Exploring crowdsourcing information to predict traffic-related impacts

• Autor(a) principal: Tafidis, Pavlos
• Data de Publicação: 2017
• Outros Autores: Teixeira, João, Bahmankhah, Behnam, Macedo, Eloísa, Coelho, Margarida C., Bandeira, Jorge
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10773/22983
• topic: Crowdsourcing; Traffic impacts; Emissions; Air pollutants

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 volumes of traffic were counted during different days of the week. The emissions estimation was based on the concept of Vehicle Specific Power (VSP), which has the capability to predict emissions during a trip often-according recorded second-by-second vehicle dynamics. Various tests were conducted in order to explore the potential correlations between these data sets and the information of a certain place’s busy times 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 environmental and traffic-related impacts.