[Call for applications] PhD position in urban mobility and artificial intelligence

Subject:

Electronic mobility market for optimized urban travel chains.

 

Thesis subject description:

Urban sprawl and economic development increasingly place pressure on urban road infrastructures and public transport modes, highlighting mobility as a theme that must be not only efficient but also sustainable.

Conventional traffic models do not account for the greater or lesser ease of transport offered to the user, which is clearly a factor in generating travel demand for passenger transport in particular.

Nonlinear phenomena such as congestion emerge and become crippling in an era of exchanges seeking efficiency. Transport users therefore spend and lose more and more time, assimilated to a cost through the concept of the value of time, whose complexity stems from the fact that transport ultimately remains a good with quality that varies with traffic.

In this doctoral research project, based on Origin-Destination field surveys in the city of Casablanca, we will deploy innovative solutions to define the domain of mobility efficiently and intelligently through the use of new protocols, data processing and analysis and, more specifically, the use of Artificial Intelligence (AI) employing high-performance Machine Learning algorithms.

These technological innovations will change both transport needs and the means to satisfy them, presenting a real opportunity to solve the difficulties that undermine mobility.

Indeed, the application of AI to mobility, notably calling on the family of artificial neural networks, aims to overcome challenges related to growing travel demand, traffic flow management and environmental degradation by internalizing transport’s negative externalities.

These intelligent transport system techniques will therefore offer optimization possibilities and open currently underexplored choice spaces such as temporal shifts and real-time modal transfers.

This project thus aims to contribute to the construction of this new category of intelligent models to solve congestion problems and propose appropriate instruments, such as a dynamic pricing mechanism.

In conclusion, based on the developed modeling, this project will result in the development of a next-generation Intelligent Personal Travel Assistant (IPTA) and intermodal system capable of proposing to the user an optimized chain of trips designed to minimize the generalized cost of any anticipated Origin-Destination link.

 

Keywords:

Urban Mobility, AI, Modal Shifts, Externalities, Congestion, Traffic Models and Simulations, Financing Models.

 

Profile and skills sought:

• Statistician and applied economist engineer with a focus on economic modeling and econometric analysis (programming skills are highly appreciated).

OR

• Master in applied mathematics/Industrial engineering with strong knowledge in operations research (optimization, simulation and algorithms) and programming.
• Clear interest in transport and logistics.
• Autonomous, analytical and critical thinking.
• Autonomous, analytical and critical thinking.
• Very good level of French and good level of English both spoken and written.

Thesis supervisors:

Pr. Othmane Benmoussa - Mobility, Innovation, Logistics Laboratory / Euromed Research Center

 

E-mail: o.benmoussa@ueuromed.org 
Cedoc.admission@ueuromed.org

FUNDING : Within the framework of the Al Khawarizmi program.

SUBMISSION DEADLINE: 14 APRIL 2025