Open AccessResearch on road traffic situation awareness system based on image big data
Author(s) -
Yu Zhu,
Yangyang Peng,
Shangzheng Wang,
Shuimeng Shi,
Jun Nan
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032170
Subject(s) - computer science , convolutional neural network , big data , intelligent transportation system , field (mathematics) , transport engineering , macro , floating car data , convolution (computer science) , artificial neural network , artificial intelligence , data mining , engineering , traffic congestion , mathematics , pure mathematics , programming language
to promote the construction of intelligent and information technology in the field of road traffic is conducive to the construction of smart cities and the formulation of macro strategies and construction plans for urban traffic development. In view of the shortcomings of the current road traffic system, based on convolution neural network, situation awareness technology, database and other technologies, using CNN, R-CNN, fast R-CNN and fast R-CNN, this paper constructs a deep convolution neural network model based on the big data of road traffic image, and carries out the system demand analysis and system framework design and implementation. Through the analysis of the actual case and the feedback of the trial, the application effect of the road traffic situation awareness system is illustrated, in order to provide scientific reference and basis for the establishment of modern intelligent transportation system