PIONEER-TOPIC#2025: On-Emergency Demand: A New Mobility Service Enhancing Accessibility During [...]

European Commission; France; Sur place; EUR 80 000 - 100 000; Plein temps

Résumé du poste

L’Université Gustave Eiffel recherche un doctorant en ingénierie pour un projet sur le service de demande en situation d’urgence. L’objectif est d’optimiser la mobilité urbaine en période de crise, avec une approche multidisciplinaire intégrant des méthodes de modélisation et simulation. Le candidat devra posséder un master en ingénierie, mathématiques appliquées ou un domaine similaire, avec un intérêt marqué pour la gestion de crise. Le projet inclut des séjours de recherche à l'Université IUAV de Venise, favorisant l'internationalité et l'innovation dans le domaine.

Prestations

Accès à des ressources et laboratoires à l'Université

Possibilité de mobilité internationale

25 jours de congés payés annuels

Qualifications

• Master en Ingénierie ou domaine équivalent requis.
• Bonne maîtrise des systèmes de transporte et de modélisation.
• Compétences en programmation (Python, Java) nécessaires.

Responsabilités

• Développer et évaluer un système de demande en situation d’urgence.
• Modéliser l’accessibilité en conditions de crise.
• Évaluer les performances par optimisations et simulations.

Connaissances

Optimisation

Recherche opérationnelle

Modélisation agent-based

Systèmes de mobilité

Programmation (Python, Java)

Gestion de crise

Formation

Master en Ingénierie des Transports

Master en Mathématiques Appliquées

Master en Informatique

Master en Urbanisme

Master en Recherche Opérationnelle

Outils

MATSim

SUMO

Description du poste

Organisation/Company Université Gustave Eiffel Department COSYS Research Field Engineering » Civil engineering Mathematics » Applied mathematics Computer science » Modelling tools Computer science » Programming Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France Application Deadline 24 Aug 2025 - 00:00 (Europe/Paris) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 7 Jul 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

In the face of increasingly frequent and complex crises, ranging from natural disasters to infrastructure breakdowns and pandemics, ensuring accessible and adaptable mobility services is a growing priority for urban transport systems. This PhD research, conducted in collaboration between Université Gustave Eiffel and IUAV University of Venice, introduces a novel concept: the On-Emergency Demand service. Building on the principles of on-demand mobility, this service is reconfigured specifically for crisis contexts. The Covid-19 pandemics has dramatically highlighted the impacts of emergency conditions on urban transport, both from the supply and demand side, resulting in a radical change of the consolidated mobility schemes[1,2].

Previous studies have shown that shared mobility and on-demand transport services, when effectively designed, can significantly enhance accessibility [3,4]. Their inherently flexible nature makes them promising candidates for deployment during emergency events. However, their traditional design must be transformed to meet the unique constraints of crisis response. In particular, the matching process between riders and vehicles must be highly efficient, prioritize evacuation urgency, and operate with minimal delay [5]. In this sense, the identification, design and sizing of meeting points, as well as the transport management of these areas is another fundamental aspect to be considered.

Unlike conventional on-demand services, which typically optimize objectives such as profit maximization or fleet utilization [6], On-Emergency Demand (OED) must adhere to alternative mathematical formulations. These include:

Objective functions aimed at minimizing total clearance time, maximizing population coverage, and ensuring equitable service delivery;

Constraints reflecting safety-critical priority rules, real-time road network disruptions, and shelter or hospital capacity limitations;

Matching algorithms that prioritize proximity to threat zones, compliance with evacuation protocols, and dynamic routing based on vehicular communication [5].

The research will focus on three core areas:

• Conceptual design: Formalizing the operational logic and emergency-specific architecture of the OED system.
• Accessibility Modelling: Developing a framework for measuring access under crisis conditions, extending methodologies such as the travel-cost approach [7].
• Simulation and Evaluation: Assessing performance using simulation-based optimization and traffic assignment models under varied crisis typologies and urban densities.

Methodology:

The proposed methodology integrates both system-level modeling and algorithmic optimization. First, the problem will be framed through a comprehensive risk assessment, accounting for the type of disaster, network topology, and the spatial distribution of critical destinations such as hospitals and shelters. These elements will guide the definition of dynamic demand and network vulnerability profiles.

The optimization component will target real-time rider-to-vehicle matching under crisis constraints. The mathematical formulation will integrate multi-objective functions (e.g., minimizing evacuation time, maximizing access equity), and be subject to constraints reflecting real-time network disruptions, traffic bottlenecks, and prioritized routing to critical facilities. Techniques such as time-dependent shortest path algorithms will be explored. To ensure scalability and adaptability in real-time contexts, heuristic and metaheuristic approaches, including large neighborhood search, will be incorporated.

The simulation framework will be built on open-source, agent-based simulation platforms such as MATSim or SUMO, enabling detailed modeling of individual traveler behavior, transport system dynamics, and network degradation during emergency conditions. This will facilitate the evaluation of On-Emergency Demand performance across different types of crises (e.g., fast-onset wildfires vs. gradual flooding), demand profiles, and urban forms. Key features will include dynamic demand generation, adaptive routing, and infrastructure disruptions.

