2022 Volume 3 Issue J2 Pages 755-763
Recently, countermeasures against traffic congestion and accidents have been promoted by utilizing probe data, which enables us to grasp the driving history and behavior of individual vehicles. Currently, the main application of probe data is to analyze traffic volume and travel speed per route, but we believe that more advanced road traffic analysis can be realized if probe data can be applied to micro traffic analysis at the driving lane level. Therefore, in this study, in order to estimate the driving lane using probe data, we analyzed the characteristics of the data and devised a method to estimate the driving lane and whether or not a lane change has occurred. As a result, we confirmed that lane change points can be estimated with high accuracy by applying a machine learning model that focuses on changes in acceleration. Furthermore, we found that combining the results of both driving lane and lane change estimation results provides more reliable estimation of the driving lane.
