3 accepted papers
Designing effective car-following (CF) models is essential for the development of safe and efficient autonomous driving systems, enabling ego vehicles to adjust their speed based on leading traffic. However, current data-driven CF models, particularly those based on reinforcement learning (RL), ofte
The inherent stochasticity of the agents' behavior presents a challenge to trajectory prediction models, which are required to generate multiple plausible future trajectories. Recently, diffusion models have been applied to implement multimodal trajectory prediction. Existing approaches typically em
Multi-agent trajectory prediction plays a pivotal role for intelligent transportation and autonomous driving. Modeling the social interaction among agents and revealing the inherent relationship between interaction and future trajectory are crucial for accurate trajectory prediction. To address thes