A Visible Light Communications Framework for Intelligent Transportation Systems

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A Visible Light Communications Framework for Intelligent Transportation Systems


In this work, we developed a visible light communication (VLC) framework that can be used for Intelligent Transportation Systems (ITS). ITS has been motivated by the need for reducing traffic congestion and offering better user experience in navigation and location-specific services. Recently, VLC has drawn a great deal of attention in the research community, including the development of new applications for ITS. It would be of great use to enable the traffic lights to be able to talk to the vehicles in their proximity and convey important information about the traffic condition. In this project, we developed a framework that can potentially support infrastructure-to-vehicle (I2V) and vehicle-to-infrastructure (V2I) communication. (In our context the infrastructure refers to traffic lights using VLC.) Specifically, traffic lights will be used to not only to order traffic flow, but also to share some important information to the cars. The developed smart traffic light system can provide information about the traffic conditions several blocks down the road and, in case of accidents, this information would be useful for the driver to detour their original route to help reduce congestion and save time. In order to do that we have developed a transmitter circuitry that is composed of an embedded system and optical electronics. In addition, we have developed the receiver circuitry in which the photodiode along with other circuitry is used for detecting and decoding the VLC signal coming from the traffic lights. We have also developed and experimented in a laboratory with a novel optical code-division multiple-access (CDMA) scheme for overloaded optical CDMA transmission in which the optical codes are uniquely decodable. This new coding system could potentially provide higher data rate in the VLC protocol establishment.



Dr. Hovannes Kulhandjian is an Assistant Professor in the Department of Electrical and Computer Engineering at California State University, Fresno (Fresno State). He joined Fresno State in Fall 2015 as a tenure-track faculty member. Before that, he was an Associate Research Engineer in the Department of Electrical and Computer Engineering at Northeastern University. He received his B.S. degree in Electronics Engineering with high honors from the American University in Cairo (AUC) in 2008, and his MS and PhD degrees in Electrical Engineering from the State University of New York at Buffalo in 2010 and 2014, respectively. His current research interests are in digital signal processing, wireless communications, and networking, with applications to underwater and visible light communications and networking geared towards Intelligent Transpiration Systems (ITS).

Dr. Kulhandjian has received research grants from Fresno State Transportation Institute (FSTI) and he also received the 2020 Claude C. Laval Award for Innovative Technology and Research at Fresno State.

Dr. Kulhandjian is an active member of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE). He is a Senior Member of IEEE. He has served as a Guest Editor for IEEE Access Special Section Journal, Session Co- Chair for IEEE UComms’18 Conference, Session Chair for ACM WUWNet’19 Conference, Publicity Chair for ACM WUWNet’17 Conference. He also serves as a member of the Technical Program Committee (TCP) for ACM and IEEE Conferences such as GLOBECOM 2019, IPCCC 2017, WiMob 2018, WD 2018, ICC 2018, WUWNet 2018, and VTC Fall 2017. He is a recipient of the Outstanding Reviewer Award from ELSEVIER Ad Hoc Networks and ELSEVIER Computer Networks.

August 2020
Intelligent transportation systems (ITS)
Traffic signal control systems
Traffic lights USE
Traffic signal networks



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