# System Dynamics Modeling for Estimating the Locations of Road Icing Using GIS
###### Abstract
For further understanding of the modeling and simulation employed in this study, the following three items are summarized. * Factors  
Factors that affect road icing are mainly divided into spatial and meteorological data. Hillshade is the factor that represents spatial information and is calculated by DEM [10,11]. This factor accelerates road icing by preventing solar radiation from reaching the ground [12,13]. The main factor of meteorological data is precipitation. In particular, the freezing rain phenomenon instantaneously accelerates road icing and causes accidents [14]. * Methods  
System dynamics is a method of simulating a certain phenomenon by connecting block diagrams based on causality. In particular, it is strong in time-series expressions that are difficult to estimate for humans, while road icing is a phenomenon that continue to vary over time [15]. * Study Contributions  
The existing case studies are not complete. GIS simulation is particularly insufficient. This study addressed this insufficiency and is described later in detail. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Factor**} & \multirow{2}{*}{**Average**} & \multirow{2}{*}{**Unit**} & \multicolumn{2}{c}{**Implication**} \\ \cline{3-4}  & & & **Type of Analysis** & **Result** \\ \hline Minimum temperature & \(-\)2.0 & \({}^{\circ}\)C & Occurrence tendency & Occurs below 0 \({}^{\circ}\)C \\ Average cloud cover & 5.8 & - & Degree of occurrence & Five or more \\ Daily precipitation & 4.3 & mm/day & Occurrence/non-occurrence & Occurrence \\ Sunrise (time) & 07:28 & H:MM & Occurrence tendency & Faint sunlight \\ Accident (time) & 07:04 & H:MM & Occurrence tendency & Morning occurrence \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Road accidents occurred due to road icing in Korea. Prior to performing road icing modeling using spatial and meteorological data, previous studies in various cases were analyzed. In general, to estimate the occurrence of road icing, the warning system is remotely controlled by monitoring the sensor information on GIS [16]. There is also a method of providing road icing information on WebGIS [17]. This method enables efficient preparation by visualizing the occurrence of road icing on the map, but has limitations in preventing them because it cannot perform prior estimation prior to occurrence [18]. Without the use of GIS, the amount of road icing can be estimated according to the weather conditions by developing a numerical model and calculating the road surface condition values according to the parameters [19]. When a numerical model is designed and meteorological data are entered, various factors can be estimated. The contents and limitations of major cases are as follows. * [PERSON] et al. performed numerical modeling related to road icing in Jeju Island, Korea. They estimated the air temperature and wind speed through the WRF model, but estimation of the accurate amount and location of road icing is insufficient [19]. * [PERSON], [PERSON], and [PERSON] performed numerical modeling on factors related to road icing. They estimated the road surface condition and traffic condition by estimating road surface temperature, storage, and friction through the NWP model [20]. Estimation of the accurate amount and location of road icing is insufficient. * [PERSON], [PERSON], and [PERSON] performed numerical modeling to estimate the occurrence of road icing. They developed a block diagram model to estimate the Ice Index through the road surface temperature, air temperature, and humidity. They could simply estimate the occurrence of road icing, and estimation of the amount and location of road icing is insufficient [21]. * [PERSON], [PERSON], and [PERSON] estimated the road surface temperature through numerical modeling from parameters. They analyzed the relationships between the \"latitude, altitude, sky-view factor, screening, roughness length, road construction, traffic density, and topography\" with the road surface temperature.