Deep learning-based vehicle behavior prediction for autonomous driving applications: A review
Behaviour prediction function of an autonomous vehicle predicts the future states of the
nearby vehicles based on the current and past observations of the surrounding environment …
nearby vehicles based on the current and past observations of the surrounding environment …
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 …
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 …
AI-TP: Attention-based interaction-aware trajectory prediction for autonomous driving
K Zhang, L Zhao, C Dong, L Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Despite the advancements in the technologies of autonomous driving, it is still challenging to
study the safety of a self-driving vehicle. Trajectory prediction is one core function of an …
study the safety of a self-driving vehicle. Trajectory prediction is one core function of an …
Predictive trajectory planning for autonomous vehicles at intersections using reinforcement learning
In this work we put forward a predictive trajectory planning framework to help autonomous
vehicles plan future trajectories. We develop a partially observable Markov decision process …
vehicles plan future trajectories. We develop a partially observable Markov decision process …
Safe trajectory generation for complex urban environments using spatio-temporal semantic corridor
Planning safe trajectories for autonomous vehicles in complex urban environments is
challenging since there are numerous semantic elements (such as dynamic agents, traffic …
challenging since there are numerous semantic elements (such as dynamic agents, traffic …
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 …
Predicting vehicle behaviors over an extended horizon using behavior interaction network
Anticipating possible behaviors of traffic participants is an essential capability of
autonomous vehicles. Many behavior detection and maneuver recognition methods only …
autonomous vehicles. Many behavior detection and maneuver recognition methods only …
Surrounding vehicles' lane change maneuver prediction and detection for intelligent vehicles: A comprehensive review
R Song, B Li - IEEE Transactions on Intelligent Transportation …, 2021 - ieeexplore.ieee.org
Identifying and evaluating the potential risks in the surrounding environment is critical for
intelligent vehicles' safety and user experience. This paper provides a comprehensive …
intelligent vehicles' safety and user experience. This paper provides a comprehensive …
Vehicle trajectory prediction using generative adversarial network with temporal logic syntax tree features
In this work, we propose a novel approach for integrating rules into traffic agent trajectory
prediction. Consideration of rules is important for understanding how people behave-yet, it …
prediction. Consideration of rules is important for understanding how people behave-yet, it …