This is high-precision data for routing and GIS analysis, with elevation information added to roads nationwide.
The system incorporates approximately 1.3 million kilometers of road network, reflecting topography including bridges, elevated roads, and tunnels, enabling various simulations such as estimating EV driving range, determining gradients, and detecting areas that are difficult to access during disasters.
Its key features include maintaining elevation values in 1cm increments and representing smooth trajectories that conform to road structures, making it easy to use in logistics operations, disaster prevention planning, and other applications.
In the logistics industry, it can be used for efficient route selection and reduction of fuel consumption.
Automakers can use this to estimate the driving range and evaluate the performance of EVs.
It can be used for simulations that take road gradients into account in urban planning and disaster prevention measures.
In analyzing evacuation routes during disasters, it is possible to design routes that avoid flood-prone areas and landslide-prone sections based on elevation differences.
This technology can be used in navigation systems for bicycles and motorcycles to provide route guidance that avoids hills and to offer gradient information.
It can be used to reproduce the elevation differences of roads along the terrain when building digital twins and 3D city models.
Elevation data is updated 12 times a year, and regularly every month to ensure consistency with road network data. Newly opened roads, changes in road structure, and elevation values requiring correction are quickly reflected, providing data that always reflects the latest terrain conditions.
For road structures such as tunnels and bridges, elevation values are assigned in a way that faithfully reflects the actual elevation differences of the road surface, utilizing actual measurements from survey vehicles and high-precision materials. Even structures that are difficult to represent with DEM (Digital Elevation Model) are given smooth elevation trajectories at the component point level, enabling analysis that closely matches actual driving conditions.
Since the power consumption of EVs is greatly affected by uphill and downhill slopes, considering the elevation difference and gradient of each road is essential for accurate range estimation.
By using this data, it becomes possible to perform energy consumption simulations that reflect the elevation differences of the entire route, thereby improving the accuracy of energy management in vehicle development and actual operation.
Yes, we assign it to all road links in the standard road network, including narrow local roads.
