Big Data for sustainable transport
planning
Robin Lovelace
Researcher, CDRC
@robinlovelace
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Structure
1. What even is ‘Big Data’
2. Data on cycling safety
3. Understanding travel patterns
4. Prioritising new investment
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What is Big Data?
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Various definitions
• 1 Billion+ rows?
• 3 or 4 V’s?
• Software needs?
• Hardware needs?
• Complexity?
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Part I: Data to improve safety
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New insights on populations at risk
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Estimates of cycling riskiness
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Part II: Better understanding of
travel patterns
“Non work flows” are hard to estimate
New sources of data can help
• Mobile phone data ( access and accuracy)
• Dedicated tracking apps
• Passive data collection (Google Maps)
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E.g. Cycle Hackney
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Current research:
Twitter to calibrate SIM
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Scenarios of cycling: national
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Part III: Prioritising new investment
in walking and cycling
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Where do people travel?
https://github.com/npct/pct
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Input: work-time population
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Making data come alive!
https://robinlovelace.shinyapps.io/fixMyPath/
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The future of big data in transport
• Smart tracking and behaviour of driverless
cars
• Real-time bus route decision making
• Intelligent congestion charging zones
• A ‘post-carbon’ transport system
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Thanks for listening!
r.lovelace@leeds.ac.uk @robinlovelace slides:
robinlovelace.net