4 papers
A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios
Dong Bi, Yongqi Zhao, Paul Kovacevic +4
Personalized driving can improve the user acceptance of automated driving systems. However, existing methods still provide limited support for translating natural-language driving…
A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions
Ji Zhou, Yilin Ding, Yongqi Zhao +4
Reliable environmental perception remains one of the main obstacles for safe operation of automated vehicles. Safety of the Intended Functionality (SOTIF) concerns safety risks fro…
A Survey on the Applications of Generative Artificial Intelligence in Automated Driving Systems Test Scenario Generation Methods
Ji Zhou, Yongqi Zhao, Yixian Hu +4
Ensuring the safety and reliability of Automated Driving Systems (ADS) remains a critical challenge, as traditional verification methods such as large-scale on-road testing are pro…
A Survey on the Application of Large Language Models in Scenario-Based Testing of Automated Driving Systems
Yongqi Zhao, Ji Zhou, Dong Bi +3
The safety and reliability of Automated Driving Systems (ADSs) must be validated prior to large-scale deployment. Among existing validation approaches, scenario-based testing has b…