Realization of head-on collision warning system at intersections-DSSS: driving safety support systems

Vehicle collision warning system can determine the relative distance and speed between target vehicle and the front vehicle by monocular vision positioning technique from automobile license plate image captured by camera so as to judge danger level and remind the driver to make appropriate action and avoid vehicle collision timely. Study on the positioning technology of this system aims to help the driver to judge and improve driving safety. Thus, the system has a broad application prospect. The research content of this paper could enrich and supply PNL visual locating method, endowing with significance of theoretical research. The paper proposes an improved vehicle measuring method based on monocular vision for vehicle license plate. This method combines the characteristics of fast speed for analytical solution method and high positioning accuracy for iterative solution method, therefore has a high robustness and overcomes the multi-solution problem of P3P iterative method. The simulation experiments show that localization precision of the improved positioning method has been improved greatly as compared with P4L method. At the same time, the real-time characteristic of collision avoidance warning system with improved visual locating method has been improved a lot, and the new location algorithm has good performance in real-time characteristic, which greatly improve the processing ability of the system for images.

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Robustness Analysis of License Plate Visual Positioning Method in Vehicle Collision Warning System

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s021800141750001x ◽

2017 ◽

Vol 31 (01) ◽

pp. 1750001 ◽

Cited By ~ 1

Author(s):

Lijuan Qin ◽

Ting Wang

Keyword(s):

Robustness Analysis ◽

Warning System ◽

Driving Safety ◽

License Plate ◽

Positioning Accuracy ◽

Robust Analysis ◽

Collision Warning ◽

Location Method ◽

Visual Positioning ◽

Positioning Method

Vehicle anti-collision warning system is a key research area of vehicle safety. It is also a necessary means to enhance driving safety and reduce traffic accidents. The visual location method is presented for this system based on license plate image. This method realizes visual positioning with the help of the mounting points of license plate. At the same time, the feasible robust analysis method is proposed for the visual positioning method with license plate frame image. Finally, the robust analysis determines good angles for commutating rotation parameter in the method of license plate image visual positioning. At the same time, it determines good angles for translation parameter and for rotation and translation transform. Therefore, robust analysis determines positions where the visual positioning method has high positioning accuracy. Robust analysis for license plate vision positioning method is useful in analysis of high positioning accuracy positions for the proposed license plate image visual location method combined with plate mounting points. The research content of this paper is beneficial to driver decision-making and improves the safety of collision warning system and intelligent vehicle.

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Study on Safe Distance for the Automotive Collision Warning System Based on Human-Vehicle-Environment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.533.375 ◽

2014 ◽

Vol 533 ◽

pp. 375-379

Author(s):

Feng Ping Cao

Keyword(s):

Warning System ◽

Calculation Model ◽

Driving Safety ◽

Simulation Experiments ◽

Collision Warning ◽

Automobile Safety ◽

Safety Distance ◽

System A ◽

Distance Model ◽

Braking Process

In order to improve the effectiveness and practicability of the car anti-collision system, a model of the safety distance between two cars took into account human, vehicle and environment was presented in the paper. Firstly, a general automobile safety distance calculation model based on the braking process was derived, and an algorithm of estimating safe running state on vehicle was presented, which includes the comprehensive factors that influence the vehicle safety travel. Then the general automobile safety distance model was corrected and regulated according to the state of driving safety. At last, the method was verified by the simulation experiments. Experimental results indicate that the algorithm was more consistent with the driver individual characteristic and the actual situation of vehicle and road, and the driver had the most impact.

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Driving safety field theory modeling and its application in pre-collision warning system

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2016.10.003 ◽

2016 ◽

Vol 72 ◽

pp. 306-324 ◽

Cited By ~ 50

Author(s):

Jianqiang Wang ◽

Jian Wu ◽

Xunjia Zheng ◽

Daiheng Ni ◽

Keqiang Li

Keyword(s):

Field Theory ◽

Warning System ◽

Driving Safety ◽

Collision Warning

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Effect of Warning System on Interactive Driving Behavior at Unsignalized Intersection under Fog Conditions: A Study Based on Multiuser Driving Simulation

Journal of Advanced Transportation ◽

10.1155/2020/8871875 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Yunfan Zhang ◽

Xuedong Yan ◽

Jiawei Wu ◽

Ke Duan

Keyword(s):

Collision Avoidance ◽

Warning System ◽

Driving Behavior ◽

Driving Simulation ◽

Driving Safety ◽

Collision Warning ◽

Action Point ◽

Increased Risk ◽

Simulation Scenario ◽

Further Development

The intersection collision warning system (ICWS) is an emerging technology designed to assist drivers in avoiding collisions at intersections. ICWS has an excellent performance in reducing the number of collisions and improving driving safety. Previous studies demonstrated that when visibility was low under fog conditions, ICWS could help drivers timely detect hazardous conflicting vehicles. However, the influences of ICWS on interactive driving behavior at unsignalized intersection between different vehicles have barely been discussed. This study aimed to investigate the patterns of drivers’ interactive behaviors with the assistance of a new kind of ICWS under fog conditions based on Multiuser Driving Simulation. The Multiuser Driving Simulation allowed multiple drivers to operate in the same simulation scenario at the same time, and it could capture drivers’ interactions preferably. Forty-eight licensed drivers completed the driving simulation experiment in three fog conditions (no fog, light fog, and heavy fog) and two warning conditions (warning and no warning), in which the drivers drove in a straight-moving situation at unsignalized intersection with potential collision risks caused by the encounter of two vehicles. The results verified that warning and fog conditions were significant factors that affected the interactive driving behavior in the unsignalized intersection collision avoidance process, including the driver’s decision, TTC of action point, average acceleration (deceleration) rate, and postencroachment time. Compared to conditions without ICWS, the ICWS could help drivers make collision avoidance actions earlier and change the speed more smoothly. In addition, with the help of Multiuser Driving Simulation, associations between decision driving behaviors of vehicles were discussed with caution. The results revealed the decision-making mechanism of drivers in the process of interaction with other drivers. Under the influence of fog, interactive driving processes were fraught with increased risk at unsignalized intersection. However, the ICWS helped drivers interact more harmoniously, safely, and efficiently. The findings shed some light on the further development of ICWS and the study on interactive driving behavior.

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