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FuzzyJam: Reducing traffic jams using a fusion of fuzzy logic and vehicular networks

Title
FuzzyJam: Reducing traffic jams using a fusion of fuzzy logic and vehicular networks
Authors
Won, MyounggyuPark, TaejoonSon, Sang H.
DGIST Authors
Won, Myounggyu; Park, Taejoon; Son, Sang H.
Issue Date
2014
Citation
2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, 1869-1875
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
Abstract
Traffic congestion is a growing problem worldwide causing time/fuel waste, pollution, and even stress. Various approaches have been proposed to reduce traffic jams. Recently, researchers have started to employ connected vehicle (CV) technology. Most solutions, however, rely on a binary approach to determine a traffic jam, i.e., whether it exists or not. Accordingly, output given to a driver in the form of driving advisory also tends to be binary and static. However, a traffic jam is a dynamic phenomenon, the intensity of which changes over time depending on various factors including randomness of driving behavior and road conditions. In this paper, we propose to integrate a fuzzy inference system into a traffic-jam-control algorithm such that the dynamics of a traffic jam is effectively represented, thereby providing diversified driving advisory depending upon the intensity of a traffic jam. Through simulations, it is shown that the integrated approach reduces traffic delay by up to 6.5% compared with the state-of-the-art solution. © 2014 IEEE.
URI
http://hdl.handle.net/20.500.11750/3747
DOI
10.1109/ITSC.2014.6957965
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • Author Son, Sang Hyuk RTCPS(Real-Time Cyber-Physical Systems Research) Lab
  • Research Interests
Files:
There are no files associated with this item.
Collection:
Information and Communication EngineeringETC2. Conference Papers
School of Undergraduate Studies2. Conference Papers


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