Ph. D. Project
Title:
Urbanloop control: from individual pods to network
Dates:
2024/10/01 - 2027/09/30
Supervisor(s):
Description:
The company Urbanloop SAS develops an on-demand individual rail transport system that allows the user to
move from one point to another without waiting, transfers, or even intermediate stops. It consists of
numerous pods (see figure below) circulating autonomously on interconnected loops.
While the work has just begun for the implementation of a first 2.2 km loop allowing the circulation of 10
pods for the Paris 2024 Olympic Games, Urbanloop is facing new challenges for a city-wide installation. This
scaling requires improving the performance of individual pod control and addressing issues related to a large
number of pods on the circulation loops. The French national ANR COMMITS research project aims to meet
these challenges.
In this context, the objectives of this PhD thesis in control engineering are as listed next.
Individual pods: The goal is to design a control law for an individual pod (i.e., assuming it is the only one
on the circulation network) to meet the specifications provided by Urbanloop in terms of speed regulation
and safety.
Pods network: The second step involves implementing the pods on the circulation network and
considering the constraints involved: avoiding collisions, managing intersections, (dis-)insertion. Cooperative
strategies based on inter-pod communications will be studied, drawing inspiration from existing work on the
control of autonomous vehicles, such as e.g., [1,2,3,4,5].
Experimental validations: The selected control laws will initially be validated through numerical
simulations and, if possible, implemented experimentally on the Tomblaine circuit in the suburbs of Nancy.
This thesis will be funded by the ANR COMMITS project involving CRAN (Nancy), LORIA (Nancy), CNAM (Paris),
and, of course, Urbanloop.
move from one point to another without waiting, transfers, or even intermediate stops. It consists of
numerous pods (see figure below) circulating autonomously on interconnected loops.
While the work has just begun for the implementation of a first 2.2 km loop allowing the circulation of 10
pods for the Paris 2024 Olympic Games, Urbanloop is facing new challenges for a city-wide installation. This
scaling requires improving the performance of individual pod control and addressing issues related to a large
number of pods on the circulation loops. The French national ANR COMMITS research project aims to meet
these challenges.
In this context, the objectives of this PhD thesis in control engineering are as listed next.
Individual pods: The goal is to design a control law for an individual pod (i.e., assuming it is the only one
on the circulation network) to meet the specifications provided by Urbanloop in terms of speed regulation
and safety.
Pods network: The second step involves implementing the pods on the circulation network and
considering the constraints involved: avoiding collisions, managing intersections, (dis-)insertion. Cooperative
strategies based on inter-pod communications will be studied, drawing inspiration from existing work on the
control of autonomous vehicles, such as e.g., [1,2,3,4,5].
Experimental validations: The selected control laws will initially be validated through numerical
simulations and, if possible, implemented experimentally on the Tomblaine circuit in the suburbs of Nancy.
This thesis will be funded by the ANR COMMITS project involving CRAN (Nancy), LORIA (Nancy), CNAM (Paris),
and, of course, Urbanloop.
Keywords:
Control, modeling, autonomous vehicle, Urbanloop, networked system
Conditions:
Duration: 3 years starting preferably in the fall of 2024
Funding: 2100 ¬/month (gross)
We are looking for a candidate holding either a master's degree, an engineering school diploma, or any
equivalent degree in control engineering, applied mathematics, or mechanical engineering (with a strong
background in control engineering in the latter case). Expertise in Matlab is desired.
Please contact Jérémie Kreiss (jeremie.kreiss@univ-lorraine.fr) and Romain Postoyan
(romain.postoyan@univ-lorraine.fr) for more information.
Funding: 2100 ¬/month (gross)
We are looking for a candidate holding either a master's degree, an engineering school diploma, or any
equivalent degree in control engineering, applied mathematics, or mechanical engineering (with a strong
background in control engineering in the latter case). Expertise in Matlab is desired.
Please contact Jérémie Kreiss (jeremie.kreiss@univ-lorraine.fr) and Romain Postoyan
(romain.postoyan@univ-lorraine.fr) for more information.
Department(s):
| Control Identification Diagnosis |
Funds:
ANR COMMITS
