A survey on motion prediction of pedestrians and vehicles for autonomous driving

M Gulzar, Y Muhammad, N Muhammad - IEEE Access, 2021 - ieeexplore.ieee.org
… Specifically, we identify and classify motion prediction literature for two road user classes ie
… and vehicle motion prediction literature and is built on three dimensions ie motion modelling …

What-if motion prediction for autonomous driving

S Khandelwal, W Qi, J Singh, A Hartnett… - arXiv preprint arXiv …, 2020 - arxiv.org
… Alternative directions for future research could explore applications of WIMP beyond
autonomous driving, perhaps for prediction of pedestrian trajectories or human actions; we will …

Motionnet: Joint perception and motion prediction for autonomous driving based on bird's eye view maps

P Wu, S Chen, DN Metaxas - Proceedings of the IEEE/CVF …, 2020 - openaccess.thecvf.com
… and motion information for motion planning. … motion prediction based on BEV maps. MotionNet
is bounding-box free and can provide complementary information for autonomous driving; …

Scenario understanding and motion prediction for autonomous vehicles—review and comparison

P Karle, M Geisslinger, J Betz… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
motion prediction are essential components for completely replacing human drivers and for
enabling highly and fully automated driving … scenarios, autonomous driving software must act …

Uncertainty-aware short-term motion prediction of traffic actors for autonomous driving

N Djuric, V Radosavljevic, H Cui… - Proceedings of the …, 2020 - openaccess.thecvf.com
… to predict future motion of traffic actors. Comprehensive overview of the topic can be found
in [30, 47]. Here, we review literature from the perspective of autonomous driving domain. We …

Interaction-aware motion prediction for autonomous driving: A multiple model kalman filtering scheme

V Lefkopoulos, M Menner, A Domahidi… - IEEE Robotics and …, 2020 - ieeexplore.ieee.org
… In this work, we propose a motion prediction scheme based … The proposed scheme is
capable of predicting collision-free, … behavior most drivers exhibit in typical driving scenarios, ie, …

Multi-modal motion prediction with transformer-based neural network for autonomous driving

Z Huang, X Mo, C Lv - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
prediction … of motion prediction, we propose a multimodal attention Transformer encoder,
which modifies the multihead attention mechanism to multi-modal attention, and each predicted

Differentiable integrated motion prediction and planning with learnable cost function for autonomous driving

Z Huang, H Liu, J Wu, C Lv - IEEE transactions on neural …, 2023 - ieeexplore.ieee.org
Predicting the future states of surrounding traffic participants and … for autonomous vehicles
(AVs). There are two major issues with the current autonomous driving system: the prediction

State estimation and motion prediction of vehicles and vulnerable road users for cooperative autonomous driving: A survey

P Ghorai, A Eskandarian, YK Kim… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
autonomous vehicles must react. This study focuses on a comprehensive survey of the literature
on motion prediction … planning and navigation functionalities of an autonomous vehicle. …

Motioncnn: A strong baseline for motion prediction in autonomous driving

S Konev, K Brodt, A Sanakoyeu - arXiv preprint arXiv:2206.02163, 2022 - arxiv.org
… In this paper, we tackle the motion prediction task. The most … We establish a simple and yet
efficient motion prediction … on the 2021 Waymo Open Dataset Motion Prediction Challenge [7] …