Infrastructure usability becomes limited during a heavy snowfall event. In order to prevent such limitations, damage calculations and a decision-making process are needed. Snow-removal routing is a type of relevant disaster-prevention service. While three-dimensional (3D) models support these measures, they contain complex information regarding compatibility. This study generates a city-level semantic information model for roads using CityGML, an open standard data schema, and calculates the optimal snow removal route using this model. To this end, constraint conditions are analyzed from the viewpoint of a snow-removal vehicle, and a road network for an optimal route is applied to a 3D road information model. Furthermore, this study proposes a new algorithm that reduces the number of nodes used in the optimal route calculation, and a genetic algorithm is used to find the solution of the formulated objective function. This new algorithm reduces the number of nodes to less than two-thirds that of the original numbers when determining the optimal travel route for snow-removal vehicles in the target area.
|Journal||ISPRS International Journal of Geo-Information|
|Publication status||Published - 2019 Dec 17|
Bibliographical noteFunding Information:
Funding: This research was supported by the Energy Cloud R&D Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (2019M3F2A1073164). This work was also supported by the Gachon University research fund of 2019 (GCU-2019-0360).
© 2019 by the authors
All Science Journal Classification (ASJC) codes
- Geography, Planning and Development
- Computers in Earth Sciences
- Earth and Planetary Sciences (miscellaneous)