Enhance autonomous vehicle safety through object behavior classification using MATLAB's Deep Learning Toolbox. This project implements CNN-LSTM hybrid networks to predict pedestrian and vehicle trajectories from camera/LiDAR data. The tutorial covers anomaly detection in traffic patterns, risk assessment modeling, and real-time decision systems. Learn to process urban scene datasets, handle occlusions, and generate safety interventions. Includes benchmark comparisons showing 40% improvement in prediction accuracy over traditional methods.