# System Dynamics Modeling for Estimating the Locations of Road Icing Using GIS
###### Abstract
Estimation of the accurate amount and location of road icing is insufficient [22]. * [PERSON], [PERSON], and [PERSON] developed a model capable of estimating the road surface temperature by combining the Unified Model of the Korean Meteorological Administration (KMA) and the physical characteristics of the road surface. Although it is possible to estimate the road surface temperature with various factors, estimation of the amount and location of road icing is not sufficient [23]. * In other studies, road icing or related factors were also estimated mainly through simple numerical modeling. Road icing was estimated by analyzing heat conduction through the air temperature and humidity [24], measuring and analyzing road surface salinity and temperature [25], and developing short-term road icing estimation algorithms for sensors [26; 27]. As in the above cases, however, estimation of the amount and location of road icing is insufficient. These methods make it possible to systematically estimate factors related to the occurrence of road icing. Such occurrence, however, is estimated using only meteorological data, excluding spatial data, and there is no simulation stage for the occurrence location. In this study, previous insufficient cases were supplemented through system dynamics and GIS. The amount of road icing was modeled using the system dynamics theory. In addition, a section of the Honam Highway, which has a total length of 27 km, was divided into 18,583 points, and the amount and location of road icing were simulated for each point. Numerical modeling for estimating the occurrence of road icing will make it possible to prepare for wintertime traffic accidents more efficiently if the location estimation step based on the modeling results is added [28; 29]. There have been many studies on GIS simulation for disaster assessment [30]. They detect topographic hazards using GIS models [31] or analyze hazards on slopes in cold regions [32]. In addition, they evaluate and estimate the size of a hazard in high-risk areas, such as roads in hazardous ranges, using spatial data on GIS [33; 34]. This method was referred to and reflected in research for the simulation of the amount and location of road icing. After deriving implications by referring to previous studies, the amount of road icing over time was modeled by adding spatial data to meteorological data. Based on this, the amount of road icing by location was simulated using GIS. The results of estimating the amount and location of road icing through the simulation performed using appropriate scenarios can be used by government agencies (e.g., road traffic authority) as data to identify areas vulnerable to wintertime traffic accidents in advance and to prevent such traffic accidents [35]. This paper consists of five main sections. In Section 2, procedures and detailed research methods to model, simulate, and validate road icing are introduced. In addition, the study area, research data types, estimation methods, and theories are described in detail. In Section 3, the results for road surface temperature, road surface moisture, and the amount and location of road icing are presented. In Section 4, the simulation results and the actual accident points are compared and analyzed using a hypothesis testing technique. Finally, in Section 5, the results of this study are summarized and future plans to supplement shortcomings are described.