• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.3B
• /
• pp.485-492
• /
• 2010

Intelligent Transport System(ITS) has been studied in various systems, such as road environment information offering, vehicle short-range wireless/wire communication, vehicle collision preventing and pedestrian safety offering systems. Related to this, the USN technology based on the sensing accuracy for motorists and pedestrians safety, the information reliability, the maintenance and convenience for Sensor Network is highlighted. This study uses various sensors to construct USN to the road, and connect it to the developed RSU so it collects the real-time road environment information and offers it to OBU and Traffic Control Surveillance Center with Road Weather Information System. RSU collects roadside information for driver's safety and analyzes it to offer IP and beacon service according to the service priority to OBU & upper layer terminal. In the upper layer terminal it is developed the IP based Settop Box application program to offer the urban traffic information & road environment, and environment sensor error, etc. Finally, RWIS develops the real-time collection of roadside information to complement the driver's safety to the intelligent traffic system, and presents various service modes with technology convergence.

• Atmosphere
• /
• v.24 no.4
• /
• pp.471-479
• /
• 2014

A road surface temperature prediction model (UM-Road) using input data of the Unified Model (UM) output and road physical properties is developed and verified with the use of the observed data at road weather information system. The UM outputs of air temperature, relative humidity, wind speed, downward shortwave radiation, net longwave radiation, precipitation and the road properties such as slope angles, albedo, thermal conductivity, heat capacity at maximum 7 depth are used. The net radiation is computed by a surface radiation energy balance, the ground heat flux at surface is estimated by a surface energy balance based on the Monin-Obukhov similarity, the ground heat transfer process is applied to predict the road surface temperature. If the observed road surface temperature exists, the simulated road surface temperature is corrected by mean bias during the last 24 hours. The developed UM-Road is verified using the observed data at road side for the period from 21 to 31 March 2013. It is found that the UM-Road simulates the diurnal trend and peak values of road surface temperature very well and the 50% (90%) of temperature difference lies within ${\pm}1.5^{\circ}C$ (${\pm}2.5^{\circ}C$) except for precipitation case.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.9 no.5
• /
• pp.38-48
• /
• 2010

Adverse weather (e.g. strong winds, snow and ice) will probably appear as a more serious and frequent threat to road traffic than in clear climate. Another consequence of climate change with a natural disastrous on road traffic is respond to traffic accident more the large and high-rise bridge zone, tunnel zone, inclined plane zone and de-icing zone than any other zone, which in turn calls for continuous adaption of monitoring procedures. Accident mitigating measures against this accident category may consist of intense winter maintenance, the use of road weather information systems for data collection and early warnings, road surveillance and traffic control. While hazard from reduced road friction due to snow and ice may be eliminated by snow removal and de-icing measures, the effect of strong winds on road traffic are not easily avoided. The purpose of the study described here, was to design of amber information the relationship between traffic safety, weather, user information on road weather and driving conditions in local-scale Geographic. The most applications are the optimization of the amber information definition, improvements to road surveillance, road weather monitoring and improved accuracy of user information delivery. Also, statistics on wind gust, surface condition, vehicle category and other relevant parameters for wind induced accidents provide basis for traffic control, early warning policies and driver education for improved road safety at bad weather-exposed locations.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.58 no.1
• /
• pp.48-55
• /
• 2009

In order to keep safe driving conditions under road networks, there are several formations such as road structure, road surface condition, traffic occupancy and supplement of an accurate information of traffic status ahead To support safe-driving on each road formation, each formation is supplied with various information to help the driver. However, in some cases like rapid status change at local-scale geography, traffic information systems often displays insufficient information because of the lack of information correlation. In order to accurately aware the driver, all road formation must be in sync. It is important to supply accurate information to the driver because this information directly impacts the drivers on the road. This paper discusses the amber information to keep the least safety driving over road formations including tunnels and bridges. This paper also will propose the informations for safe-driving conditions, information linkage on the road and rule-base safety information, as ITS technology, being displayed for all drivers under the worst weather conditions.

• International Journal of Highway Engineering
• /
• v.20 no.2
• /
• pp.127-135
• /
• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.1076-1079
• /
• 2000

In this paper, a simplified visualization method is proposed for an urban space in consideration of weather and sun moving. In the proposed method, buildings and roads with shadows are visualized by the ray tracing algorithm. Also sky, snow, and rain are visualized by textures. Some textures such as snow and rain are generated in advance by the ray casting algorithm. Then we can obtain images with weather condition and shadows of sunlight by buildings along the road in relatively low computational cost

• International Journal of Highway Engineering
• /
• v.19 no.6
• /
• pp.147-153
• /
• 2017

PURPOSES : This research aims to estimate the occurrence of hydroplaning on roads based on the road alignment types and rainfall intensity in Seoul. METHODS : Three types of data were used for estimation of hydroplaning in this study. The Inner Circulation Road (12.5 km) to the Bukbu Expressway (7.4 km) in Seoul was selected as the test road and data was collected for road information using a probe-vehicle. Precipitation was observed from Automatic Weather System in Seoul. These data were interpolated by applying Inverse Distance Weighted Methodology for hydroplaning estimation. Finally, the water depth information of the roads was observed using an RCM411 device. RESULTS : This study demonstrated that the cross slope with small-angle-tilt or vertical section with large-angle-tilt are the primary factors causing hydroplaning on the roads. The flow velocity on steep slope is high; however, large drainage lengths result in hydroplaning on the roads. CONCLUSIONS : This result can contribute towards the reduction of car accidents on rainy days. Furthermore, information regarding hydroplaning can be delivered to drivers more rapidly and precisely in the future.

• The KIPS Transactions:PartB
• /
• v.14B no.6
• /
• pp.445-452
• /
• 2007

We proposed a detection scheme of weather information in CCTV video images in this paper. The scheme obtains the RGB distribution of shiny day and divide a target image into cloud, rain, snow and for RGB distributions. shiny day RGB distribution. Our scheme designed systematically to detection and separation special characteristics of images from complex weather information. Our algorithm has less overhead than the previous methods to use weather database DB at the view of time and space. And our algorithm can be use in real world system with low cost of implementation. Also, our algorithm use informations of temperature, humidity, date, and time to detect the information of weather with high quality.

• International Journal of Highway Engineering
• /
• v.15 no.5
• /
• pp.177-185
• /
• 2013

PURPOSES : This study attempts to design and establish the road surface condition detection system by using the image processing that is expected to help implement the low-cost and high-efficiency road information detection system by examining technology trends in the field of road surface condition information detection and related case studies. METHODS : Adapted visual information collecting method(setting a stereo camera outside of the vehicle) and visual information algorithm(transform a Wavelet Transform, using the K-means clustering) Experiments and Analysis on Real-road, just as four states(Dry, Wet, Snow, Ice). RESULTS : Test results showed that detection rate of 95% or more was found under the wet road surface, and the detection rate of 85% or more in snowy road surface. However, the low detection rate of 30% was found under the icy road surface. CONCLUSIONS : As a method to improve the detection rate of the mobile road surface condition information detection system developed in this study, more accurate phase analysis in the image processing process was needed. If periodic synchronization through automatic settings of the camera according to weather or ambient light was not made at the time of image acquisition, a significant change in the values of polarization coefficients occurs.

• International journal of advanced smart convergence
• /
• v.12 no.4
• /
• pp.190-201
• /
• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.