In order to evaluate the performance of the proposed urban traffic prediction models, we implement the models to predict traffic amount in Cologne, Germany.
This paper proposes a new dynamic satellite bandwidth allocation technique (Predictive Resource Reservation Access, PRRA) which is based on accurate videoconference traffic prediction.
The experimental evaluations show that this method is effective for predictive complex event processing and it outperforms other popular methods when processing traffic prediction in intelligent transportation systems.
Now, actual traffic prediction – forecasts of congestion levels hours and even days in advance – is on the horizon.
Neural networks have been extensively applied to short-term traffic prediction in the past years.
Motivated by that, in this paper, we propose a network traffic prediction and estimation method respectively.
Also, traffic prediction is utilized for adaptively allocating the bandwidth opportunities.
This approach is practical for general traffic prediction only when there are many such vehicles in the area, relaying information every 10 seconds or so.
One possible example would be using its online mapping and traffic prediction software, called Clearflow, in future versions of Microsoft Auto.
If Bunger's forecasts hold up, traffic prediction and dynamic routing will begin to make an impact in the marketplace within about five years.
Researchers use data science tools to uncover human mobility patterns; new method will improve traffic prediction, urban planning, and other transportation needs.
