14 citations · 15 across the 7 of their papers we have counts for
7 papers
Multimodal Drivers' Emotion Recognition and Safety-Oriented Intervention for Intelligent Transportation Systems
Chang Liu, Dalai Mengke, Hanbo Zhou +3
Driver emotions can affect risk perception, decision-making, and vehicle control under complex road conditions. Existing studies mainly focus on driver emotion recognition, while l…
Lane Change Intention Prediction of two distinct Populations using a Transformer
Francesco De Cristofaro, Cornelia Lex, Jia Hu +1
In complex traffic scenarios, intention prediction of surrounding vehicles can improve the strategy of automated driving functions. Existing work on intention prediction is often t…
Toward a Full-Stack Co-Simulation Platform for Testing of Automated Driving Systems
Dong Bi, Yongqi Zhao, Zhengguo Gu +3
Virtual testing has emerged as an effective approach to accelerate the deployment of automated driving systems. Nevertheless, existing simulation toolchains encounter difficulties…
A Communication-Latency-Aware Co-Simulation Platform for Safety and Comfort Evaluation of Cloud-Controlled ICVs
Yongqi Zhao, Xinrui Zhang, Tomislav Mihalj +10
Testing cloud-controlled intelligent connected vehicles (ICVs) requires simulation environments that faithfully emulate both vehicle behavior and realistic communication latencies.…
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…
Human-Machine Shared Control Approach for the Takeover of CACC
Haoran Wang, Zhexi Lian, Zhenning Li +5
Cooperative Adaptive Cruise Control (CACC) often requires human takeover for tasks such as exiting a freeway. Direct human takeover can pose significant risks, especially given the…
Chat2Scenario: Scenario Extraction From Dataset Through Utilization of Large Language Model
Yongqi Zhao, Wenbo Xiao, Tomislav Mihalj +2
The advent of Large Language Models (LLM) provides new insights to validate Automated Driving Systems (ADS). In the herein-introduced work, a novel approach to extracting scenarios…