Development of a road traffic state identification method based on image texture features

Author(s):  
Song Chen ◽  
Ande Chang ◽  
Xiansheng Li ◽  
Jing Wang
2019 ◽  
Vol 20 (2) ◽  
pp. 114-122 ◽  
Author(s):  
Asmâa Ouessai ◽  
Mokhtar Keche

Abstract Reliable road traffic state identification systems should be designed to provide accurate traffic state information anywhere and anytime. In this paper we propose a road traffic classification system, based on traffic variables estimated using the second order Divided Difference Kalman Filter (DDKF2). This filter is compared with the Extended Kalman Filter (EKF) using both simulated and real-world dataset of highway traffic. Monte-Carlo simulations indicate that the DDKF2 outperforms the EKF filter in terms of parameters estimation error. The real-word evaluation of the DDKF2 filter in terms of classification rate confirms that this filter is promising for real-world traffic state identification systems.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Ying Wu ◽  
Jikun Liu

AbstractWith the rapid development of gymnastics technology, novel movements are also emerging. Due to the emergence of various complicated new movements, higher requirements are put forward for college gymnastics teaching. Therefore, it is necessary to combine the multimedia simulation technology to construct the human body rigid model and combine the image texture features to display the simulation image in texture form. In the study, GeBOD morphological database modeling was used to provide the data needed for the modeling of the whole-body human body of the joint and used for dynamics simulation. Simultaneously, in order to analyze and summarize the technical essentials of the innovative action, this experiment compared and analyzed the hem stage of the cross-headstand movement of the subject and the hem stage of the 180° movement. Research shows that the method proposed in this paper has certain practical effects.


2014 ◽  
Vol 694 ◽  
pp. 80-84
Author(s):  
Xiao Tong Yin ◽  
Chao Qun Ma ◽  
Liang Peng Qu

The analysis of the unban road traffic state based on kinds of floating car data, is based on the model and algorithm of floating car data preprocessing and map matching, etc. Firstly, according to the characteristics of the different types of urban road, the urban road section division has been carried on the elaboration and optimization. And this paper introduces the method of calculating the section average speed with single floating car data, also applies the dynamic consolidation of sections to estimate the section average velocity.Then the minimum sample size of floating car data is studied, and section average velocity estimation model based on single type of floating car data in the different case of floating car data sample sizes has been built. Finally, the section average speed of floating car in different types is fitted to the section average car speed by the least square method, using section average speed as the judgment standard, the grade division standard of urban road traffic state is established to obtain the information of road traffic state.


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