Backcasting: optimal control of mobility systems based on a strategic system dynamic model

A new approach is emerging, which is expected to change the way we conceive and evaluate the future mobility of people and goods. Whether it will be more electrified, connected, automated, digitalized, or not, will depend on the targets we aim for at specific time horizons: environmental, economic, societal, etc. In the current approach, human decision-makers advocate potential actions that are then assessed by "predicting" their impacts. In the new paradigm, we will first set the goals, and then the roadmap of policies and technologies required to achieve these goals will be established ("backcasting"). Backcasting can be seen as a dynamic optimization process (optimal control). It will be made possible by the availability of a dynamic model that describes mobility systems in very macroscopic terms, yet capable of representing the causal relationships between policies and their impacts.
This doctoral topic represents a fundamental step in an ambitious research program. It focuses on formulating a backcasting optimal control problem (OCP), solving it with methods to be developed, and demonstrating it for one or more appropriately identified test cases. Based on a model, the formulation of the OCP will require the precise definition of inputs, states, optimization criteria, and constraints. The model will then be analyzed and manipulated or simplified to make it compatible with an acceptable resolution of the OCP. Criteria of optimality, stability, constraint satisfaction, and, above all, computational efficiency will be considered to establish the most suitable method. Finally, test scenarios will be processed and executed, and their results analyzed. A demonstration software platform may be prepared and made available to potential users in the form of a web service.

Keywords: Optimization, Optimal Control, Backcasting, Mobility

• Academic supervisor & IFPEN supervisor   Dr Antonio SCIARRETTA , ORCID 0000-0002-4643-0706
• Doctoral School    ED580 – STIC Sciences et Technologies de l’Information et de la Communication, https://www.universite-paris-saclay.fr/en/doctoral-schools/sciences-and-technologies-information-and-communication 
• PhD location    IFPEN, Rueil-Malmaison, France 
• Duration and start date    3 years, starting in the fourth quarter 2024 (Novembre 4)
• Employer    IFPEN 
• Academic requirements    University Master degree in Control Engineering or Transportation Engineering or Applied Mathematics or Information Engineering
• Language requirements    Fluency in French or English, willingness to learn French   

To apply, please send your cover letter and CV to the IFPEN supervisor indicated below.