ABSTRACT
With the rapid development of Internet, it is increasingly convenient to obtain real-time traffic condition information, which has greatly stimulated the improvement of urban traffic guidance. Traffic conditions are generally divided into four grades in the existing network platform, which are expressed in different colours. The understanding of traffic condition is still at the level of abstract senses. Therefore, it is difficult to grasp the characteristics of urban traffic. To this end, a new idea is proposed in this paper, and the new idea is to study the urban traffic characteristics based on real-time traffic condition information extraction with image identification technology. With this method, we can not only quantify the abstract traffic condition information, but also solve the loss of traffic condition information. In addition, an instance is analysed in this paper, it shows that it can provide references for urban traffic organization management very well.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes on contributors
Jia Wang received his BS in Information and Computing Science from Changsha University of Science and Technology, Changsha, China in 2003, ME in Transportation Planning and Management from Changsha University of Science and Technology, Changsha, China in 2006, and PhD in Transportation Planning and Management from Central South University, Changsha, China in 2013. Since 2006, he has been a teacher at Changsha University of Science and Technology. His current research interests include urban transit, public transit and comprehensive transportation.
Yang-Lingzhi Yang received her BE in Transportation from Changsha University of Science and Technology, Changsha, China in 2015. Currently, she is a graduate student major in Transportation Planning and Management at Changsha University of Science and Technology.
Shuai Liu received his BE in Transportation from Changsha University of Science and Technology, Changsha, China in 2016. Currently, he is a graduate student major in Transportation Planning and Management at Changsha University of Science and Technology.