MATEC Web Conf.
Volume 81, 20162016 5th International Conference on Transportation and Traffic Engineering (ICTTE 2016)
|Number of page(s)||6|
|Section||Transportation System Modeling and Forecasting|
|Published online||25 October 2016|
Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling
1 Faculty of Electrical Engineering, University of Tuzla, 75000 Tuzla, Bosnia and Herzegovina
2 Magicsoft, 75000 Tuzla, Bosnia and Herzegovina
3 Leftor, 75000 Tuzla, Bosnia and Herzegovina
4 IVL, 75000 Tuzla, Bosnia and Herzegovina
Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS), since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS). The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS) prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error), coefficient of determination (R2) and Pearson coefficient (r), were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.