Ameliorating Accuracy of a Map Navigation When Dealing with Different Altitude Traffics that Share Exact Geolocation

Many users use a location-based application on a portable device to be a navigator when driving. However, there exists an incident that two roads are located on the same geolocation, i.e., same values of latitude and longitude but different altitude, for very long distance where one road is located on the ground level and another one is elevated. This incident mostly confuses a location-based application to precisely retrieve the actual road that a vehicle is currently on and, consequently, causes the application to either navigate incorrectly or suggest a route that is a detour. Calling an altitude from a GPS sensor might be a possible solution but it came with problems of accuracy, especially for mid-grade GPS sensors that equipped with most smartphone in today’s market. We proposed a concept of implementing a classification model that can classify whether a vehicle is on a ground road or an elevated road regardless of geolocation data. We trained and validated two models using a dataset that we had collected from actual driving on two roads in Thailand that fell under this condition. A data instance that we collected contained measurements related to driving or driving environment such as a real-time speed at any certain interval of time. We reported validation results of both models as well as other important statistics.