Automatic Detection Method of Lane-Changing Intentions Based on Relationship with Adjacent Vehicles Using Artificial Potential Fields

Abstract

This paper presents a new method to detect lane changes of other vehicles automatically. The main contribution of this work is to propose a new feature using a potential field that changes the distribution depending on the relative number of adjacent vehicles. Previous researches have considered only some of limited situations, for example, that the preceding vehicle is slower than the target vehicle. Therefore, degradation of the detection performance can occur under conditions that were not considered. On the other hand, the new feature we propose is able to describe general lane-changing situations by applying a dynamic potential model. We trained an estimation model and evaluated the performance using a traffic dataset with over 900 lane changes. It was confirmed that the proposed method outperforms previous methods in terms of both accuracy and early detection.