Ultimately, simulation outputs will be validated against empirical data from real-world scenarios, including the 2018 Camp Fire evacuation in California, evacuation planning scenarios in Luxembourg, and real or simulated case studies located in the north-eastern part of Italy. This validation will support the generalizability and reliability of the proposed models. The combined expertise from prior work on dynamic ride-sharing, evacuation under communication constraints, and accessibility policy metrics provides a solid foundation for the interdisciplinary and practical development of this service.

References

[1] Nocera S., Bruzzone F., Cavallaro F., 2024. COVID-19 response in Italy: Focus on public transport. In: Shibayama T., Emberger G. (eds.), International perspectives on public transport responses to COVID-19, pp. 329-339. Elsevier, Amsterdam. DOI: 10.1016/B978-0-443-13295-7.00031-9. ISBN: 978-0-443-13295-7

[2] Cavallaro F., Nocera S. (2024). Covid-19 effects on transport-related air pollutants: Insights, evaluations, and policy perspectives. Transport Reviews 44(2): 483-516. doi: 10.1080/01441647.2023.2225211

[3] Bruzzone, F., Cavallaro, F., & Nocera, S. Accessibility potential of long-distance Mobility-as-a-Service.

[4] Alisoltani, N., & Leclercq, L., Zargayouna, M. Can dynamic ride-sharing reduce traffic congestion?

[5] Idoudi, H., Ameli, M., Alisoltani, N., & Zargayouna, M. Large-Scale Evacuation with Vehicular Communication: Navigating Through Dark Zones.

[6] Alisoltani, N., Delhoum, Y., Ameli, M., & Zargayouna, M. Optimizing Shared Mobility: A Penalized Column Generation Model for Peer-to-Peer Ride-Sharing.

[7] Cavallaro, F., Bruzzone, F., & Nocera, S. Accessibility to cultural economy opportunities by high-speed rail.

Where to apply

E-mail [e-mail]

Requirements

Research Field Engineering » Civil engineering Education Level Master Degree or equivalent

Research Field Engineering » Industrial engineering Education Level Master Degree or equivalent

Research Field Computer science » Modelling tools Education Level Master Degree or equivalent

Research Field Mathematics » Applied mathematics Education Level Master Degree or equivalent

Skills/Qualifications

• Strong background in optimization, operations research, simulation, or mobility systems.
• Knowledge of agent-based modeling platforms (MATSim, SUMO) is a plus.
• Programming skills (Python, Java, or similar).
• Fluency in English (working language of the PhD).
• Interest in crisis management and sustainable mobility.

Specific Requirements

• A Master’s degree (or equivalent) in one of the following fields:
  Transportation Engineering, Applied Mathematics, Computer Science, Urban Planning, or Operations Research.
• Proven interest or background in mobility systems, transport modeling, simulation-based optimization, or crisis/emergency management.
• Strong programming skills, preferably in Python, Java, or C++.
• Familiarity with agent-based simulation tools (e.g., MATSim, SUMO) and/or optimization algorithms (e.g., shortest path, vehicle routing, metaheuristics) is an asset.
• Good command of English (written and spoken) – working language of the PhD.
• Ability to work independently while collaborating across institutions.
• Willingness and ability to spend research stays abroad, especially at IUAV University of Venice, during the PhD.

Languages ENGLISH Level Excellent

Research Field Engineering » Civil engineeringMathematics » Applied mathematicsComputer science » Modelling toolsComputer science » Programming

Additional Information

• High-quality doctoral training leading to a PhD degree delivered by Université Gustave Eiffel, under joint supervision with IUAV University of Venice (PIONEER partner).
• Appointment for 36 months under a full-time doctoral contract.
• Employment under French labour law, including 35 hours per week, 25 days of annual paid leave and access to social security and health insurance
• Opportunity to work in a multidisciplinary international team, with guidance from experts in shared mobility, transportation resilience, and urban accessibility.
• Potential eligibility for the European Doctorate label, subject to conditions.
• Participation in international workshops, scientific conferences, and mobility to partner institutions in the EU.
• Access to laboratories and resources at both universities (including simulation platforms, datasets, and computing facilities).

Eligibility criteria

• Master’s degree or equivalent (Bac+5) in one of the following fields:
  • Transportation Engineering
  • Urban Planning
  • ,Computer Science
  • Applied Mathematics
  • Operations Research
• Strong academic background and motivation to conduct interdisciplinary research
• Proficiency in English (spoken and written)
• Familiarity with transport modeling, simulation or optimization methods is an asset
• Candidates must meet mobility rules under the PIONEER framework

Selection process

The thesis will take place under the PIONEER+ project, a European Universities Alliance, coordinated by université Gustave Eiffel.
Candidates pre-selected by the thesis supervisors will be invited to an interview in English before a panel composed of members of the PIONEER alliance between September 22nd and October 15th, 2025.

Additional comments

The doctoral candidate will conduct 12 months of research mobility at IUAV University of Venice during the PhD program.