1 citations · 1 across the 4 of their papers we have counts for
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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…
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…
A Framework for Human-Reason-Aligned Trajectory Evaluation in Automated Vehicles
Lucas Elbert Suryana, Saeed Rahmani, Simeon Craig Calvert +2
One major challenge for the adoption and acceptance of automated vehicles (AVs) is ensuring that they can make sound decisions in everyday situations that involve ethical tension.…