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

Antonio Comi & Antonio Polimeni

Transportation Letters2026https://doi.org/10.1080/19427867.2025.2612627article
ABDC B
Weight
0.50

What the paper says

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.

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https://doi.org/https://doi.org/10.1080/19427867.2025.2612627

Or copy a formatted citation

@article{antonio2026,
  title        = {{A methodology for urban bike network design using floating car data: evidence from a medium-size city}},
  author       = {Antonio Comi & Antonio Polimeni},
  journal      = {Transportation Letters},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1080/19427867.2025.2612627},
}

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

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.