Bike Network Design: An approach based on micro-mobility geo-referenced data

Cycling and micro-mobility, in general, have been long promoted as sustainable and suitable modes of transport due to emission mitigation, congestion reduction and improvements to users' health and lifestyle. However, as most cities in the world have followed a car-centric development, their bicycle network is often highly fragmented, constituting the biggest barrier for attracting new users. This paper introduces a data-driven procedure based on micro-mobility geo-referenced data collected in the city of Rome (Italy). The aim is to identify corridors of high-density micro-mobility demand through an iterative clustering procedure and to evaluate potential growth scenarios of the bicycle network by locating the strategic missing links in the existing infrastructure to achieve a fully connected bicycle network that maximizes the overall usage of deployed bike lanes. The procedure has been applied to the city of Rome (Italy) adopting point data of the e-scooter sharing operator Dott.