Probabilistic prediction of vehicle semantic intention and motion
Accurately predicting the possible behaviors of traffic participants is an essential capability
for future autonomous vehicles. The majority of current researches fix the number of driving …
for future autonomous vehicles. The majority of current researches fix the number of driving …
Vehicle trajectory prediction using intention-based conditional variational autoencoder
Vehicle trajectory prediction has been an active research area in autonomous driving. In a
real traffic scene, autonomous vehicle needs to predict future motion of surrounding vehicles …
real traffic scene, autonomous vehicle needs to predict future motion of surrounding vehicles …
Attention based vehicle trajectory prediction
K Messaoud, I Yahiaoui… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Self-driving vehicles need to continuously analyse the driving scene, understand the
behavior of other road users and predict their future trajectories in order to plan a safe …
behavior of other road users and predict their future trajectories in order to plan a safe …
Multi-head attention based probabilistic vehicle trajectory prediction
This paper presents online-capable deep learning model for probabilistic vehicle trajectory
prediction. We propose a simple encoder-decoder architecture based on multihead …
prediction. We propose a simple encoder-decoder architecture based on multihead …
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 …
Multi-modal trajectory prediction of surrounding vehicles with maneuver based lstms
N Deo, MM Trivedi - 2018 IEEE intelligent vehicles symposium …, 2018 - ieeexplore.ieee.org
To safely and efficiently navigate through complex traffic scenarios, autonomous vehicles
need to have the ability to predict the future motion of surrounding vehicles. Multiple …
need to have the ability to predict the future motion of surrounding vehicles. Multiple …
End-to-end prediction of driver intention using 3d convolutional neural networks
P Gebert, A Roitberg, M Haurilet… - 2019 IEEE Intelligent …, 2019 - ieeexplore.ieee.org
Despite extraordinary progress of Advanced Driver Assistance Systems (ADAS), an
alarming number of over 1, 2 million people are still fatally injured in traffic accidents every …
alarming number of over 1, 2 million people are still fatally injured in traffic accidents every …
Intent prediction of vulnerable road users from motion trajectories using stacked LSTM network
Intent prediction of vulnerable road users (VRUs) has got some attention recently from the
research community, due to its critical role in the advancement of both advanced driving …
research community, due to its critical role in the advancement of both advanced driving …
Ltp: Lane-based trajectory prediction for autonomous driving
The reasonable trajectory prediction of surrounding traffic participants is crucial for
autonomous driving. Especially, how to predict multiple plausible trajectories is still a …
autonomous driving. Especially, how to predict multiple plausible trajectories is still a …
Vehicle motion prediction at intersections based on the turning intention and prior trajectories model
T Zhang, W Song, M Fu, Y Yang… - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
Intersections are quite important and complex traffic scenarios, where the future motion of
surrounding vehicles is an indispensable reference factor for the decision-making or path …
surrounding vehicles is an indispensable reference factor for the decision-making or path …