Optimising Urban Mobility and Safety with Micromobility Technologies

Abstract

This thesis aims to research how micromobility technologies and advanced data-driven systems can optimise urban mobility and enhance safety in urban environments. The study mainly focuses on technological advancements such as real-time vehicle monitoring, data analytics, geo-fencing and AI-powered solutions that enhance micromobility to seamlessly integrate into urban infrastructure. Key urban challenges include vehicle congestion, insufficient parking, pedestrian and user safety, as well as sidewalk riding, which are addressed to mitigate safety risks and prevent accidents. To gather data for this research a semi-structured qualitative approach, utilising an in-depth interview with the head of a leading micromobility company was chosen due to his years of experience in this leadership role, overseeing all operations, technological innovations, and strategic decision-making within the company. The research reveals that while technological and safety advancements such as AI-powered data gathering and real-time data analysis have significantly improved safety and urban design, the absence of consistent safety regulations across the market poses a significant challenge. The representative highlighted how unregulated markets limit the full implementation of advanced safety regulations as competitors can offer quicker, less regulated alternatives creating an operational imbalance. Despite the progress made in technology, further advancements in real-time safety monitoring, enforcement of parking and riding regulations, and data sharing between cities and operators are crucial in supporting the sustainable growth of the industry.