Can Google Maps Popular Times Be an Alternative Source of Information to Estimate Traffic-Related Impacts?

In almost every transport policy document the mitigation of road transport externalities such as traffic congestion, emissions or noise is one of the main targets. The deployment of ICT (Information and Communication Technologies) tools in transportation systems has played a critical role in increasing the sustainability in urban areas. In recent years, many initiatives tried to estimate traffic variables using alternative sources of information or explore potential correlations between traffic-impacts and data from social media as traditional data collection is usually considered costly and lengthy. The aim of this paper is to explore the potential of using Google Maps feature "Popular times" as an alternative source of information to predict traffic-related impacts. For that purpose, its relationships with traffic volumes, travel times, pollutant emissions and noise of different areas in different periods were examined using linear regression models. Different data sets were collected: i) crowdsourcing information from Google Maps; ii) traffic dynamics with the use of a light-duty vehicle equipped with a GNSS data logger; and iii) traffic volumes. The emissions estimation was based on the concept of Vehicle Specific Power (VSP), while noise estimations were conducted with the use of “The Common Noise Assessment Methods in Europe” (CNOSSOS-EU) model. The findings of this study showed encouraging results as it was possible to establish clear relationships between popular times and traffic volumes, CO₂ emissions and noise levels proving the potential of using web-based information as a cost efficient and effective data to estimate traffic-related impacts.