, Highways | Conference | 1550-3607 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maram Bani Younes | 1 | 63 | 10.84 |
| Boukerche, A. | 2 | 61 | 16.98 |