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cs.RO2025
A Physics-informed End-to-End Occupancy Framework for Motion Planning of Autonomous Vehicles
Shuqi Shen, Junjie Yang, Hongliang Lu +3
Accurate and interpretable motion planning is essential for autonomous vehicles (AVs) navigating complex and uncertain environments. While recent end-to-end occupancy prediction me…
cs.RO2025
Deployment-friendly Lane-changing Intention Prediction Powered by Brain-inspired Spiking Neural Networks
Shuqi Shen, Junjie Yang, Hui Zhong +3
Accurate and real-time prediction of surrounding vehicles' lane-changing intentions is a critical challenge in deploying safe and efficient autonomous driving systems in open-world…