UFN: User Friendly Navigation Framework Based on Systematic Utilization of User Friendliness Features from Historical Traffic Data

Due to the ever-increasing number of traffic vehicles, navigation services play an important role in daily life. Current studies typically plan the fastest route by two steps: traffic forecasting and route planning. The planned routes may not be safe or comfortable for drivers. Even if some studies consider the user friendliness factors and extract the safety and comfort information from historical traffic (HT) data, they simply combine it with driving time in the beginning of traffic forecasting. It would be more accurate to keep and use all the information until the planned route is obtained. To address this challenge, we propose a user friendly navigation framework called UFN. UFN extracts user friendliness features from HT data and systematically predicts all the features without combining them beforehand. Based on the prediction results, UFN plans the most user friendly route by simplifying and solving a multiple-objective optimization problem. Experimental results demonstrate UFN is accurate, and the more accurate the predicted user friendliness features, the more user friendly the planned route.