9 papers
DiscoGen: Procedural Generation of Algorithm Discovery Tasks in Machine Learning
Alexander D. Goldie, Zilin Wang, Adrian Hayler +17
Automating the development of machine learning algorithms has the potential to unlock new breakthroughs. However, our ability to improve and evaluate algorithm discovery systems ha…
Edge Case Detection in Automated Driving: Methods, Challenges, and Future Directions
Saeed Rahmani, Sabine Rieder, Erwin de Gelder +6
Automated vehicles (AVs) promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains challenging, particularly due…
Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning
Saeed Rahmani, Gözde Körpe, Zhenlin +4
Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency. Model Predictive Control (MP…
Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic
Saeed Rahmani, Shiva Rasouli, Daphne Cornelisse +3
Autonomous vehicles (AVs) are now operating on public roads, which makes their testing and validation more critical than ever. Simulation offers a safe and controlled environment f…
Learning to Drive in New Cities Without Human Demonstrations
Zilin Wang, Saeed Rahmani, Daphne Cornelisse +4
While autonomous vehicles have achieved reliable performance within specific operating regions, their deployment to new cities remains costly and slow. A key bottleneck is the need…
Automated Vehicles at Unsignalized Intersections: Safety and Efficiency Implications of Mixed Human and Automated Traffic
Saeed Rahmani, Zhenlin Xu, Simeon C. Calvert +1
The integration of automated vehicles (AVs) into transportation systems presents an unprecedented opportunity to enhance road safety and efficiency. However, understanding the inte…