Uncertainty-aware driver trajectory prediction at urban intersections
Predicting the motion of a driver's vehicle is crucial for advanced driving systems, enabling
detection of potential risks towards shared control between the driver and automation …
detection of potential risks towards shared control between the driver and automation …
Multimodal trajectory predictions for autonomous driving using deep convolutional networks
Autonomous driving presents one of the largest problems that the robotics and artificial
intelligence communities are facing at the moment, both in terms of difficulty and potential …
intelligence communities are facing at the moment, both in terms of difficulty and potential …
Deep predictive autonomous driving using multi-agent joint trajectory prediction and traffic rules
Autonomous driving is a challenging problem because the autonomous vehicle must
understand complex and dynamic environment. This understanding consists of predicting …
understand complex and dynamic environment. This understanding consists of predicting …
Interaction-aware probabilistic behavior prediction in urban environments
Planning for autonomous driving in complex, urban scenarios requires accurate prediction
of the trajectories of surrounding traffic participants. Their future behavior depends on their …
of the trajectories of surrounding traffic participants. Their future behavior depends on their …
Maneuver-based trajectory prediction for self-driving cars using spatio-temporal convolutional networks
B Mersch, T Höllen, K Zhao… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
The ability to predict the future movements of other vehicles is a subconscious and effortless
skill for humans and key to safe autonomous driving. Therefore, trajectory prediction for …
skill for humans and key to safe autonomous driving. Therefore, trajectory prediction for …
SafeVRU: A research platform for the interaction of self-driving vehicles with vulnerable road users
This paper presents our research platform Safe VRU for the interaction of self-driving
vehicles with Vulnerable Road Users (VRUs, ie, pedestrians and cyclists). The paper details …
vehicles with Vulnerable Road Users (VRUs, ie, pedestrians and cyclists). The paper details …
[HTML][HTML] Injecting knowledge in data-driven vehicle trajectory predictors
Vehicle trajectory prediction tasks have been commonly tackled from two distinct
perspectives: either with knowledge-driven methods or more recently with data-driven ones …
perspectives: either with knowledge-driven methods or more recently with data-driven ones …
Uncertainty-aware short-term motion prediction of traffic actors for autonomous driving
We address one of the crucial aspects necessary for safe and efficient operations of
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
Joint multi-policy behavior estimation and receding-horizon trajectory planning for automated urban driving
B Zhou, W Schwarting, D Rus… - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
When driving in urban environments, an autonomous vehicle must account for the
interaction with other traffic participants. It must reason about their future behavior, how its …
interaction with other traffic participants. It must reason about their future behavior, how its …
Combining stochastic and scenario model predictive control to handle target vehicle uncertainty in an autonomous driving highway scenario
T Brüdigam, M Olbrich, M Leibold… - 2018 21st International …, 2018 - ieeexplore.ieee.org
Autonomous vehicles face the challenge of providing safe transportation while efficiently
maneuvering in an uncertain environment. Considering surrounding vehicles, two types of …
maneuvering in an uncertain environment. Considering surrounding vehicles, two types of …