Abstract

The main objective of this work is to present a modular platform to manage traffic information for smart mobility. The management and collection of dynamic data is a challenging process especially in the context of low penetration of floating car data (FCD) and limited availability of traffic monitoring stations. In this work, three different road segments of a European medium-sized city were selected to collect vehicle dynamic data over multiple scenarios of traffic demand. Simultaneously, traffic volumes were recorded in real time. The main objective of this pilot experiment was to assess how it would be possible to read and predict traffic congestion and emissions levels with limited information and how data from multiple sources should be managed in order to correlate and deal with this information in real time. It was possible to correlate simultaneously multiple data set such as congestion values, specific vehicle power (VSP) mode distribution, Google traffic data and emission. Preliminary findings suggest that in urban arterials travel time and congestion levels can be reliable indicators for estimating emissions in real time. In sections of rural arterials, the estimation of real-time traffic performance is more complex. Key issues towards the implementation of a prototyping platform in an urban context are also discussed