Ensuring the safety of connected human-driven vehicles (CHDVs) during the transition period are still unclear. To address this, we develop a co-simulation platform integrating high-fidelity driving simulators with communication scenarios. Focusing on Cellular Vehicle-to-Everything (C-V2X) technology, we will examine safety risks from critical communication incidents such as cyber-attacks and signal loss. This research aims to establish a comprehensive framework for evaluating the dynamic safety impacts of connected vehicle (CV) technologies and their influence on driving safety and behavioral adaptation.

Ensuring driving safety in an aging society is a critical concern. Previous findings raise concerns because statistically, older drivers show negative effects on road safety. To address this, our study focuses on developing Large Language Model (LLM)-based driving assistance systems specifically designed for older drivers. By analyzing human behavior in interaction with these systems, we aim to evaluate their effectiveness and provide recommendations for designing human-machine interfaces and systems that enhance communication and interaction for this demographic.

Despite constituting a smaller proportion of vehicles, commercial vehicles account for a disproportionately high share of road crashes due to increased exposure and a higher prevalence of risky driving behaviors among their drivers. Our research specifically targets taxi and truck drivers, focusing on two main directions: (1) identifying critical driving behaviors such as distraction and fatigue to inform targeted safety management strategies; and (2) developing and evaluating the effectiveness of driver training intervention programs aimed at improving driving safety among truck drivers and fostering driving empathy toward disabled passengers among taxi drivers.

The rise of automated vehicles (AVs) in mixed traffic poses safety challenges for the safety of all road users. To address the challenges, we will develop a multi-user experimental platform combining driving simulators, e-scooters, bicycles, and pedestrian VR environments. This platform enables systematic study of interaction conflicts involving AVs and vulnerable road users (VRUs). We will assess safety outcomes and behavioral responses among various road users, and inform the design of resilient AV systems and urban infrastructure to promote the safe coexistence of all road users within future mobility ecosystems.