A methodology for urban bike network design using floating car data: evidence from a medium-size city

Urban mobility plays a key-role in developing sustainable cities, prompting planners to promote alternatives to private cars. Among these, bikes offers significant potential. Therefore, this paper presents a methodology for designing bike networks using floating car data (FCD) and survey insights. FCD enables the estimation of origin-destination matrices, while surveys identify car trips that could shift to bikes. The approach is validated through a case study in Rovigo, a medium-size city in Northern Italy. Data from five working days, covering about 1,900 cars and 24,000 trips, allowed classification of travel patterns and demand analysis. Based on these findings, the proposed methodology achieved notable results, extending the existing bike network by approximately 28% in length. This study demonstrates the feasibility of leveraging FCD and behavioural data to support sustainable mobility planning and enhance cycling infrastructure.