Predicting vehicle behaviors over an extended horizon using behavior interaction network

W Ding, J Chen, S Shen - 2019 international conference on …, 2019 - ieeexplore.ieee.org
Anticipating possible behaviors of traffic participants is an essential capability of
autonomous vehicles. Many behavior detection and maneuver recognition methods only …

Interaction-based trajectory prediction over a hybrid traffic graph

S Kumar, Y Gu, J Hoang, GC Haynes… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
Behavior prediction of traffic actors is an essential component of any real-world self-driving
system. Actors' long-term behaviors tend to be governed by their interactions with other …

Learning interaction-aware probabilistic driver behavior models from urban scenarios

J Schulz, C Hubmann, N Morin… - 2019 IEEE intelligent …, 2019 - ieeexplore.ieee.org
Human drivers have complex and individual behavior characteristics which describe how
they act in a specific situation. Accurate behavior models are essential for many applications …

Exploring dynamic context for multi-path trajectory prediction

H Cheng, W Liao, X Tang, MY Yang… - … on Robotics and …, 2021 - ieeexplore.ieee.org
To accurately predict future positions of different agents in traffic scenarios is crucial for
safely deploying intelligent autonomous systems in the real-world environment. However, it …

BARK: Open behavior benchmarking in multi-agent environments

J Bernhard, K Esterle, P Hart… - 2020 IEEE/RSJ …, 2020 - ieeexplore.ieee.org
Predicting and planning interactive behaviors in complex traffic situations presents a
challenging task. Especially in scenarios involving multiple traffic participants that interact …

Deep predictive autonomous driving using multi-agent joint trajectory prediction and traffic rules

K Cho, T Ha, G Lee, S Oh - 2019 IEEE/RSJ International …, 2019 - ieeexplore.ieee.org
Autonomous driving is a challenging problem because the autonomous vehicle must
understand complex and dynamic environment. This understanding consists of predicting …

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 …

Deep learning-based vehicle behavior prediction for autonomous driving applications: A review

S Mozaffari, OY Al-Jarrah, M Dianati… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Behaviour prediction function of an autonomous vehicle predicts the future states of the
nearby vehicles based on the current and past observations of the surrounding environment …

Multi-agent driving behavior prediction across different scenarios with self-supervised domain knowledge

H Ma, Y Sun, J Li, M Tomizuka - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
How to make precise multi-agent trajectory prediction is a crucial problem in the context of
autonomous driving. It is significant to have the ability to predict surrounding road …

Multi-modal probabilistic prediction of interactive behavior via an interpretable model

Y Hu, W Zhan, L Sun… - 2019 IEEE Intelligent …, 2019 - ieeexplore.ieee.org
For autonomous agents to successfully operate in real world, the ability to anticipate future
motions of surrounding entities in the scene can greatly enhance their safety levels since …