Human motion trajectory prediction: A survey
With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …
of such systems to perceive, understand, and anticipate human behavior becomes …
A survey on motion prediction of pedestrians and vehicles for autonomous driving
Autonomous vehicle (AV) industry has evolved rapidly during the past decade. Research
and development in each sub-module (perception, state estimation, motion planning etc.) of …
and development in each sub-module (perception, state estimation, motion planning etc.) of …
Set-based prediction of traffic participants considering occlusions and traffic rules
M Koschi, M Althoff - IEEE Transactions on Intelligent Vehicles, 2020 - ieeexplore.ieee.org
Provably safe motion planning for automated road vehicles must ensure that planned
motions do not result in a collision with other traffic participants. This is a major challenge in …
motions do not result in a collision with other traffic participants. This is a major challenge in …
[HTML][HTML] Pedestrian intention prediction: A convolutional bottom-up multi-task approach
The ability to predict pedestrian behaviour is crucial for road safety, traffic management
systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous …
systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous …
Kinematics-aware multigraph attention network with residual learning for heterogeneous trajectory prediction
Trajectory prediction for heterogeneous traffic agents plays a crucial role in ensuring the
safety and efficiency of automated driving in highly interactive traffic environments …
safety and efficiency of automated driving in highly interactive traffic environments …
A robust scenario MPC approach for uncertain multi-modal obstacles
Motion planning and control algorithms for autonomous vehicles need to be safe, and
consider future movements of other road users to ensure collision-free trajectories. In this …
consider future movements of other road users to ensure collision-free trajectories. In this …
Real-time constrained trajectory planning and vehicle control for proactive autonomous driving with road users
I Batkovic, M Zanon, M Ali… - 2019 18th European …, 2019 - ieeexplore.ieee.org
For motion planning and control of autonomous vehicles to be proactive and safe,
pedestrians' and other road users' motions must be considered. In this paper, we present a …
pedestrians' and other road users' motions must be considered. In this paper, we present a …
Experimental validation of safe mpc for autonomous driving in uncertain environments
The full deployment of autonomous driving systems on a worldwide scale requires that the
self-driving vehicle can be operated in a provably safe manner, ie, the vehicle must be able …
self-driving vehicle can be operated in a provably safe manner, ie, the vehicle must be able …
Context-based cyclist path prediction using recurrent neural networks
This paper proposes a Recurrent Neural Network (RNN) for cyclist path prediction to learn
the effect of contextual cues on the behavior directly in an end-to-end approach, removing …
the effect of contextual cues on the behavior directly in an end-to-end approach, removing …
What truly matters in trajectory prediction for autonomous driving?
Trajectory prediction plays a vital role in the performance of autonomous driving systems,
and prediction accuracy, such as average displacement error (ADE) or final displacement …
and prediction accuracy, such as average displacement error (ADE) or final displacement …