A reliable early warning framework for vessel-bridge collisions via spatiotemporal trajectory prediction and anomaly detection
An enhanced autoencoder network is designed that couples spatial encoding with dynamic behavior modeling to effectively extract latent trajectory features and offers a reliable and practical solution for intelligent vessel navigation and proactive risk warning in complex inland bridge environments.