| Issue |
ITM Web Conf.
Volume 8, 2016
International Conference on Big Data and its Applications (ICBDA 2016)
|
|
|---|---|---|
| Article Number | 01007 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/itmconf/20160801007 | |
| Published online | 22 November 2016 | |
Planning of Autonomous Multi-agent Intersection
1 ITMO University, Department of Secure Information Technology, Kronverkskiy pr., 49, Saint Petersburg, Russia, 197101
2 SPbU, Department of Information Systems in Economy, Universitetskaya emb., 7/9, Saint Petersburg, Russia, 199034
* Corresponding author: wixnin@cit.ifmo.ru
In this paper, we propose a traffic management system with agents acting on behalf autonomous vehicle at the crossroads. Alternatively to existing solutions based on usage of semiautonomous control systems with the control unit, proposed in this paper algorithm apply the principles of decentralized multi-agent control. Agents during their collaboration generate intersection plan and determinate the optimal order of road intersection for a given criterion based on the exchange of information about them and their environment. The paper contains optimization criteria for possible routes selection and experiments that perform in order to estimate the proposed model. Experiment results show that this model can significantly reduce traffic density compared to the traditional traffic management systems. Moreover, the proposed algorithm efficiency increases with road traffic density. Furthermore, the availability of control unit in the system significantly reduces the negative impact of possible failures and hacker attacks.
© Owned by 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.