Hierarchical adaptable and transferable networks (hatn) for driving behavior prediction
When autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient transferable and …
driving, humans have long mastered the essence of driving with efficient transferable and …
Design and implementation of human driving data–based active lane change control for autonomous vehicles
This article describes the design, implementation, and evaluation of an active lane change
control algorithm for autonomous vehicles with human factor considerations. Lane changes …
control algorithm for autonomous vehicles with human factor considerations. Lane changes …
A hybrid rule-based and data-driven approach to driver modeling through particle filtering
Autonomous vehicles need to model the behavior of surrounding human driven vehicles to
be safe and efficient traffic participants. Existing approaches to modeling human driving …
be safe and efficient traffic participants. Existing approaches to modeling human driving …
Influencing leading and following in human–robot teams
Roles such as leading and following can emerge naturally in human groups. However, in
human–robot teams, such roles are often predefined due to the difficulty of scalably learning …
human–robot teams, such roles are often predefined due to the difficulty of scalably learning …
Driver intention prediction using model-added Bayesian network
R Song - Proceedings of the Institution of Mechanical …, 2021 - journals.sagepub.com
The autonomous driving technology requires reliable detection and prediction of the
surrounding environment. Predicting the lane change intention of the surrounding traffic is …
surrounding environment. Predicting the lane change intention of the surrounding traffic is …
Self-adaptive motion prediction-based proactive motion planning for autonomous driving in urban environments
Y Jeong - IEEE Access, 2021 - ieeexplore.ieee.org
This paper presents self-adaptive motion prediction-based proactive motion planning for
autonomous driving in urban environments. In order to achieve fully autonomous driving in …
autonomous driving in urban environments. In order to achieve fully autonomous driving in …
Driving maneuver classification using domain specific knowledge and transfer learning
With the increasing number of vehicles, the usage of technology has also been increased in
the transportation system. Although automobile companies are using advanced …
the transportation system. Although automobile companies are using advanced …
A modeled approach for online adversarial test of operational vehicle safety
The scenario-based testing of operational vehicle safety presents a set of principal other
vehicle (POV) trajectories that seek to force the subject vehicle (SV) into a certain safety …
vehicle (POV) trajectories that seek to force the subject vehicle (SV) into a certain safety …
[HTML][HTML] Analysis of effects of autonomous vehicle market share changes on expressway traffic flow using IDM
In this study, the impact of traffic flow on the market penetration rate of autonomous vehicles
(AV) was analyzed using the data for the year 2020 of the Yongin IC∼ Yangji IC section of …
(AV) was analyzed using the data for the year 2020 of the Yongin IC∼ Yangji IC section of …
A memory-attention hierarchical model for driving-behavior recognition and motion prediction
Proper understanding and prediction of driving behavior of surrounding vehicles are one of
the most significant requirements for automated driving especially when it comes to safety …
the most significant requirements for automated driving especially when it comes to safety …