<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper explores the potential of using crowdsourcing tools, namely Google “Popular times” (GPT) as an alternative source of information to predict traffic-related impacts. Using linear regression models, we examined the relationships between GPT and traffic volumes, travel times, pollutant emissions and noise of different areas in different periods. Different data sets were collected: i) crowdsourcing information from Google Maps; ii) traffic dynamics with the use of a probe car equipped with a Global Navigation Satellite System data logger; and iii) traffic volumes. The emissions estimation was based on the Vehicle Specific Power methodology, while noise estimations were conducted with the use of “The Common Noise Assessment Methods in Europe” (CNOSSOS-EU) model. This study shows encouraging results, as it was possible to establish clear relationships between GPT and traffic and environmental performance.</p></abstract>

This paper explores the potential of using crowdsourcing tools, namely Google “Popular times” (GPT) as an alternative source of information to predict traffic-related impacts. Using linear regression models, we examined the relationships between GPT and traffic volumes, travel times, pollutant emissions and noise of different areas in different periods. Different data sets were collected: i) crowdsourcing information from Google Maps; ii) traffic dynamics with the use of a probe car equipped with a Global Navigation Satellite System data logger; and iii) traffic volumes. The emissions estimation was based on the Vehicle Specific Power methodology, while noise estimations were conducted with the use of “The Common Noise Assessment Methods in Europe” (CNOSSOS-EU) model. This study shows encouraging results, as it was possible to establish clear relationships between GPT and traffic and environmental performance.

Exploring the Potential of Web Based Information of Business Popularity for Supporting Sustainable Traffic Management

Centre for Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering

- Campus Diepenbeek Agoralaan Gebouw H - B-3590 Diepenbeek, Kantoor H-B103b,

Transport and Telecommunication Journal

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This paper explores the potential of using crowdsourcing tools, namely Google “Popular times” (GPT) as an alternative source of information to predict...

Exploring the Potential of Web Based Information of Business Popularity for Supporting Sustainable Traffic Management

Publié en ligne: 27 févr. 2020

Pages: 47 - 60

DOI: https://doi.org/10.2478/ttj-2020-0004

Mots clés
ICT, Google Maps, Crowdsourcing, Noise, missions, Sustainable Transport

© 2020 Jorge M. Bandeira et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Exploring the Potential of Web Based Information of Business Popularity for Supporting Sustainable Traffic Management

Publié en ligne: 27 févr. 2020

Pages: 47 - 60

DOI: https://doi.org/10.2478/ttj-2020-0004

Mots clésICT, Google Maps, Crowdsourcing, Noise, missions, Sustainable Transport

© 2020 Jorge M. Bandeira et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
ICT, Google Maps, Crowdsourcing, Noise, missions, Sustainable Transport