• Journal of Sensor Science and Technology
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• v.23 no.4
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• pp.259-265
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• 2014

When raining or snowing, windshield wiper system is very important for safety of driver. However, manual wiper system frequently needed to be controlled for sufficient visibility and it was very uncomfortable. So, rain sensor which controls automatically was developed. This rain sensor technology uses optical sensing technique sensed the rainfall by receiving reflected light of rain dropped on the windshield. The technology used optical sensor was simple and easy to implement as a rain sensing system in the car. However, it is sometime shown low accuracy to measure rainfall on the windshield when affected by ambient lights from surroundings. It is also given inconvenience to the driver to control the car. To solving these problems, we propose a rain sensing system using image sensor and the fuzzy wiper control algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.227-235
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• 2018

In this study, we developed a relational formula for observing high - resolution rainfall using vehicle rain sensor. The vehicle rain sensor consists of eight channels. Each channel generates a sensor signal by detecting the amount of rainfall on the windshield of the vehicle when rainfall occurs. The higher the rainfall, the lower the sensor signal is. Using these characteristics of the sensor signal generated by the rain sensor, we developed a relational expression. In order to generate specific rainfall, an artificial rainfall generator was constructed and the change of the sensor signal according to the variation of the rainfall amount in the artificial rainfall generator was analyzed. Among them, the optimal sensor channel which reflects various rainfall amounts through the sensitivity analysis was selected. The sensor signal was generated in 5 minutes using the selected channel and the representative values of the generated 5 - minute sensor signals were set as the average, 25th, 50th, and 75th quartiles. The calculated rainfall values were applied to the actual rainfall data using the constructed relational equation and the calculated rainfall amount was compared with the rainfall values observed at the rainfall station. Although the reliability of the relational expression was somewhat lower than that of the data of the verification result data, it was judged that the experimental data of the residual range was insufficient. The rainfall value was calculated by applying the developed relation to the actual rainfall, and compared with the rainfall value generated by the ground rainfall observation instrument observed at the same time to verify the reliability. As a result, the rain sensor showed a fine rainfall of less than 0.5 mm And the average observation error was 0.36mm.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.65-70
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• 2013

The integrated sensor module of vehicle combines the functions of rain sensor, auto defog sensor, and sun angle sensor into a single module. These functions originally were applied to work separatively. This integrated sensor module should meet the each performance which appears from the individual modules up to the same level or higher. Therefore, it is important to verify the stability and the accuracy considering the characteristics of the integrated sensor module according to various situations. For the verification, we need to use the actual data of integrated sensor module measured but, a lot of time and money is needed to collect data measured under various circumstances when operating. Thus, through the development of this simulator for the control of the integrated sensor module, we can use it effectively for the initial verification of integrated sensor module by implementing the various situations. In this paper, the simulator for controlling the integrated sensor module which combines vision-based rain sensor, auto defog sensor, auto light sensor, and sun angle sensor has been developed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1727-1730
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• 2003

A windshield wiper system plays a key part in assurance of driver's safety at rainfall. However, because quantity of rain and snow vary irregularly according to time and velocity of automotive, a driver changes speed and operation period of a wiper from time to time in order to secure enough visual field in the traditional windshield wiper system. Because a manual operation of windshield wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming direct cause of traffic accident. Therefore, this paper presents the basic architecture of vision-based smart windshield wiper system and the rain sensing algorithm that regulate speed and operation period of windshield wiper automatically according to quantity of rain or snow. Also, this paper introduces the fuzzy wiper control algorithm based on human's expertise, and evaluates performance of suggested algorithm in simulator model. In especial, the vision sensor can measure wide area relatively than the optical rain sensor. hence, this grasp rainfall state more exactly in case disturbance occurs.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.7
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• pp.649-657
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• 2004

A windshield wiper system plays a key part in assurance of driver's safety at rainfall. However, because quantity of rain and snow vary irregularly according to time and velocity of automotive, a driver changes speed and operation period of a wiper from time to time in order to secure enough visual field in the traditional windshield wiper system. Because a manual operation of wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming direct cause of traffic accident. Therefore, this paper presents the basic architecture of vision-based smart wiper system and the rain sensing algorithm that regulate speed and interval of wiper automatically according to quantity of rain or snow. Also, this paper introduces the fuzzy wiper control algorithm based on human's expertise, and evaluates performance of suggested algorithm in the simulator model. Especially the vision sensor can measure wider area relatively than the optical rain sensor, hence, this grasps rainfall state more exactly in case disturbance occurs.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1694-1699
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• 2003

A windshield wiper system plays a key part in assuring the driver's safety during the rainfall. However, because the quantity of rain and snow vary irregularly according to time and the velocity of the automobile, a driver changes wiper speed and interval from time to time to secure enough visual field in the traditional windshield wiper system. Because a manual operation of windshield wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming a direct cause of traffic accidents. Therefore, this paper presents the basic architecture of a vision-based smart windshield wiper system and a rain sensing algorithm that regulates speed and interval of the windshield wiper automatically according to the quantity of rain or snow. This paper also introduces a fuzzy wiper control algorithm based on human's expertise, and evaluates the performance of the suggested algorithm in an experimental simulator.

• Journal of IKEEE
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• v.24 no.1
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• pp.232-237
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• 2020

In this paper, we propose an efficient sensor fusion method for autonomous vehicle recognition and distance measurement. Typical sensors used in autonomous vehicles are radar, lidar and camera. Among these, the lidar sensor is used to create a map around the vehicle. This has the disadvantage, however, of poor performance in weather conditions and the high cost of the sensor. In this paper, to compensate for these shortcomings, the distance is measured with a radar sensor that is relatively inexpensive and free of snow, rain and fog. The camera sensor with excellent object recognition rate is fused to measure object distance. The converged video is transmitted to a smartphone in real time through an IP server and can be used for an autonomous driving assistance system that determines the current vehicle situation from inside and outside.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.

• Journal of Mechanical Science and Technology
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• v.20 no.9
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• pp.1418-1427
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• 2006

Windshield wipers play a key role in assuring the driver's safety during precipitation. The traditional wiper systems, however, requires driver's constant attention in adjusting the wiper speed and the intermittent wiper interval because the amount of precipitation on the windshield constantly varies according to time and vehicle's speed. Because the manual adjustment of the wiper distracts driver's attention, which may be a direct cause of traffic accidents, many companies have developed automatic wiper systems using some optical sensors with various levels of success. This paper presents the development of vision-based smart windshield wiper system that can automatically adjust its speed and intermittent interval according to the amount of water drops on the windshield. The system employs various image processing algorithms to detect water drops and fuzzy logic to determine the speed and the interval of the wiper.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.783-791
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• 2018

The biased estimation of low density rainfall network and radar rainfall has limited application to extreme rainfall in a small area. To improve this, more rainfall information needs to be produced. In this study, we analyzed the applicability of the vehicle rainfall sensor developed and used recently. The developed rainfall sensor was attached to the vehicle to observe the rainfall according to the movement of the vehicle. The analytical method used time series and average rainfall values for observations of rainfall sensors and nearby rainfall stations. The results show that the trend of observed values according to rainfall events shows a certain pattern. It is analyzed that it is caused by various causes such as the difference between the observation position of the rainfall sensor and the nearby rainfall station, the moving speed of the vehicle, and the rainfall observation method. This result shows the possibility of rainfall observation using a rainfall sensor for a vehicle, and it is possible to observe rainfall more precisely through experiments and improvement of rainfall sensors in various conditions in the future.