Feel Old Yet? Updating Mode of Transportation Distributions from Travel Surveys using Data Fusion with Mobile Phone Data

TL;DR

This paper presents a novel data fusion method combining mobile phone application data with traditional surveys to update transportation mode distributions, revealing recent shifts in urban mobility patterns in Santiago, Chile.

Contribution

It introduces a cost-effective approach using data fusion and matrix factorization to infer current transportation modes from mobile data, enhancing traditional survey-based datasets.

Findings

Mass-transit usage decreased in Santiago from 2012 to 2020.

Motorised transport increased across Santiago.

Infrastructure improvements boosted public transport resilience.

Abstract

Up-to-date information on different modes of travel to monitor transport traffic and evaluate rapid urban transport planning interventions is often lacking. Transport systems typically rely on traditional data sources providing outdated mode-of-travel data due to their data latency, infrequent data collection and high cost. To address this issue, we propose a method that leverages mobile phone data as a cost-effective and rich source of geospatial information to capture current human mobility patterns at unprecedented spatiotemporal resolution. Our approach employs mobile phone application usage traces to infer modes of transportation that are challenging to identify (bikes and ride-hailing/taxi services) based on mobile phone location data. Using data fusion and matrix factorization techniques, we integrate official data sources (household surveys and census data) with mobile phone application usage data. This integration enables us to reconstruct the official data and create an updated dataset that incorporates insights from digital footprint data from application usage. We illustrate our method using a case study focused on Santiago, Chile successfully inferring four modes of transportation: mass-transit, motorised, active, and taxi. Our analysis revealed significant changes in transportation patterns between 2012 and 2020. We quantify a reduction in mass-transit usage across municipalities in Santiago, except where metro/rail lines have been more recently introduced, highlighting added resilience to the public transport network of these infrastructure enhancements. Additionally, we evidence an overall increase in motorised transport throughout Santiago, revealing persistent challenges in promoting urban sustainable transportation. We validate our findings comparing our updated estimates with official smart card transaction data.