Analyzing driver behavior under naturalistic driving conditions: A review
H Singh, A Kathuria - Accident Analysis & Prevention, 2021 - Elsevier
For a decade, researchers working in the area of road safety have started exploring the use
of driving behavior data for a better understanding of the causes related to road accidents. A …
of driving behavior data for a better understanding of the causes related to road accidents. A …
[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 …
Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment
Driving intelligence tests are critical to the development and deployment of autonomous
vehicles. The prevailing approach tests autonomous vehicles in life-like simulations of the …
vehicles. The prevailing approach tests autonomous vehicles in life-like simulations of the …
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 …
Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment
This paper proposes a cooperative strategy of connected and automated vehicles (CAVs)
longitudinal control for a mixed connected and automated traffic environment based on deep …
longitudinal control for a mixed connected and automated traffic environment based on deep …
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 …
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 …
Operation analysis of freeway mixed traffic flow based on catch-up coordination platoon
X Yang, Y Zou, L Chen - Accident Analysis & Prevention, 2022 - Elsevier
As one of the innovative technologies of intelligent transportation systems (ITS), Connected
and Autonomous Vehicles (CAVs) have been deployed gradually. Given that there will be a …
and Autonomous Vehicles (CAVs) have been deployed gradually. Given that there will be a …
[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 …
Driver distraction detection based on vehicle dynamics using naturalistic driving data
Distracted driving such as phone use during driving is risky, as it increases the probability of
severe crashes. Detecting distraction using Naturalistic Driving Studies was attempted in …
severe crashes. Detecting distraction using Naturalistic Driving Studies was attempted in …