• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.04a
• /
• pp.1-4
• /
• 2008

Prediction models currently being used for road traffic noise in apartment are equation of NIER, HW-NOISE of Korea Expressway Corporation, FHWA of United States, CRTN of United Kingdom, NMPB of France, ASJ RTN-Model 2003 of Japan and ISO 9613-1, 2 as a international standard. ISO 9613 species an engineering method for calculating the attenuation of sound during propagation outdoors in order to predict the levels of environmental noise at a distance from a variety of sources. This study, prior to investigation of every prediction methods listed above, aims to examine the model internationally standardized and to establish a reference for the prediction of road traffic noise in apartment.

• Journal of Korean Society of Transportation
• /
• v.29 no.2
• /
• pp.123-131
• /
• 2011

This study proposes a model for road surface temperature prediction on basis of the heat-energy balance equation between atmosphere and road surface. The overall model is consisted of two types of modules: 1) Canopy 1 is used to describe heat transfer between soil surface and atmosphere; and 2) Canopy 2 can reflect the characteristics of pavement type. Input data used in the model run is obtained from the Korea Meteorological For model validation, the observed and predicted surface temperature data are compared using data collected on MoonEui Bridge along CheongWon-Sangju Expressway, and the comparison is made on winter and other seasons separately. Analysis results show that average difference between two temperatures lies within ${\pm}2^{\circ}C$ which is considered as appropriate from a micrometeorology point of view. The model proposed in this paper can be adopted as a useful tool in practical applications for winter maintenance. This study being a fundamental research is anticipated to be a starting point for further development of robust surface road temperature prediction algorithms.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.11 no.6
• /
• pp.131-142
• /
• 2007

The road user cost in indirect costs as well as direct costs such as the inspection/ diagnosis cost and the repair/reinforcement cost should be considered as one of the important items in the life-cycle cost-effective design and maintenance of the bridges. To estimate the road user cost, this paper formulates the road user cost as a sum of the user delay cost and the vehicle operating cost considering the detour effect. A numerical traffic simulation and a regression analysis are performed to develop a regression model due to a time delay. The proposed regression model is applied to the generation of the maintenance strategy based on the life-cycle cost and performance, and its effectiveness and applicability is investigated. The road user cost has a great influence on establishing the maintenance strategy, and the proposed regression model could be successfully utilized to estimate the road user cost of a bridge.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.6
• /
• pp.222-232
• /
• 2019

Mongolia is a developing country with a smaller population living across a large territory where infrastructure is underdeveloped. The country has been actively implementing road construction in recent years. The Mongolian government has increased investments in new road construction, but funding for major maintenance or reconstruction projects declined between 2012 and 2016. On the other hand, road network management has not been implemented owing to insufficient road maintenance and If the road network expands, there is a risk that the cost of overall maintenance will increase significantly in the future. Therefore, in order to cope with these problems, this study reviewed applying Korean road model to Mongolia for systematic management of road infrastructure.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.7
• /
• pp.3369-3385
• /
• 2019

There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.1
• /
• pp.85-96
• /
• 2023

The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.2
• /
• pp.30-38
• /
• 2015

In this study, to improve effectiveness of road management services and the safety of the road in winter, road surface temperature prediction model was developed. We have utilized the existing input data of meteorological data and additional traffic data. This Road surface temperature prediction model was utilizing a Heat-Balance Method additionally considering amount of traffic that produce heat radiation by vehicle-tire friction. This improved model was compared to the based model to check into influence of traffic affecting the road surface temperature. There were verified by comparing the real observed road surface temperature of the third Gyeong-In highway and road surface temperature from the two models. As a result, the error of real observed and the predicted value (RMSE) was found to average $1.97^{\circ}C$. Observed road surface temperature was dramatically affected by the sunlight from 6 a.m. to 2 p.m. and degree of influence decreases after that. The predictive value of the model is lower than the observed value in the afternoon, and higher at night. These results appear due to the shielding of solar radiation caused by the vehicle in the afternoon and at night, the vehicle appeared to cause thermal heat supply.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.4
• /
• pp.156-172
• /
• 2020

The purpose of this study was to predict road surface temperature using high-resolution solar radiation data. The road surface temperature prediction model (RSTPM) was applied to predict road surface temperature; this model was developed based on the heat-balance method. In addition, using SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry-model), the shadow patterns caused by the terrain effects were analyzed, and high-resolution solar radiation data with 10 m spatial resolution were calculated. To increase the accuracy of the shadow patterns and solar radiation, the day that was modeled had minimal effects from fog, clouds, and precipitation. As a result, shadow areas lasted for a long time at the entrance and exit of a tunnel, and in a high-altitude area. Furthermore, solar radiation clearly decreased in areas affected by shadows, which was reflected in the predicted road surface temperatures. It was confirmed that the road surface temperature should be high at topographically open points and relatively low at higher altitude points. The results of this study could be used to forecast the freezing of sections of road surfaces in winter, and to inform decision making by road managers and drivers.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.612-616
• /
• 2007

This paper describes a procedure to improve road noise using DPDS estimation. We can estimate a body local stiffness at chassis mounting point where the path of road input vibration by DPDS with experiment and FE simulation. DPDS result from FE model has a good correlation with experiment data. FE model DPDS shows weak points among chassis mounting points. Body panel thickness and shape were changed to meet DPDS target. Improved DPDS of critical points makes a road noise level lower.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.3
• /
• pp.1098-1104
• /
• 2011

This paper presents the development of the surface profile sensing system (SPSS) and its application to analysis of road surface. The SPSS which can robustly reconstruct the road input profiles from the intermixed data with the vehicle's dynamic motion, is implemented using the multi-sensor system with the optimally shaped transfer function. The performance of this system is evaluated by a series of experimental works in the devised simulator. And a real car test equipped with the proposed system is performed in the proving ground over both deterministic and random road surfaces. Finally, a feasibility of the system is investigated considering the road model.