Understanding the impact of city-wide cycling corridors on cycling mode share among different demographic clusters in Greater Melbourne, Australia

Understanding the impact of city-wide cycling corridors on cycling mode share among different demographic clusters in Greater Melbourne, Australia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding the impact of city-wide cycling corridors on cycling mode share among different demographic clusters in Greater Melbourne, Australia Afshin Jafari, Steve Pemberton, Dhirendra Singh, Tayebeh Saghapour, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4538181/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Apr, 2025 Read the published version in Transportation → Version 1 posted 9 You are reading this latest preprint version Abstract In car-dominated cities like Melbourne, Australia, limited data on cyclists' travel patterns and socio-demographic differences complicate understanding the effectiveness of infrastructure investment interventions aimed at promoting cycling. Recent advancements in city-scale transport modelling enable virtual testing of such interventions. However, the application of agent- and activity-based models for large-scale cycling simulations has been constrained by data and complexity. In this study, we developed a city-scale agent-based simulation model for Greater Melbourne to evaluate changes in travel mode share from cycling infrastructure modifications. We clustered bicycle riders into five demographic groups: Maverick Males, Motivated Adults, Conscientious Commuters, Young Sprinters, and Relaxed Cruisers, estimating mode choice parameters for each group. Using aggregated smartphone application data, we developed a cycling trip routing methodology to incorporate road infrastructure impacts. Results indicated that travel time significantly influences mode choice across all clusters. Cycling infrastructure was crucial for four clusters, and travel cost influenced four clusters. The calibrated model assessed the potential impact of fully implementing Greater Melbourne's strategic cycling corridors, a network of key cycling routes. Simulations suggested an initial 30% increase in cycling use, raising the mode share to approximately 2.6%, indicating a modest overall impact. Further analysis showed that even with full implementation, on average about half of the lengths of the routed bikeable trips would still occur on roads without any cycling infrastructure. This underscores the need to improve infrastructure on both major corridors and minor roads, and to complement these improvements with behavioural interventions. Bike use Bicycle infrastructure Mode choice model Active transport MATSim Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Apr, 2025 Read the published version in Transportation → Version 1 posted Editorial decision: Revision requested 26 Aug, 2024 Reviews received at journal 22 Aug, 2024 Reviews received at journal 06 Aug, 2024 Reviewers agreed at journal 27 Jul, 2024 Reviewers agreed at journal 26 Jul, 2024 Reviewers invited by journal 25 Jul, 2024 Editor assigned by journal 24 Jul, 2024 Submission checks completed at journal 07 Jun, 2024 First submitted to journal 06 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4538181","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338547567,"identity":"2e1cb11e-ee1d-4a1d-b290-7c91ffe84108","order_by":0,"name":"Afshin 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