Exploring crowdsourcing information to predict traffic-related impacts

Due to the increased public awareness on global climate change and other environmental problems, advanced strategies and tools are being developed and used to reduce the environmental impact of transport. The main objective of this paper is to explore the potential of using crowdsourcing information as an alternative or complementary source data to predict traffic-related impacts. Three main road connections to two important commercial areas in the city of Aveiro in Portugal, are examined. Driving patterns over different periods were collected using a probe vehicle equipped with a GNSS data logger and traffic volumes were counted during different days. The emissions estimation was based on the concept of Vehicle Specific Power (VSP), which has the capability to predict emissions during a trip through second-by-second vehicle dynamics data. Various tests were conducted in order to explore the potential correlations between these data sets and the information of the peak periods of a certain place that are provided by Google Maps. The findings of the study prove the potential of crowdsourcing information and shows that ICT technologies can be used to estimate emissions and traffic-related impacts.