07/12/2021
Marie Skłodowska-Curie Actions

MSCA-COFUND-CLEAR-Doc - PhD Position #CD21-03: Mobility as a Service in urban transportation networks: simulation-based analysis and optimization

This job offer has expired


  • ORGANISATION/COMPANY
    Université Gustave Eiffel
  • RESEARCH FIELD
    Computer scienceInformatics
    MathematicsApplied mathematics
    Other
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    21/03/2022 17:00 - Europe/Brussels
  • LOCATION
    France › Marne-La-Vallée
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    35
  • OFFER STARTING DATE
    01/10/2022
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / Marie Skłodowska-Curie Actions COFUND
  • MARIE CURIE GRANT AGREEMENT NUMBER
    101034248

OFFER DESCRIPTION

Context

In recent years, the increasing number of transport services offered in cities and the advancements in technology and ICT have introduced an innovative and emerging Mobility as a Service (MaaS) concept. MaaS builds on a single, digital customer interface to sources and manages travel-related services (ITF, 2020). At its core, it supports the integration of scheduled public transport modes with on-demand services (such as ride-sourcing, bike, car sharing, and taxis) into a comprehensive mobility offer. This way, all modes of transport are grouped in one mobile application wherein users can choose the plan regarding routes, modes including reservation, and payment options for each trip.

MaaS offers more accessibility to all users and involves a remarkable improvement in the efficiency of the urban mobility system. However, existing MaaS projects still face tremendous challenges and do not address all transportation modes. On the one hand, providers of on-demand services should accept sharing data with all other MaaS ecosystem members in order to integrate planning and payment into a standard application and contribute to strengthening the public transport supply. On the other hand, the acceptability and utility of users need to be guaranteed. Therefore, users should be accompanied to follow the transition from mobility-based on private vehicles to more sustainable trips where public transport would be combined with shared mobilities.

Several studies have addressed the challenges of MaaS and proposed different governance models to provide guidelines that would enable its full implementation (Ile de France mobilities, 2020; Jittrapirom et al., 2017). However, to the best of our knowledge, no study addresses the complete picture of interactions between demand and supply sides. Regarding the demand side, there are several projects with real data that have developed discrete choice models to reflect the users’ preferences towards using MaaS systems (Sochor et al., 2015; Feneri et al., 2020). This thesis aims to plug in the results of the mentioned research projects on the demand side to an agent-based simulator and develop for the first time a simulation framework to investigate a MaaS ecosystem. Indeed, all simulation-based studies on MaaS considered a single on-demand service (e.g., ridehailing, taxi, etc.) that competes or completes the existing supply (e.g., Jung, et al., 2013; Ikeda, et al., 2015; Biswas, et al., 2017; Li, et al., 2018; Narayan, et al., 2020; Babar & Burtch, 2020; Zhu, et al., 2020; Alisoltani et al., 2021).

This thesis will address more than one mobility system under the MaaS principle. Moreover, the existing works in the literature are in general offered two separate settings: centralized or decentralized dispatcher (Nourinejad, et al., 2014; Poulhès et Berrada, 2019; Sieber et al., 2020, Ameli et al., 2021). However, the comparison between two settings are missing in the literature. In addition, addressing a hybrid framework including centralized MaaS and other decentralized mobility systems is also an interesting research direction for further investigation. Another challenge is to evaluate the performance of a MaaS system compared to an existing system without full implementation of MaaS, and its interactions with other competitive mobility providers. In other words, the transition from a current transportation system to a fully integrated system with MaaS needs to be investigated in order to provide insights regarding the road map toward the fully implemented MaaS system.

Objective

The main objectives of the thesis are to describe, explore and analyze an ecosystem that would bring together (i) shared mobility services integrated into a MaaS and (ii) independent services out of MaaS. This analysis aims to ultimately determine the balance between the two sets of services and subsequently assess the profitability for each service providers and for the other stakeholders (passengers, citizens, organizing authority).

