[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 …
Safe, efficient, and comfortable velocity control based on reinforcement learning for autonomous driving
A model used for velocity control during car following is proposed based on reinforcement
learning (RL). To optimize driving performance, a reward function is developed by …
learning (RL). To optimize driving performance, a reward function is developed by …
A physics-informed deep learning paradigm for car-following models
Car-following behavior has been extensively studied using physics-based models, such as
Intelligent Driving Model (IDM). These models successfully interpret traffic phenomena …
Intelligent Driving Model (IDM). These models successfully interpret traffic phenomena …
Data-driven Traffic Simulation: A Comprehensive Review
Autonomous vehicles (AVs) have the potential to significantly revolutionize society by
providing a secure and efficient mode of transportation. Recent years have witnessed …
providing a secure and efficient mode of transportation. Recent years have witnessed …
A sequence to sequence learning based car-following model for multi-step predictions considering reaction delay
L Ma, S Qu - Transportation research part C: emerging technologies, 2020 - Elsevier
Car-following behavior modeling is of great importance for traffic simulation and analysis.
Considering the multi-steps decision-making process in human driving, we propose a …
Considering the multi-steps decision-making process in human driving, we propose a …
A reinforcement learning-based vehicle platoon control strategy for reducing energy consumption in traffic oscillations
The vehicle platoon will be the most dominant driving mode on future roads. To the best of
our knowledge, few reinforcement learning (RL) algorithms have been applied in vehicle …
our knowledge, few reinforcement learning (RL) algorithms have been applied in vehicle …
Calibration and evaluation of the Responsibility-Sensitive Safety model of autonomous car-following maneuvers using naturalistic driving study data
X Xu, X Wang, X Wu, O Hassanin, C Chai - Transportation research part C …, 2021 - Elsevier
Safety guarantees are vital to the dependability of the automated vehicle (AV), so are of
primary concern to the AV industry and regulatory bodies. Responsibility-Sensitive Safety …
primary concern to the AV industry and regulatory bodies. Responsibility-Sensitive Safety …
Empirical study on the properties of adaptive cruise control systems and their impact on traffic flow and string stability
Adaptive cruise control (ACC) systems are standard equipment in many commercially
available vehicles. They are considered the first step of automation, and their market …
available vehicles. They are considered the first step of automation, and their market …
Extraction of descriptive driving patterns from driving data using unsupervised algorithms
Understanding drivers' behavioral characteristics is critical for the design of decision-making
modules in autonomous vehicles (AVs) and advanced driver assistance systems (ADASs) …
modules in autonomous vehicles (AVs) and advanced driver assistance systems (ADASs) …
A generative car-following model conditioned on driving styles
Abstract Car-following (CF) modeling, an essential component in simulating human CF
behaviors, has attracted increasing research interest in the past decades. This paper pushes …
behaviors, has attracted increasing research interest in the past decades. This paper pushes …