The driving safety field based on driver–vehicle–road interactions
Vehicle driving safety is influenced by many factors, including drivers, vehicles, and road
environments. The interactions among them are quite complex. Consequently, existing …
environments. The interactions among them are quite complex. Consequently, existing …
Driving safety field theory modeling and its application in pre-collision warning system
The concept and contents of driving safety field theory were presented in our previous study.
On this basis, this study focus on driving safety field theory modeling and application. First, a …
On this basis, this study focus on driving safety field theory modeling and application. First, a …
A physics-informed road user safety field theory for traffic safety assessments applying artificial intelligence-based video analytics
The rapid technological advancements in video analytics and the availability of big data
have made traffic conflict techniques a viable tool for road safety assessments. They can …
have made traffic conflict techniques a viable tool for road safety assessments. They can …
Task-Driven Controllable Scenario Generation Framework Based on AOG
Sampling, generation, and evaluation of scenarios are essential steps for intelligent testing
of autonomous vehicles. Since uncertainty in driving behavior always leads to different …
of autonomous vehicles. Since uncertainty in driving behavior always leads to different …
How do drivers respond to driving risk during car-following? Risk-response driver model and its application in human-like longitudinal control
X Zhao, R He, J Wang - Accident Analysis & Prevention, 2020 - Elsevier
The blooming of intelligent connected vehicle (ICV) has been continuously shaping a hybrid
traffic environment in which the road is shared among ICVs and vehicles driven by human …
traffic environment in which the road is shared among ICVs and vehicles driven by human …
A flexible and explainable vehicle motion prediction and inference framework combining semi-supervised AOG and ST-LSTM
Accurate trajectory prediction of surrounding vehicles is important for automated vehicles. To
solve several existing problems of maneuver-based trajectory prediction, we propose four …
solve several existing problems of maneuver-based trajectory prediction, we propose four …
Research on the quantitative evaluation of the traffic environment complexity for unmanned vehicles in urban roads
S Yang, L Gao, Y Zhao, X Li - IEEE Access, 2021 - ieeexplore.ieee.org
The primary goal of the paper is to explore the human-vehicle-road interaction mechanism
in the traffic environment and evaluate the traffic environment complexity for unmanned …
in the traffic environment and evaluate the traffic environment complexity for unmanned …
Quantifying the Individual Differences of Drivers' Risk Perception via Potential Damage Risk Model
There will be a time when automated vehicles coexist with human-driven ones.
Understanding how drivers assess driving risks and modeling their differences is crucial for …
Understanding how drivers assess driving risks and modeling their differences is crucial for …
A general autonomous driving planner adaptive to scenario characteristics
Autonomous vehicle requires a general planner for all possible scenarios. Existing
researches design such a planner by a unified scenario description. However, it may …
researches design such a planner by a unified scenario description. However, it may …
Path planning using a multiclass support vector machine
In this paper, a new path planning algorithm for unstructured environments based on a
Multiclass Support Vector Machine (MSVM) is presented. Our method uses as its input an …
Multiclass Support Vector Machine (MSVM) is presented. Our method uses as its input an …