Exploring Driving Behavior for Autonomous Vehicles Based on Gramian Angular Field Vision Transformer
Effective classification of autonomous vehicle (AV) driving behavior emerges as a critical area for diagnosing AV operation faults, enhancing autonomous driving algorithms, and reducing accident rates. This paper presents the Gramian Angular Field Vision Transformer (GAF-ViT) model, designed to analyze AV driving behavior. The proposed GAF-ViT model consists of three key components: GAF Transformer Module, Channel Attention Module, and Multi-Channel ViT Module. These modules collectively convert representative sequences of multivariate behavior into multi-channel images and employ image recognition techniques for behavior classification. A channel attention mechanism is applied to multi-channel images to discern the impact of various driving behavior features. Experimental evaluation on the Waymo Open Dataset of trajectories demonstrates that the proposed model achieves state-of-the-art performance. Furthermore, an ablation study effectively substantiates the efficacy of individual modules within the model.
Code (0)
등록된 구현이 없습니다.
Tasks
Autonomous DrivingAutonomous VehiclesMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Exploring the Influence of Driving Context on Lateral Driving Style Preferences: A Simulator-Based Study
Technological advancements focus on developing comfortable and acceptable driving characteristics in autonomous vehicles. Present driving functions predominantly possess predefined parameters, and there is no universally…
Autonomous VehiclesBeyond One Model Fits All: Ensemble Deep Learning for Autonomous Vehicles
Deep learning has revolutionized autonomous driving by enabling vehicles to perceive and interpret their surroundings with remarkable accuracy. This progress is attributed to various deep learning models, including Media…
AllAutonomous DrivingAutonomous VehiclesDeep LearningExiting the Simulation: The Road to Robust and Resilient Autonomous Vehicles at Scale
In the past two decades, autonomous driving has been catalyzed into reality by the growing capabilities of machine learning. This paradigm shift possesses significant potential to transform the future of mobility and res…
Autonomous DrivingAutonomous VehiclesSelf-Perception Versus Objective Driving Behavior: Subject Study of Lateral Vehicle Guidance
Advancements in technology are steering attention toward creating comfortable and acceptable driving characteristics in autonomous vehicles. Ensuring a safe and comfortable ride experience is vital for the widespread ado…
Autonomous VehiclesMachine Learning-Based Vehicle Intention Trajectory Recognition and Prediction for Autonomous Driving
In recent years, the expansion of internet technology and advancements in automation have brought significant attention to autonomous driving technology. Major automobile manufacturers, including Volvo, Mercedes-Benz, an…
Autonomous DrivingAutonomous Vehicles