collaborators

6 papers

cs.LG2026

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…

cs.HC2026

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…

cs.SE2026

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…

cs.RO2025

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.…

cs.RO2025

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…

cs.RO2025

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…