In particular, the thesis will:

• Identify different configurations and business models of MaaS through a broad review of existing experiences and studies,

• Design a methodological framework for the simulation and optimization of MaaS as a centralized system that integrates the public transport modes and at least a provider of an on-demand service,

• Design and evaluate different MaaS deployment scenarios in a multimodal and competitive universe and assess them from different perspectives, i.e., economic, social, and environmental

Methodology

The scope of this thesis lies at the intersection of mathematical optimization and transport economics. It will include, in particular, a bottom-up technical analysis, which will define the various services offered from the various physical and human components at a very fine level of detail. Centralized governance models for a subset of services will then be designed in order to take into account their different components and technical constraints.

We will consider at least three categories of operators: (i) those who will agree to join the MaaS ecosystem regularly, (ii) those who prefer not to join the MaaS ecosystem, (iii) and those who will agree to join the MaaS occasionally (for instance in peak-hour or depending on the demand volume, the congestion of PT, etc.). In addition to defining mathematical models for these scenarios, solution methods need to be designed to optimize the models and provide the results for each of these scenarios.

The technical analysis formulated in mathematical optimization problems will represent the basis of economic analysis, which will determine the conditions for the success of MaaS that ensures the viability of public transport, the profit for the on-demand service providers and the increase of the social welfare in general.

This analysis from two perspectives will be carried out by relying on multi-agent simulation models (an agent-based simulator, e.g., MATSim type), which detail the operation of several services in real-time while explaining the vehicle and passenger movements one by one."

International Mobility:

To be discussed with the PhD thesis supervisor.

More Information

Benefits

  • High-quality doctoral training rewarded by a PhD degree, delivered by Université Gustave Eiffel
  • Access to cutting-edge infrastructures for research & innovation.

  • Appointment for a period of 36 months based on a salary of 2 700 € (gross salary per month).

  • Job contract under the French labour legislation in force, respecting health and safety, and social security: 35 hours per week contract, 25 days of annual leave per year.

  • International mobility will be mandatory

  • An international environment supported by the adherence to the European Charter & Code.

  • Access to dedicated CLEAR-Doc trainings with a strong interdisciplinary focus, together with a Career development Plan.

 

Eligibility criteria

  • At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree. At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.
  • At the time of the deadline, applicants must be in the first four years (full-time equivalent research experience) of their research career (career breaks excluded) and not yet been awarded a doctoral degree. Career breaks refer to periods of time where the candidate was not active in research, regardless of his/her employment status (sick leave, maternity leave etc). Short stays such as holidays and/or compulsory national service are not taken into account.
  • At the time of the deadline, applicants must not have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 years immediately prior to the call deadline.
  • Applicants must be available to start the programme on schedule (around 1st October 2022).

Selection process

Additional comments

  • The First step before applying is contacting the PhD supervisor. You will not be able to apply without an acceptation letter from the PhD supervisor.
  • Please contact the PhD supervisor for any additional detail on job offer.
  • There are no restrictions concerning the age, gender or nationality of the candidates. Applicants with career breaks or variations in the chronological sequence of their career, with mobility experience or with interdisciplinary background or private sector experience are welcome to apply.
  • Support service is available during every step of the application process by email: clear-doc@univ-eiffel.fr

Web site for additional job details

Offer Requirements

  • REQUIRED EDUCATION LEVEL
    Computer science: Master Degree or equivalent
    Mathematics: Master Degree or equivalent
  • REQUIRED LANGUAGES
    ENGLISH: Good

Skills/Qualifications

  • At the time of the deadline, applicants must be in possession or finalizing their Master’s degree or equivalent/postgraduate degree.
  • At the time of recruitment, applicants must be in possession of their Master’s degree or equivalent/postgraduate degree which would formally entitle to embark on a doctorate.

Work location(s)
1 position(s) available at
Université Gustave Eiffel
France
Marne-La-Vallée
77454
5, Boulevard Descartes

EURAXESS offer ID: 716432

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