Driving Safety in Smart Cabin: From Driver Behavior Regulation to Driver Monitoring System

Abstract

With the development of driving automation technology and in-vehicle infotainment systems, vehicles are becoming increasingly intelligent. The new capabilities in smart cabins present both opportunities and challenges for the advancement of intelligent transportation systems. Serving as the interface between the vehicle's various systems and the occupants within the cockpit (including both drivers and passengers), the intelligent cabin conveys key information related to driving safety to the driver. Considering how the behavior of drivers within the cabin changes under the impact of new technologies is vital for the efficient and safe transmission of information, which is essential for ensuring driving safety. At the same time, in the foreseeable future, vehicles controlled by autonomous driving systems and human road users will inevitably need to share public roads, creating a mixed traffic flow where autonomous vehicles and human road users coexist. Therefore, the safety and operational efficiency of autonomous/assisted driving are not only closely related to control technologies but are also intimately connected to the interaction behaviors between humans and autonomous/assisted driving vehicles, traffic regulations, and legal frameworks. To address these issues, it is necessary to model changes in driver behavior within mixed traffic flows and evaluate driving safety, with the aim of optimizing autonomous driving control systems. This seminar will introduce some of the work conducted in the fields of intelligent driving, intelligent cabin, and mixed traffic.

Speaker

Prof. Dengbo He is an Assistant Professor at the Thrust of Intelligent Transportation and Thrust of Robotics and Autonomous Systems, the Hong Kong University of Science and Technology (Guangzhou) (HKUST-GZ). Before joining HKUST-GZ in 2021, he worked as a Postdoctoral Fellow at the University of Toronto from 2020 to 2021. He received an MS degree from Shanghai Jiao Tong University in 2016 and a PhD degree from the University of Toronto in 2020. With over 80 journal and conference papers published, along with 6 book chapters and 1 edited book, he has made significant contributions to his field. In recognition of his work, he received the Human Factors and Ergonomics Society’s 2023 Jerome H. Ely Human Factors Article Award. Additionally, over the past 3 years, he has secured more than 3 million in research grants.