A Decentralized Weighted Vote Traffic Congestion Detection Framework for ITS

Yang Song, Zhuzhu Wang, Junwei Zhang, Zhuo Ma, Jianfeng Ma

Abstract: With the rapid development of Internet of Vehicles (IoV), the applications of traffic congestion detection based on Intelligent Traffic System (ITS) are proposed and widely used. However, location privacy leakage has become a serious problem in traffic congestion detection based on traffic voting, because vehicles will upload traffic congestion information and their own locations to the traffic management server. In this paper, we propose a decentralized weighted vote traffic congestion detection framework, which allows vehicles can safely participate in the traffic voting, under location privacy protection, and accurately obtain the traffic congestion status of the road. Specifically, we introduce blockchain technology into traffic congestion detection, and apply smart contract to replace the traditional trusted third party. We propose a weighted voting scheme, and set the weight of votes depending on the distance between the vehicle’s current position and the location of congestion. The security analysis result shows that our framework can satisfy the above requirements. Finally, the experiment results demonstrate that our framework is efficient and practical.