Autonomous Vehicle Lab
At Khalifa University's Autonomous Vehicle Lab, our research focuses on advancing autonomous vehicle technology, prioritizing safety, seamless integration into smart urban environments, and ensuring AI systems are aligned with passenger needs.
Our key research areas include:
- Developing strategies to enhance the safety of key components in AV decision-making.
- Enabling multi-agent vehicles to safely and efficiently share perception and decision-making data, including epistemic and aleatoric uncertainties, through V2X industry standards.
- Designing decision-making frameworks that deliver strong safety assurances, grounded in rigorous theoretical validation.
News
- Join the Third ROAD++ Challenge at ECCV 2024!
- New Publication: TerrainSense: Vision-Driven Mapless Navigation for Unstructured Off-Road Environments. ICRA 2024
- 3 papers accepted at IEEE ICAR 2023
- AV Lab wins a $100,000 prize at the RTA self-driving transport challenge 2023
- New Publication: A Fully Polynomial Time Approximation Scheme for Constrained MDPs under Local Transitions. IEEE CDC 2023
- New Publication: Approximability and Efficient Algorithms for Constrained Fixed-Horizon POMDPs with Durative Actions. AIJ
- New Publication: DClEVerNet: Deep Combinatorial Learning for Efficient EV Charging Scheduling in Large-scale Networked Facilities. ACM E-Energy 2023
- New Publication: DFR-FastMOT: Detection Failure Resistant Tracker for Fast Multi-Object Tracking Based on Sensor Fusion. ICRA 2023
- New Publication: A Unified Framework for POMDPs with Constraints and Durative Actions, AAAI 2023
- New Publication: Approximations for Generalized Unsplittable Flow on Paths with Application to Power Systems Optimization
- Open Desert Trail Detection (O2DTD) Dataset Released!
- We are hiring!
- New Publication: Autonomous Recharging and Flight Mission Planning for Battery-Operated Autonomous Drones
- Autonomous Vehicle Lab Launch
- AV Lab wins 1st spot at the RTA self-driving transport challenge
subscribe via RSS