Active travel modelling: a methodological approach to networks for walking and cycling commuting analysis

Abstract Walking and cycling, commonly referred to as active travel, have become integral components of modern transport planning. Recently, there has been growing recognition of the substantial role that active travel can play in making cities more liveable, sustainable and healthy, as opposed to more traditional vehicle-centered travel. This shift in perspective has spurred interest in developing new datasets of varying resolution levels to represent, for instance, walking and cycling street networks. This has also led to the development of tailored computational tools and quantitative methods to model and analyse active travel flows. In response to this surge in active travel-related data and methods, our study develops a methodological framework primarily focused on walking and cycling as modes of commuting. We explore commonly used data sources and tools for constructing and analysing walking and cycling networks, with a particular emphasis on distance as a key factor that influences, describes, and predicts commuting behaviour. We propose and explore a workflow consisting of three main steps: (1) the construction of the active travel network, (2) routing choices considering distance, and (3) modelling of commuting flows on the network. The network efficiency is analysed by measuring the network detours resulting from the commuting patterns. These are modelled making use of the open-source R package cppSim developed within this project, offering a reproducible and scalable solution for future analysis. Our findings demonstrate the importance of tailored network construction and routing methodologies in accurately predicting active travel flows, providing valuable insights for urban transport planning and policymaking.