Two-Stream Networks for Lane-Change Prediction of Surrounding Vehicles

Abstract-- In highway scenarios, an alert human driver will typically anticipate early cutin and cutout maneuvers of surrounding vehicles using only visual cues. Different sizes of the regions around the vehicles are analyzed, evaluating the importance of the interaction between vehicles and the context information in the performance. I. INTRODUCTION One of the closest and most plausible scenarios in the To deal with lane-change prediction of surrounding vehicles, adoption of the autonomous vehicles is autonomous navigation in this paper we pose the problem as an action at SAE L3 (chauffeur) or L4 (autopilot) on highways, recognition problem using visual information from cameras. The most advanced The idea behind our proposal is to use the same source of information automation systems to date are the Highway Chauffeur (visual cues) and the same type of approach (action (HC) and the Highway Autopilot (HA), which includes the recognition) that drivers use to anticipate these maneuvers. HC is mostly considered as L3 and HA as L4[1].