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Found 7 papers, 0 papers with code
Speeding Up Path Planning via Reinforcement Learning in MCTS for Automated Parking
In this paper, we address a method that integrates reinforcement learning into the Monte Carlo tree search to boost online path planning under fully observable environments for automated parking tasks.
Integrating Higher-Order Dynamics and Roadway-Compliance into Constrained ILQR-based Trajectory Planning for Autonomous Vehicles
This paper addresses the advancements in on-road trajectory planning for Autonomous Passenger Vehicles (APV).
Learning from Naturalistic Driving Data for Human-like Autonomous Highway Driving
In this study, a method of learning cost parameters of a motion planner from naturalistic driving data is proposed.
Driver Identification through Stochastic Multi-State Car-Following Modeling
In this study, a joint model of the two types of heterogeneity in car-following behavior is proposed as an approach of driver profiling and identification.
Cross Scene Prediction via Modeling Dynamic Correlation using Latent Space Shared Auto-Encoders
A method is proposed to solve the problem via modeling dynamic correlation using latent space shared auto-encoders.
Off-road Autonomous Vehicles Traversability Analysis and Trajectory Planning Based on Deep Inverse Reinforcement Learning
Different cost functions of traversability analysis are learned and tested at various scenes of capability in guiding the trajectory planning of different behaviors.
Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-supervised Learning
This work studies the semantic segmentation of 3D LiDAR data in dynamic scenes for autonomous driving applications.
Robotics
