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08/30/2023
Explainable and Trustworthy Traffic Sign Detection for Safe Autonomous Driving: An Inductive Logic Programming Approach
Traffic sign detection is a critical task in the operation of Autonomous...
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07/03/2023
Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approach
The dynamic nature of driving environments and the presence of diverse r...
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05/26/2023
Adaptive PD Control using Deep Reinforcement Learning for Local-Remote Teleoperation with Stochastic Time Delays
Local-remote systems allow robots to execute complex tasks in hazardous ...
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03/29/2023
Decision Making for Autonomous Driving in Interactive Merge Scenarios via Learning-based Prediction
Autonomous agents that drive on roads shared with human drivers must rea...
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09/16/2022
Value Summation: A Novel Scoring Function for MPC-based Model-based Reinforcement Learning
This paper proposes a novel scoring function for the planning module of ...
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07/31/2022
Learning an Interpretable Model for Driver Behavior Prediction with Inductive Biases
To plan safe maneuvers and act with foresight, autonomous vehicles must ...
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09/22/2021
Early Lane Change Prediction for Automated Driving Systems Using Multi-Task Attention-based Convolutional Neural Networks
Lane change (LC) is one of the safety-critical manoeuvres in highway dri...
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07/09/2021
ARC: Adversarially Robust Control Policies for Autonomous Vehicles
Deep neural networks have demonstrated their capability to learn control...
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07/09/2021
Adversarial Mixture Density Networks: Learning to Drive Safely from Collision Data
Imitation learning has been widely used to learn control policies for au...
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03/27/2021
Self-adaptive Torque Vectoring Controller Using Reinforcement Learning
Continuous direct yaw moment control systems such as torque-vectoring co...
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03/17/2021
Weakly Supervised Reinforcement Learning for Autonomous Highway Driving via Virtual Safety Cages
The use of neural networks and reinforcement learning has become increas...
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07/28/2020
Lane-Change Initiation and Planning Approach for Highly Automated Driving on Freeways
Quantifying and encoding occupants' preferences as an objective function...
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02/27/2020
Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies
Deep learning has become an increasingly common technique for various co...
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12/23/2019