Melbourne taps AI to ease traffic congestion

Australian's University of Melbourne has teamed up with a slew of public and private sector organisations to create an artificial intelligence (AI) application that can predict traffic congestion up to three hours ahead, as well as optimise traffic and improve road safety. The AI application, to be hosted on Amazon Web Services (AWS), can also optimise traffic signals for on-road vehicles, freight and public transport such as buses and trams. Majid Sarvi, a transport engineering expert and director at the university's Australian Integrated Multimodal EcoSystem, an initiative to test integrated transport technology on the streets of Melbourne, said the AI application observes the nature of traffic and figures out complex traffic patterns across the network through machine learning. "If we can upscale the application to provide more accurate prediction with machine learning and real-time data, it will soon be possible to substantially reduce delays in hotspots across Melbourne and many locations across the globe," he added. PeakHour Urban Technologies, a Melbourne-based AI specialist with a focus on transportation, developed the application's AI core engine which uses AWS to power its predictive capabilities.