TEMA (Transport tEchnology and Mobility Assessment platform)
Big data in support of regional mobility and vehicle emissions analysis. TEMA (Transport tEchnology and Mobility Assessment platform) is a flexible and modular big data platform, based on GPS mobility data and interfaced with GIS-based digital geographic mapping systems. It aims at harnessing the potential of big data in support to transport policy, performing a wide-range of mobility analyses. It characterises the driving behaviour of the vehicles at a regional level and investigates the potential of innovative vehicle technologies nested in complex transportation systems. The platform is designed also to serve real-world vehicle emission applications. It evaluates driving and evaporative gaseous emissions from conventional fuel vehicles and eco-innovation technologies assessments.
Outcome impact:
The applications of TEMA carried out so far included:
• quantification of the real-world potential of deploying electrified vehicles under different technological and infrastructural constraints, (De Gennaro et al., 2014a), (Paffumi et al., 2015);
• quantification and geo-referencing of the shift from oil to electric energy and the impact on the electricity distribution grid of EVs (De Gennaro et al., 2014b);
• design of a customer-driven smart recharge infrastructure and tailored V2G application in public areas (De Gennaro et al., 2015), (Paffumi et al., 2016);
• evaluation of the driving and evaporative real world emissions from the current fleet of conventional vehicles and gaseous emissions reduction potential from the introduction of new vehicle technologies (Martini et al., 2014), (De Gennaro et al., 2016b);
• evaluation of the Utility Factor (UF), based on collected vehicle activity data to evaluate the real world conditions of use of plug-in hybrid electric vehicles, (Paffumi et al., (2018));
• support to the eco-innovation technologies assessments, (Lodi et al., 2018);
• in-vehicle battery durability assessment (De Gennaro et al., n.d.), (Loiselle-Lapointe et al., 2018).