A Real Time Green Map for Smart Mobility using AI

In the field of smart mobility, Artificial Intelligence (AI) approaches are influential and can give a highly beneficial contribution. GREEMO project aims to develop, through AI technologies, a real-time ecological map of the road traffic. This map allows electric vehicles (EVs) and thermal vehicles (TVs) to display respectively energy consumption cost and CO2 emission on the different road sections. The road traffic ecological map will not only be able to visualize the real-time energy consumption and CO2 emission of road traffic, but also optimize energy consumption and CO2 emission by proposing low-consumption and low-CO2 emission routes. This map is similar to traffic maps currently deployed in GPS. Thus, EVs would be able to estimate the amount of energy required to complete their routes, and TVs would be able to estimate the amount of CO2 emission of their travels. The ecological map will make it possible to integrate energy consumption and CO2 emission criteria in the choice of routes, offering to the drivers an optimal travel mode. It will also be useful for EVs and TVs fleet operators by allowing them better route planning during their missions (delivery/collection of goods, cold chain, etc.) taking into account energy consumption and CO2 emission. In addition, it can be used in predictive maintenance operations if the differences between real and planned energy consumption and CO2 emission are significant. The project thus aims to develop an innovative platform with very high added value on several aspects: EVs energy consumption and TV CO2 emission modeling-based AI in complementarity with the model based on the laws of physics, the development of a real-time ecological map, and the integration of the energy and CO2 emission criteria in the choice of routes. The resulting platform will combine two different but complementary approaches (deterministic and stochastic), to model the energy consumption and CO2 emission on the different road sections.  This will make it possible to identify the most optimal route in terms of EV energy consumption and TV CO2 emission, to analyze in real-time driving behaviors, and to offer smart mobility services.

• EDI University of Latvia
• INSOFDEV Romania

• Research Laboratory 
• Companies in Automotive Applications 
• Regions and agglomerations