
This study proposes an innovative trajectory prediction model that integrates cognitive insights on perceived safety and dynamic decision-making to enhance the performance of autonomous driving systems in mixed autonomy environments.


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cognitive-driven-trajectory-prediction-model-for-autonomous-driving-in-mixed-autonomy-environments


Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environments


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A novel generative model that integrates characterized diffusion and spatial-temporal interaction networks to accurately predict trajectories of vehicles in complex and dynamic traffic scenarios.


characterized-diffusion-and-spatial-temporal-interaction-network-for-accurate-trajectory-prediction-in-autonomous-driving


Characterized Diffusion and Spatial-Temporal Interaction Network for Accurate Trajectory Prediction in Autonomous Driving



A novel method for generating optimal trajectories by combining predictions from an ensemble of heterogeneous trajectory prediction models, outperforming existing sampling techniques.


optimal-trajectory-sampling-from-heterogeneous-ensemble-of-motion-forecasting-models


Optimal Trajectory Sampling from Heterogeneous Ensemble of Motion Forecasting Models
