Generating traffic flow and speed regional model data using internet GPS vehicle records

© 2019 The Authors..

Nowadays, many smart-phones and vehicles are equipped with Global Position System (GPS) for tracking and navigation purposes, providing an opportunity to derive highly representative local vehicular flow and estimate vehicular emissions information. Here, we report and discuss methods used to handle large volumes of such activity data, namely 124 million GPS recordings from the web page Maplink.com.br, extract high spatial resolution vehicular flow information for a vast area in South-east Brazil, and correct for bias using traffic counts observations for the same area. The method consists in filter speed and accelerations, assign buffers to the road network, aggregate speed by street, fill missing number of lanes, generate traffic flow. Methods presented here were used to inform traffic-related air quality modelling and used as part of local air pollution management activities but are also amenable to any work that would be enhanced by more locally representative or time-resolved inputs for traffic flow, e.g. traffic network management, and demand modelling. •124 million GPS observations from electronic devices were used to generate traffic flow.•Spatial bias was investigated and accounted for using independent local traffic count data.•Traffic count rescaled GPS traffic flow provide a robust description of spatial and quantitative traffic patterns.

Medienart:

E-Artikel

Erscheinungsjahr:

2019

Erschienen:

2019

Enthalten in:

Zur Gesamtaufnahme - volume:6

Enthalten in:

MethodsX - 6(2019) vom: 28., Seite 2065-2075

Sprache:

Englisch

Beteiligte Personen:

Ibarra-Espinosa, Sergio [VerfasserIn]
Ynoue, Rita [VerfasserIn]
Giannotti, Mariana [VerfasserIn]
Ropkins, Karl [VerfasserIn]
de Freitas, Edmilson Dias [VerfasserIn]

Links:

Volltext

Themen:

Brazil
Data
GPS
Internet
Journal Article
Spatial bias
Traffic flow generation based on GPS recordings
Vehicles

Anmerkungen:

Date Revised 30.09.2020

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.1016/j.mex.2019.08.018

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM302716025