By 2050, over two thirds of the global population will live in cities, where an increase in transport volume with higher demand of goods and deliveries is expected. The urban transport system must decouple negative externalities, such as empty trips, low vehicle fill-rate, congestion and emissions from transport-related activities to improve the overall effectiveness and sustainability. The mobility sector is currently undergoing a transformation driven by technological trends, such as automation, electrification, and digitalisation. New vehicle and transport solutions are emerging as a response to these trends and challenges. Driverless multipurpose vehicles (DMVs) are an emerging road vehicle concept for heavy-duty transport in cities. DMVs can change their transport application during transport missions, flexibly changing between passenger and cargo transport, or being used for other transport tasks. Furthermore, they are autonomous and built on an electric system architecture with extensive modularity. Taking these factors into account, DMVs may develop into effective, silent, zero-emission vehicles that support the circular economy in urban settings, leading to a growing decoupling of resource consumption and emissions from the urban transport system. However, there is a lack of understanding of how emerging vehicle concepts, such as DMVs influence efficiency and sustainability in the urban transport system. The purpose of the research project is to study the effect of driverless multipurpose vehicles on system efficiency and sustainability in city transport. The methodology used to answer the research questions are based on solving complex and large-scale mixed-integer linear programming programs that model transport system networks and simultaneously contain low-level vehicle information. This is a development project.