학술논문

Cut-Out Scenario Generation With Reasonability Foreseeable Parameter Range From Real Highway Dataset for Autonomous Vehicle Assessment
Document Type
Periodical
Source
IEEE Access Access, IEEE. 11:45349-45363 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Autonomous vehicles
Vehicle safety
Behavioral sciences
Correlation
Automobiles
Connected vehicles
Connected and automated vehicles
car-following
lane change
logical scenarios
safety-test assessment
scenario-based approach
Language
ISSN
2169-3536
Abstract
This study aims to generate test cases for scenario-based assessment of automated driving systems (ADS) when encounter a cut-out maneuver where the lead vehicle having changed lanes, revealing a new lead vehicle that, in some cases, is slower than the original lead (the cutting-out) vehicle. We extracted the cut-out scenarios from an established real-world traffic dataset recorded by instrumented vehicles on Japanese highways and then defined them using vehicle kinematic parameters (velocities and distances). The extracted scenarios were analyzed based on the direct correlation between every two consecutive vehicles: a rear part that describes the correlation between the following vehicle and the cutting-out vehicle; and a frontal part that describes the correlation between the cutting-out vehicle and the preceding vehicle. Parameter ranges were quantified with a regression model and determined based on the risk acceptance threshold applied in the field of Japanese high-speed trains and annual exposure by professional highway drivers to produce a scenario space with a reasonably foreseeable range in which ADS may not produce crashes lest it performs worse than human drivers. A multi-dimensional distribution analytical approach was used to derive a correlation between the following and preceding vehicles considering the initial longitudinal velocities. Results suggest that when the time headway between the following vehicle and the cutting-out vehicle is equal to or more than 2 s, there should not have collision risks between the following vehicle and the preceding vehicle. These findings can help to understand normative driver behavior during cut-out scenarios and to generate accident-free scenario space for which ADS must perform flawlessly.