Recent advances in motion and behavior planning techniques for software architecture of autonomous vehicles: A state-of-the-art survey
Autonomous vehicles (AVs) have now drawn significant attentions in academic and
industrial research because of various advantages such as safety improvement, lower …
industrial research because of various advantages such as safety improvement, lower …
Scenario understanding and motion prediction for autonomous vehicles—review and comparison
Scenario understanding and motion prediction are essential components for completely
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …
Interaction dataset: An international, adversarial and cooperative motion dataset in interactive driving scenarios with semantic maps
Behavior-related research areas such as motion prediction/planning, representation/
imitation learning, behavior modeling/generation, and algorithm testing, require support from …
imitation learning, behavior modeling/generation, and algorithm testing, require support from …
A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
Decentralized structural-rnn for robot crowd navigation with deep reinforcement learning
Safe and efficient navigation through human crowds is an essential capability for mobile
robots. Previous work on robot crowd navigation assumes that the dynamics of all agents …
robots. Previous work on robot crowd navigation assumes that the dynamics of all agents …
Robotic vision for human-robot interaction and collaboration: A survey and systematic review
Robotic vision, otherwise known as computer vision for robots, is a critical process for robots
to collect and interpret detailed information related to human actions, goals, and …
to collect and interpret detailed information related to human actions, goals, and …
Surround vehicle motion prediction using LSTM-RNN for motion planning of autonomous vehicles at multi-lane turn intersections
Y Jeong, S Kim, K Yi - IEEE Open Journal of Intelligent …, 2020 - ieeexplore.ieee.org
This paper presents a surround vehicle motion prediction algorithm for multi-lane turn
intersections using a Long Short-Term Memory (LSTM)-based Recurrent Neural Network …
intersections using a Long Short-Term Memory (LSTM)-based Recurrent Neural Network …
Driving style: How should an automated vehicle behave?
L Oliveira, K Proctor, CG Burns, S Birrell - Information, 2019 - mdpi.com
This article reports on a study to investigate how the driving behaviour of autonomous
vehicles influences trust and acceptance. Two different designs were presented to two …
vehicles influences trust and acceptance. Two different designs were presented to two …
Research on quantum cognition in autonomous driving
Q Song, W Wang, W Fu, Y Sun, D Wang, Z Gao - Scientific reports, 2022 - nature.com
Autonomous vehicles for the intention of human behavior of the estimated traffic participants
and their interaction is the main problem in automatic driving system. Classical cognitive …
and their interaction is the main problem in automatic driving system. Classical cognitive …
Learning from naturalistic driving data for human-like autonomous highway driving
Driving in a human-like manner is important for an autonomous vehicle to be a smart and
predictable traffic participant. To achieve this goal, parameters of the motion planning …
predictable traffic participant. To achieve this goal, parameters of the motion planning …