[HTML][HTML] Trajectory data-based traffic flow studies: A revisit
In this paper, we review trajectory data-based traffic flow studies that have been conducted
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …
over the last 15 years. Our purpose is to provide a roadmap for readers who have an interest …
[HTML][HTML] About calibration of car-following dynamics of automated and human-driven vehicles: Methodology, guidelines and codes
A comprehensive literature review reveals that there exist lots of ambiguities, confusion and
even contradictions in setting a car-following calibration problem. In particular, confusion …
even contradictions in setting a car-following calibration problem. In particular, confusion …
Synthetic data in machine learning for medicine and healthcare
Synthetic data in machine learning for medicine and healthcare | Nature Biomedical Engineering
Skip to main content Thank you for visiting nature.com. You are using a browser version with …
Skip to main content Thank you for visiting nature.com. You are using a browser version with …
Design and experimental validation of deep reinforcement learning-based fast trajectory planning and control for mobile robot in unknown environment
This article is concerned with the problem of planning optimal maneuver trajectories and
guiding the mobile robot toward target positions in uncertain environments for exploration …
guiding the mobile robot toward target positions in uncertain environments for exploration …
A flow feedback traffic prediction based on visual quantified features
J Chen, M Xu, W Xu, D Li, W Peng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Traffic flow prediction methods commonly rely on historical traffic data, such as traffic volume
and speed, but may not be suitable for high-capacity expressways or during peak traffic …
and speed, but may not be suitable for high-capacity expressways or during peak traffic …
Deep learning-based trajectory planning and control for autonomous ground vehicle parking maneuver
In this paper, a novel integrated real-time trajectory planning and tracking control framework
capable of dealing with autonomous ground vehicle (AGV) parking maneuver problems is …
capable of dealing with autonomous ground vehicle (AGV) parking maneuver problems is …
[HTML][HTML] Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives
Automated vehicles (AVs) are widely considered to play a crucial role in future transportation
systems because of their speculated capabilities in improving road safety, saving energy …
systems because of their speculated capabilities in improving road safety, saving energy …
Human-like autonomous car-following model with deep reinforcement learning
This study proposes a framework for human-like autonomous car-following planning based
on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation …
on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation …
Vehicle trajectory prediction using LSTMs with spatial–temporal attention mechanisms
Accurate vehicle trajectory prediction can benefit a variety of intelligent transportation system
applications ranging from traffic simulations to driver assistance. The need for this ability is …
applications ranging from traffic simulations to driver assistance. The need for this ability is …
Driver activity recognition for intelligent vehicles: A deep learning approach
Driver decisions and behaviors are essential factors that can affect the driving safety. To
understand the driver behaviors, a driver activities recognition system is designed based on …
understand the driver behaviors, a driver activities recognition system is designed based on …