Fog-based Intelligent Transportation System for Trafic Light Optimization | [Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences • 2021]

Author(s):

1. Muhammad Rusyadi Ramli: Department of IT Convergence Engineering, Kumoh National Institute of Technology,61 Daehak-ro, Yangho-dong, Gumi, Gyeongsangbuk-do, 39177, Korea

2. Riesa Krisna Astuti Sakir: Department of IT Convergence Engineering, Kumoh National Institute of Technology,61 Daehak-ro, Yangho-dong, Gumi, Gyeongsangbuk-do, 39177, Korea

3. Dong-Seong Kim: Department of IT Convergence Engineering, Kumoh National Institute of Technology,61 Daehak-ro, Yangho-dong, Gumi, Gyeongsangbuk-do, 39177, Korea

Abstract:

This paper presents fog-based intelligent transportation systems (ITS) architecture for trafic light optimization. Specifically, each intersection consists of trafic lights equipped with a fog node. The roadside unit (RSU) node is deployed to monitor the trafic condition and transmit it to the fog node. The trafic light center (TLC) is used to collect the trafic condition from the fog nodes of all intersections. In this work, two trafic light optimization problems are addressed where each problem will be processed either on fog node or TLC according to their requirements. First, the high latency for the vehicle to decide the dilemma zone is addressed. In the dilemma zone, the vehicle may hesitate whether to accelerate or decelerate that can lead to trafic accidents if the decision is not taken quickly. This ifrst problem is processed on the fog node since it requires a real-time process to accomplish. Second, the proposed architecture aims each intersection aware of its adjacent trafic condition. Thus, the TLC is used to estimate the total incoming number of vehicles based on the gathered information from all fog nodes of each intersection. The results show that the proposed fog-based ITS architecture has better performance in terms of network latency compared to the existing solution in which relies only on TLC.

Page(s): 29-35

DOI: DOI not available

Published: Journal: Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences, Volume: 58, Issue: S, Year: 2021

Keywords:

FOG Computing , Smart City , Road Safety , Reduce Gas Emission

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