Research themes
We have structured our research within the Transport & Planning Department around four key themes. Three of these themes are directly connected to the primary societal challenges concerning transportation and mobility at present. The fourth theme addresses the methodological and technical challenges that arise within our field of work. Urbanisation and Smart Sustainable Transport To ensure effective access within urban regions, we need to create novel, sustainable, and intelligent transportation systems. That is what our theme Urbanization and Smart Sustainable Transport is about. It encompasses various topics including Mobility as a Service (MaaS), on-demand mobility, secure and eco-friendly active mode transportation, cities with reduced car dependence, electric and automated urban mobility, as well as coordinated and interconnected traffic management. Climate-friendly Transportation and Resilience To address climate change, it’s crucial to reduce the environmental impact of transportation. At the same time, we require transportation systems capable of handling climate change consequences such as heavy rainfall. This is why Climate-friendly Transportation and Resilience is one of our main themes. It explores and formulates potential solutions, including sustainable multi-modal traffic management, transport electrification, and strategies for enhancing resilience within traffic and transport systems. Well-being, Health, Equity, and Digitisation in Transport The theme Well-being, Health, Equity, and Digitisation in Transport centers around the development of transportation systems that prioritize the well-being and health of every individual. It also aims to enhance equity and accessibility while leveraging digitisation and automation to bolster the efficiency and efficacy of transportation services. The theme encompasses subjects like the interaction between land use and transport innovation, traffic and transportation safety, and equity and inclusiveness within transportation. Computational Modelling and Analysis for Transportation Engineering The theme Computational Modelling and Analysis for Transportation Engineering focuses on employing numerical modelling, simulation, artificial intelligence, and machine learning to solve transportation engineering problems and formulate effective systems. It also integrates the utilisation of sensing, monitoring, and data analysis techniques to enhance the accuracy of models and simulations. Additionally, this theme involves risk analyses and quantification of uncertainties to establish more resilient and reliable models.