Interactive Vehicle Automation Lab
FOR Intelligent Vehicles & Dynamical Systems
Research Overview
We connect research in mechanical engineering, electrical engineering, computer science, psychology and mathematics to tackle a wide range of problems across the field of intelligent vehicles and dynamical systems. Our group aims to develop innovative dynamic models and control algorithms to characterise and improve the behaviour of intelligent vehicles and mechanical systems in relation to safety, comfort, acceptance, naturalness and trust, provide fundamental insights into human-centric intelligent systems, and build next-generation of intelligent vehicles as well as robots to address challenges in human-robot interaction, decision making and control, human factors and transportation.
Decision-making of Intelligent Vehicles
Within the complex and interactive environment, automated vehicles (AVs) not only need to avoid the dynamic and static obstacles, but also need to coorperate or negotiate with other road users, One critical challenge is that the AVs cannot socially behave like rational human drivers when interacting with other road users, especially in interactive urban environments engaged with heterogenous road users. Our study is to develop human-centric decision making and control algorithms for AVs in relation to trust, acceptance and naturalness.
Human-Robot Interaction
Although automated vehicle studies are moving forward with a fast pace, the This study is to investigate how the humans interact with robots and automated vehicles. The future connected and autoamted vehicles as well as robots will co-exist with humans. There should be many challenges arising due to the uncertainty of humans behaviour and the limited understanding between humans and robots or intelligent vehicles. Our research in this area focuses on investigating human factors, predicting human behaviour, and developing human-centric autonomous systems that can co-exist and coorperatve with humans.
Dynamics and control
Our research in dynamics is to develop dynamic models to characterise the dynamics behaviour of mechanical systems, particularly nonlinear systems. Through exploring the nonlinear properties of these mechanical system, we can optimise designs of the sytems, and improve the accuracy of mathematical modelling. WIth the developed dynamic systems, we also develop controllers to improve their performance in relation to comfortability, stability, safety and energy economy.
