scholarly journals Safety effect analysis of motorcycle V2I collision warning system

2021 ◽  
Author(s):  
Tien‐Pen Hsu ◽  
Ku‐Lin Wen ◽  
Chin‐Hung Liu
Keyword(s):  
Warning System ◽  
Effect Analysis ◽  
Collision Warning ◽  
Safety Effect

scholarly journals Key Parameters Estimation and Adaptive Warning Strategy for Rear-End Collision of Vehicle

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Xiang Song ◽  
Xu Li ◽  
Weigong Zhang
Keyword(s):  
Field Tests ◽  
Warning System ◽  
Time Estimation ◽  
Adaptive Strategy ◽  
Parameters Estimation ◽  
Collision Warning ◽  
Variable Threshold ◽  
Luenberger Observer ◽  
Safety Distance ◽  
Driving Conditions

The rear-end collision warning system requires reliable warning decision mechanism to adapt the actual driving situation. To overcome the shortcomings of existing warning methods, an adaptive strategy is proposed to address the practical aspects of the collision warning problem. The proposed strategy is based on the parameter-adaptive and variable-threshold approaches. First, several key parameter estimation algorithms are developed to provide more accurate and reliable information for subsequent warning method. They include a two-stage algorithm which contains a Kalman filter and a Luenberger observer for relative acceleration estimation, a Bayesian theory-based algorithm of estimating the road friction coefficient, and an artificial neural network for estimating the driver’s reaction time. Further, the variable-threshold warning method is designed to achieve the global warning decision. In the method, the safety distance is employed to judge the dangerous state. The calculation method of the safety distance in this paper can be adaptively adjusted according to the different driving conditions of the leading vehicle. Due to the real-time estimation of the key parameters and the adaptive calculation of the warning threshold, the strategy can adapt to various road and driving conditions. Finally, the proposed strategy is evaluated through simulation and field tests. The experimental results validate the feasibility and effectiveness of the proposed strategy.

A Novel Method for Tramcar Anti-Collision Warning System Based on Monocular Vision

2012 ◽  
Vol 430-432 ◽  
pp. 1871-1876
Author(s):  
Hui Bo Bi ◽  
Xiao Dong Xian ◽  
Li Juan Huang
Keyword(s):  
Software Design ◽  
Early Warning System ◽  
Warning System ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Monocular Vision ◽  
System Construction ◽  
Collision Warning ◽  
Lane Width ◽  
Novel Method

For the problem of tramcar collision accident in coal mine underground, a monocular vision-based tramcar anti-collision warning system based on ARM and FPGA was designed and implemented. In this paper, we present an improved fast lane detection algorithm based on Hough transform. Besides, a new distance measurement and early-warning system based on the invariance of the lane width is proposed. System construction, hardware architecture and software design are given in detail. The experiment results show that the precision and speed of the system can satisfy the application requirement.

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