Connected and automated multimodal transport

We take advantage of advancements in traffic sensing, information and communication technologies, and big data to research and develop advanced techniques and efficient computational algorithms for modelling and simulation of multimodal and connected traffic networks, in different geographic scales (regional, city-wide, or corridor level) and at different resolutions levels (micro, meso and macro).

Further, we develop advanced mathematical methods to improve the accuracy of short-term predictions of the onset and severity of network congestion in real-time. We also develop optimisation platforms to help traffic control agents make best control decisions to prevent the onset of traffic congestion and gridlocks in real-time.