Explainable multimodal trajectory prediction using attention models
K Zhang, L Li - Transportation Research Part C: Emerging …, 2022 - Elsevier
Automated vehicles are expected to navigate complex urban environments safely along with
several non-cooperating agents. Therefore, accurate trajectory prediction is crucial for safe …
several non-cooperating agents. Therefore, accurate trajectory prediction is crucial for safe …
Artificial intelligence for vehicle behavior anticipation: Hybrid approach based on maneuver classification and trajectory prediction
Innovative technologies and naturalistic driving data sources provide a great potential to
develop reliable autonomous driving systems. Understanding the behaviors of surrounding …
develop reliable autonomous driving systems. Understanding the behaviors of surrounding …
Predicting vehicles trajectories in urban scenarios with transformer networks and augmented information
A Quintanar, D Fernández-Llorca… - 2021 IEEE Intelligent …, 2021 - ieeexplore.ieee.org
Understanding the behavior of road users is of vital importance for the development of
trajectory prediction systems. In this context, the latest advances have focused on recurrent …
trajectory prediction systems. In this context, the latest advances have focused on recurrent …
Amenet: Attentive maps encoder network for trajectory prediction
Trajectory prediction is critical for applications of planning safe future movements and
remains challenging even for the next few seconds in urban mixed traffic. How an agent …
remains challenging even for the next few seconds in urban mixed traffic. How an agent …
How would surround vehicles move? a unified framework for maneuver classification and motion prediction
Reliable prediction of surround vehicle motion is a critical requirement for path planning for
autonomous vehicles. In this paper, we propose a unified framework for surround vehicle …
autonomous vehicles. In this paper, we propose a unified framework for surround vehicle …
Wsip: Wave superposition inspired pooling for dynamic interactions-aware trajectory prediction
Predicting motions of surrounding vehicles is critically important to help autonomous driving
systems plan a safe path and avoid collisions. Although recent social pooling based LSTM …
systems plan a safe path and avoid collisions. Although recent social pooling based LSTM …
S2tnet: Spatio-temporal transformer networks for trajectory prediction in autonomous driving
W Chen, F Wang, H Sun - Asian conference on machine …, 2021 - proceedings.mlr.press
To safely and rationally participate in dense and heterogeneous traffic, autonomous vehicles
require to sufficiently analyze the motion patterns of surrounding traffic-agents and …
require to sufficiently analyze the motion patterns of surrounding traffic-agents and …
MPC-PF: socially and spatially aware object trajectory prediction for autonomous driving systems using potential fields
NP Bhatt, A Khajepour… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Predicting object motion behaviour is a challenging but crucial task for safe decision making
and path planning for autonomous vehicles. It is challenging in large part due to the …
and path planning for autonomous vehicles. It is challenging in large part due to the …
Multimodal motion prediction with stacked transformers
Predicting multiple plausible future trajectories of the nearby vehicles is crucial for the safety
of autonomous driving. Recent motion prediction approaches attempt to achieve such …
of autonomous driving. Recent motion prediction approaches attempt to achieve such …
Predicting motion of vulnerable road users using high-definition maps and efficient convnets
Following detection and tracking of traffic actors, prediction of their future motion is the next
critical component of a self-driving vehicle (SDV) technology, allowing the SDV to operate …
critical component of a self-driving vehicle (SDV) technology, allowing the SDV to operate …