Estimation of instantaneous pollutant emissions (and energy consumption) from road transportation through coupling mesoscopic traffic modeling and speed profile generation

Estimating traffic-related energy consumption and pollutant emissions is a complex problem that is relevant for a wide range of problems, from planning to operations. In particular, energy efficiency and pollution metrics play a fundamental role in the environmental impact assessment of new technologies, such as smart cities or connected, cooperative, and autonomous mobility, in order to evaluate new algorithms or the impact of upcoming products.
Besides the characteristics of the road network, the key role in determining these environmental metrics is played by the speed trajectories followed by the vehicles in the network. Most of existing methods provide only mean-value estimations per road-link. However, mean speed is largely insufficient to capture the dynamic behavior that is responsible for local peaks and affects substantially the total amount. Therefore instantaneous speed profile (ISP) estimation is needed on the various road-links that compose the road network considered. 
The approach proposed consists of (i) generating mobility data with a “mesoscopic” traffic simulator (MATSim) using a limited amount of publicly available information, (ii) using the average speed/flows calculated as the input of an ISP estimator, (iii) evaluating the ISP per road-link fulfilling these averages and satisfying spatial and time correlation. Overall, the proposed approach would fill the existing gap between macroscopic data and instantaneous/local consumptions and emissions. 
Once the coupling made, possible applications of the approach should be tested. To this purpose, a case study shall be defined, modeled, and analyzed. A baseline scenario should be defined from a current situation in a chosen road network (at a region or urban area level). Then changes in the infrastructure, in the car fleet, in the mobility offer could be analyzed and benefits in terms of energy consumption and local emissions could be evaluated.

Keywords: traffic modelling, autonomous mobility, air quality

• Supervisor    Dr. Antonio SCIARRETTA, IFP Energies nouvelles, antonio.sciarretta@ifpen.fr 
• Doctoral School    ED580 - STIC Sciences et Technologies de l'Information et de la Communication, https://www.universite-paris-saclay.fr 
• Co- supervisor    Dr. Milos BALAC, Institute for Transport Planning and Systems (IVT), ETH Zurich, Switzerland, milos.balac@ivt.baug.ethz.ch 
• PhD location    IFP Energies nouvelles, Rueil-Malmaison, France
• Duration and start date    3 years, starting in fourth quarter 2021
• Employer    IFP Energies nouvelles, Rueil-Malmaison, France
• Academic requirements    University Master degree in Transportation Engineering, Information Engineering, Dynamical Systems and Control Science
• Language requirements    Fluency in English. Fluency in, or willingness to learn, French