Driving behavior modeling and characteristic learning for human-like decision-making in highway
C Xu, W Zhao, C Wang, T Cui… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
To make autonomous vehicles consider driver's personalized characteristics, this paper
proposes an integrated model and learning combined (IMLC) algorithm to realize human …
proposes an integrated model and learning combined (IMLC) algorithm to realize human …
An integrated decision-making framework for highway autonomous driving using combined learning and rule-based algorithm
C Xu, W Zhao, J Liu, C Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In order to solve the manual labelling, long-tail effect and driving conservatism of the existing
decision-making algorithm. This paper proposed an integrated decision-making framework …
decision-making algorithm. This paper proposed an integrated decision-making framework …
Brain-Inspired Modeling and Decision-Making for Human-Like Autonomous Driving in Mixed Traffic Environment
In this paper, a human-like driving system is designed for autonomous vehicles (AVs), which
aims to make AVs better integrate into the human transportation systems and mitigate …
aims to make AVs better integrate into the human transportation systems and mitigate …
Human-like decision making of artificial drivers in intelligent transportation systems: An end-to-end driving behavior prediction approach
Drivers can be either human beings or artificial drivers in future intelligent transportation
systems (ITSs). It is important to learn how people drive so that artificial drivers can be …
systems (ITSs). It is important to learn how people drive so that artificial drivers can be …
Driver lane-changing intention recognition based on stacking ensemble learning in the connected environment: A driving simulator study
H Zhang, S Gao, Y Guo - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
The connected environment provides information on surrounding traffic and areas beyond
the visual range traffic to improve driving behavior and avoid dangerous incidents. However …
the visual range traffic to improve driving behavior and avoid dangerous incidents. However …
Automated vehicle's behavior decision making using deep reinforcement learning and high-fidelity simulation environment
Automated vehicles (AVs) are deemed to be the key element for the intelligent transportation
system in the future. Many studies have been made to improve AVs' ability of environment …
system in the future. Many studies have been made to improve AVs' ability of environment …
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 …
Combined hierarchical learning framework for personalized automatic lane-changing
B Zhu, J Han, J Zhao, H Wang - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
There have been explosive developments in automatic driving in recent years. Several kinds
of self-driving vehicles have been introduced, but drivers are generally required to stay alert …
of self-driving vehicles have been introduced, but drivers are generally required to stay alert …
A learning-based autonomous driver: emulate human driver's intelligence in low-speed car following
In this paper, an offline learning mechanism based on the genetic algorithm is proposed for
autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is …
autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is …
Humanlike behavior generation in urban environment based on learning-based potentials with a low-cost lane graph
It is crucial to understand the surrounding cars with respect to the road context and interact
with them harmoniously for the success of autonomous cars used in the mixed urban traffic …
with them harmoniously for the success of autonomous cars used in the mixed urban traffic …