A survey on trajectory-prediction methods for autonomous driving
In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
Machine learning for autonomous vehicle's trajectory prediction: A comprehensive survey, challenges, and future research directions
V Bharilya, N Kumar - Vehicular Communications, 2024 - Elsevier
The significant contribution of human errors, accounting for approximately 94%(with a
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …
Crat-pred: Vehicle trajectory prediction with crystal graph convolutional neural networks and multi-head self-attention
J Schmidt, J Jordan, F Gritschneder… - … on Robotics and …, 2022 - ieeexplore.ieee.org
Predicting the motion of surrounding vehicles is essential for autonomous vehicles, as it
governs their own motion plan. Current state-of-the-art vehicle prediction models heavily rely …
governs their own motion plan. Current state-of-the-art vehicle prediction models heavily rely …
A review on intention-aware and interaction-aware trajectory prediction for autonomous vehicles
This paper presents a literature review on Intention-aware and Interaction-aware Trajectory
Prediction for Autonomous Vehicle, which covers primary studies since 2008. The research …
Prediction for Autonomous Vehicle, which covers primary studies since 2008. The research …
Handling occlusions in automated driving using a multiaccess edge computing server-based environment model from infrastructure sensors
M Buchholz, J Müller, M Herrmann… - IEEE Intelligent …, 2021 - ieeexplore.ieee.org
Sensors in an automated vehicle (AV) can encounter occlusions caused by other traffic,
buildings, and vegetation, especially in urban areas. Information from infrastructure sensors …
buildings, and vegetation, especially in urban areas. Information from infrastructure sensors …
Stopnet: Scalable trajectory and occupancy prediction for urban autonomous driving
We introduce a motion forecasting (behavior prediction) method that meets the latency
requirements for autonomous driving in dense urban environments without sacrificing …
requirements for autonomous driving in dense urban environments without sacrificing …
Effects of uncertain trajectory prediction visualization in highly automated vehicles on trust, situation awareness, and cognitive load
Automated vehicles are expected to improve safety, mobility, and inclusion. User
acceptance is required for the successful introduction of this technology. One essential …
acceptance is required for the successful introduction of this technology. One essential …
Motion planning for connected automated vehicles at occluded intersections with infrastructure sensors
Motion planning at urban intersections that accounts for the situation context, handles
occlusions, and deals with measurement and prediction uncertainty is a major challenge on …
occlusions, and deals with measurement and prediction uncertainty is a major challenge on …
[HTML][HTML] Risk-aware controller for autonomous vehicles using model-based collision prediction and reinforcement learning
Abstract Autonomous Vehicles (AVs) have the potential to save millions of lives and
increase the efficiency of transportation services. However, the successful deployment of …
increase the efficiency of transportation services. However, the successful deployment of …
Map-enhanced generative adversarial trajectory prediction method for automated vehicles
Trajectory prediction in dynamic and highly interactive scenarios is a critical method for
achieving advanced autonomous driving. Maximizing the guidance and constraints provided …
achieving advanced autonomous driving. Maximizing the guidance and constraints provided …