Estimating distance decay: for the National Propensity to Cycle Tool (NPCT)

Robin Lovelace, University of Leeds. Talk at the Institute for Transport Studies (ITS)

Slides: speakerdeck.com/robinlovelace

I What is distance decay?

Discovering distance decay

Source: Lovelace (2014): my thesis

Distance of trip != distance/yr

Source: Lovelace (2014): my thesis

Distance decay in active travel

Data: derived from Iacono et el. (2010)

Distance decay: the formula

p = f(d)

Euclidean or route distance?

Source: Lovelace (2014): my thesis

Distance decay in the literature

Source: Lovelace et al., forthecoming.

Tested functional forms

Source: Martínez and Viegas (2013)

DD functional forms

Exponential vs cubic vs linear

Some real data

Source: Lovelace et al. (forthcoming)

Linear model to the data

Cubic polynomial models

Log-square-root model

II Why distance decay?

Source: NPCT modelOutput (Leeds)

Distance decay in everyday life

Source: Lovelace (2014): my thesis

Distance and energy use

Distance and mode dependence (Sheffield)

Distance and mode dependence (England)

Source: Lovelace (2014): my thesis

Energy and travel mode

Source: Lovelace (2014): my thesis

III The uses of distance decay

Uses of dd: a few ideas

● If we're to transition away from fossil fuels, we must use modes that are less energy intensive

● Distance decay for sustainable travel modes can tell us what future travel patterns must look like

● Characterising travel systems● Especially relevant for active travel● The National Propensity to Cycle Tool (NPCT)

'Spatial interaction

models'

Source: Lovelace et al. (forthecoming), Geographical Analysis

DD to characterise travel systems

Modelling travel

Source: Lovelace et al. (2014)

IV Wider context of distance decay

Resulting report: national benefits

Benefits of cycling nationwide

See https://tinyurl.com/conversation-cycling

Webtag estimates of benefit:cost

See https://tinyurl.com/conversation-cycling

https://www.gov.uk/government/publications/webtag-tag-overview

An open source policy planning tool (+ live demo!)

DD in the NPCT

Further work on distance decay

● The distance-decay of road traffic incidents?● Its use to estimate non-work travel?● Verification of dd parameters using Big Data

Key references

● Iacono, M., Krizek, K. J., & El-Geneidy, A. (2010). Measuring non-motorized accessibility: issues, alternatives, and execution. Journal of Transport Geography, 18(1), 133–140. doi:10.1016/j.jtrangeo.2009.02.002

● Lovelace, R., Clarke, M., Cross, P., & Birkin, M. (n.d.). Verification of big data for estimating retail flows: a comparison of three sources against model results. Geographical Analysis.

● Lovelace, R., Malleson, N., Harland, K., & Birkin, M. (2014). Geotagged tweets to inform a spatial interaction model: a case study of museums. Arxiv Working Paper.

● Lovelace, R. (2014). The energy costs of commuting: a spatial microsimulation approach. University of Sheffield. Retrieved from http://etheses.whiterose.ac.uk/5027/

● Martínez, L. M., & Viegas, J. M. (2013). A new approach to modelling distance-decay functions for accessibility assessment in transport studies. Journal of Transport Geography, 26, 87–96. doi:10.1016/j.jtrangeo.2012.08.018