This paper presents a novel SLAM system, Semantic Point and Line Features SLAM (DPL-SLAM). By using dection algorithm and LK flow constrains, our proposed SLAM framework can handle dynamic environments and can be used for real-time operation. 
we present SLAM^2, a novel semantic RGB-D SLAM system that can obtain accurate estimation of the camera pose and the 6DOF pose of other objects, resulting in complete and clean static 3D model mapping in dynamic environments. 
This paper introduces a two-stage trajectory planning framework that considers safety, efficiency, and ride comfort simultaneously in dynamic environments. 
The proposed algorithm employs a deep Q-learning network to effectively learn safe and efficient driving strategies in complex multi-vehicle roundabouts. 
This paper presents a contingency-aware spatiotemporal optimization framework that integrates dynamic risk assessment and trajectory optimization to ensure the autonomous host vehicle (HV) achieve safer, more efficient lane changes. 
This paper proposes a scalable multi-vehicle decision-making framework that integrates Level-k recursive reasoning with Monte Carlo Tree Search for efficient coordination at unsignalized intersections. 