To effectively design adaptive traffic signal control for congested traffic networks, it is essential to account for three fundamental characteristics of traffic flow: (i) its dynamic nature, (ii) spatial patterns, and (iii) stochastic behaviour. In this presentation, we will discuss how these three key attributes are captured and embedded within a rigorous analytical framework, which is then transformed into an intelligent traffic control system through AI-based computational techniques. This system, known as Dynamic Intersection Signal Control Optimization (DISCO), is validated using VISSIM simulations and tested in real-world environments. The applications span diverse scenarios—including roundabouts and adaptive area-wide control—demonstrating DISCO’s versatility and effectiveness in practice.
Professor Lo’s expertise includes dynamic traffic management, network analysis, smart city, and sustainability. He is Founding Editor-in-Chief of Transportmetrica B: Transport Dynamics and Managing Editor of the Journal of Intelligent Transportation Systems. Professor Lo was awarded the prestigious triennial World Conference on Transportation Research (WCTR) Prize, HKUST School of Engineering Research Excellence Award, etc. He is a Justice of the Peace (JP), Fellow of Hong Kong Academy of Engineering, Fellow of Hong Kong Institution of Engineers (HKIE), Fellow of Chartered Institute of Logistics and Transport (CILT), Fellow of Hong Kong Institute of Highway and Transportation (IHT), and Fellow of Hong Kong Society for Transportation Studies.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
