Literature Database Entry


Sanket Gupte and Mohamed Younis, "Vehicular Networking for Intelligent and Autonomous Traffic Management," Proceedings of IEEE International Conference on Communications (ICC 2012), Ottawa, Canada, June 2012, pp. 5306-5310.


Traffic congestion has become a daily problem that most people suffer. This not only impacts the productivity of the population but also poses a safety risk. Most of the technologies for intelligent highways focus on safety measures and increased driver awareness, and expect a centralized management for the traffic flow. This paper presents a new approach for enabling autonomous and adaptive traffic management through vehicular networks. By allowing data exchange between vehicles about route choices, congestions and traffic alerts, a vehicle makes a decision on the best course of action. Unlike centralized schemes that provide recommendations, our VANET-based Autonomous Management (VAM) approach factors in the destination and routes of nearby vehicles in deciding on whether rerouting is advisable. In addition, VAM leverages the presence of smart traffic lights and enables coordination between vehicles and light-controllers in order to ease congestion. The collective effect of all vehicles will be an autonomous reshape of the traffic pattern based on their destinations and road conditions. The simulation results demonstrate the advantage of VAM.

Quick access

Original Version DOI (at publishers web site)
BibTeX BibTeX


Sanket Gupte
Mohamed Younis

BibTeX reference

    address = {Ottawa, Canada},
    author = {Gupte, Sanket and Younis, Mohamed},
    booktitle = {IEEE International Conference on Communications (ICC 2012)},
    doi = {10.1109/ICC.2012.6364617},
    issn = {1938-1883},
    month = {6},
    pages = {5306-5310},
    publisher = {IEEE},
    title = {{Vehicular Networking for Intelligent and Autonomous Traffic Management}},
    year = {2012},

Copyright notice

Links to final or draft versions of papers are presented here to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or distributed for commercial purposes without the explicit permission of the copyright holder.

The following applies to all papers listed above that have IEEE copyrights: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

The following applies to all papers listed above that are in submission to IEEE conference/workshop proceedings or journals: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

The following applies to all papers listed above that have ACM copyrights: ACM COPYRIGHT NOTICE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or

The following applies to all SpringerLink papers listed above that have Springer Science+Business Media copyrights: The original publication is available at

This page was automatically generated using BibDB and bib2web.