1 citations · 2 across the 6 of their papers we have counts for
6 papers
SDS++: Online Situation-Aware Drivable Space Estimation for Automated Driving
Manuel Muñoz Sánchez, Gijs Trots, Robin Smit +4
Autonomous Vehicles (AVs) need an accurate and up-to-date representation of the environment for safe navigation. Traditional methods, which often rely on detailed environmental rep…
Characterization and Mitigation of Insufficiencies in Automated Driving Systems
Yuting Fu, Jochen Seemann, Caspar Hanselaar +4
Automated Driving (AD) systems have the potential to increase safety, comfort and energy efficiency. Recently, major automotive companies have started testing and validating AD sys…
Prediction Horizon Requirements for Automated Driving: Optimizing Safety, Comfort, and Efficiency
Manuel Muñoz Sánchez, Chris van der Ploeg, Robin Smit +3
Predicting the movement of other road users is beneficial for improving automated vehicle (AV) performance. However, the relationship between the time horizon associated with these…
Overcoming the Fear of the Dark: Occlusion-Aware Model-Predictive Planning for Automated Vehicles Using Risk Fields
Chris van der Ploeg, Truls Nyberg, José Manuel Gaspar Sánchez +2
As vehicle automation advances, motion planning algorithms face escalating challenges in achieving safe and efficient navigation. Existing Advanced Driver Assistance Systems (ADAS)…
Robustness Benchmark of Road User Trajectory Prediction Models for Automated Driving
Manuel Muñoz Sánchez, Emilia Silvas, Jos Elfring +1
Accurate and robust trajectory predictions of road users are needed to enable safe automated driving. To do this, machine learning models are often used, which can show erratic beh…
Optimization-based Fault Mitigation for Safe Automated Driving
Niels Lodder, Chris van der Ploeg, Laura Ferranti +1
With increased developments and interest in cooperative driving and higher levels of automation (SAE level 3+), the need for safety systems that are capable to monitor system healt…