[Job-offers-cs] Post-doc position at Telecom SudParis and Ecole des Mines de Saint-Etienne (France): combination of on-demand and fixed-schedule services in public-transit systems

Thu Nov 7 21:12:11 EET 2019

-------- Forwarded Message --------
Subject: [DMANET] Post-doc position at Telecom SudParis and Ecole des 
Mines de Saint-Etienne (France): combination of on-demand and 
fixed-schedule services in public-transit systems
Date: Fri, 18 Oct 2019 15:12:11 +0200
From: FEILLET Dominique <feillet at emse.fr>
To: dmanet at zpr.uni-koeln.de

Hello,

We are proposing a 12-months post-doc position on ride-sharing systems, 
and, more specifically, about the combination of on-demand and 
fixed-schedule services.

More details can be found below.

Best regards,

Dominique Feillet

*------------------------------------------
*

*Postdoc position:* Ride-sharing for transit

*Keywords.* Intelligent Transportation Systems, Routing Algorithms, 
Multimodal Transportation; Smart Cities; Digital Society

*Institutions.* The Postdoctoral Researcher will be hired for 12 months 
at Telecom SudParis and/or Ecole des Mines de Saint-Etienne. Telecom 
SudParis is member of Institut Polytechnique de Paris. Both schools are 
members of Institut Mines-Telecom. The Postdoctoral Researcher will work 
with Prof. Dominique Feillet, Assoc. Prof. Andrea Araldo, Assoc. Prof. 
Vincent Gauthier.

*Context and motivation**
*

The advent of Information Technology is disrupting the transportation 
ecosystem. One of the most visible revolutions is the success of ride 
sharing platforms, as Uber and Lyft, which provide on-demand service at 
low cost, thanks to (i) immediate communication between riders and 
drivers through easy-to-use smartphone apps and (ii) intelligent 
algorithms to optimize vehicle routing. On the other hand, the type of 
service offered by public transit has not evolved at the same pace over 
the last years. The contrast between “user-centric” on-demand services 
offered by private companies and “fixed-line-centric” public transit 
risks to penalize the latter, as users often prefer the former [Sad17]. 
However, on-demand services are not the answer to all mobility problems. 
Araldo, one of the holders of this project, has shown [Bus18] that they 
are not suitable to serve dense demand (in terms of trip requests per 
km2 per second). On the other hand, fixed schedule transit is not 
efficient when demand is sparse [Qua09] as, in order to catch a 
sufficient number of passengers per vehicle, which justifies the cost of 
operating it, the frequency of the corresponding line and the density of 
stations must be low enough, which would result in poor quality of 
service for passengers. This problem is evident in suburbs and is one of 
the reasons for geographical inequity in modern society [Cag17]. 
Therefore, a combination of on-demand and fixed-schedule services is 
needed in order to guarantee high throughput for dense demand and, at 
the same time, the flexibility needed to guarantee quality of service in 
sparse-demand areas. For these reasons, in recent years public 
authorities have launched pilots to experiment with different ways to 
complement their offers with on-demand services, by subsidizing 
ride-sharing companies [Laz17] or proposing flexible route buses. In 
current literature and in the practice the design of transit schedules 
and the design of routing algorithms for on-demand transportation have 
been treated as separate problems. The novelty of this project is to 
explore instead the inter-relation between the two design problems. In 
particular, we study how to adapt ride-sharing routes to the schedules 
of fixed transit in order to improve travelers’ quality of service while 
limiting the operational cost for the operator.

*Scientific goal and activity*

The project aims to integrate on-demand services into public transit, by 
making vehicle routing algorithms aware of the transit schedules. By 
doing so, users can travel efficient multi-modal routes that include 
both on-demand transportation and mass transit. The broader goal is to 
offer a transportation service able to adapt to travelers’ demand and to 
combine the advantages of fixed-schedule transit and on-demand services, 
thus improving human mobility. The postdoctoral researcher will devise 
simplified models of public transit, e.g., [Dag15] and [Wal15]. He/She 
will implement ride sharing employing state of the art algorithms 
[Alo17] to match travelers to vehicles and create vehicle routes. He/She 
will devise methods to create efficient multi-modal routes for users. 
He/She will devise methods to modify vehicle routes in order to improve 
the quality of multi-modal routes. The research will be performed in 
collaboration with a company in the field of transportation, which will 
provide data and use cases.

*Dates*

The Postdoctorate covers a period of 12 months. The starting date is 
flexible, but not later than Spring 2020.

*Candidate requirements*

The candidate must hold a PhD in Computer Science, Transportation, 
Systems, Applied Mathematics or any other domain related to the 
position. Required skills are experience in optimization, algorithm 
design and testing, simulation. He/She must be proficient with at least 
one programming language (C++ is a plus, but other languages are fine). 
To candidate, please be sure to include the following elements: (i) CV, 
(ii) complete list of publications (separating journals and 
conferences), (ii) 5 “best” publications that best fit this position, 
(iv) motivation letter, (v) research statement related to this position, 
(vi) references or recommendation letters, (vii) all the marks of higher 
education, (viii) the text of the deliberation of the PhD commission, 
(ix) the reviews of the PhD thesis from the PhD reviewers.

*Contact*

Assoc. Prof. A. Araldo, andrea.araldo at telecom-sudparis.eu
Prof. D. Feillet, feillet at emse.fr
Assoc. Prof. V. Gauthier, vincent.gauthier at telecom-sudparis.eu

*References*

[Alo17] Alonso-mora, J., Samaranayake, S., Wallar, A., Frazzoli, E., 
&amp; Rus, D. (2017). On-demand high-capacity ride-sharing via dynamic 
trip-vehicle assignment. Proceedings of the National Academy of
Sciences of the United States of America
[Bas18] Basu, Araldo et Al. (2018) Implementation and Policy 
Applications of AMoD in multi-modal activity driven agent-based urban 
simulator SimMobility, in Trans. Res. Records
[Cag17] Caggiani et Al. (2017) Facing Equity in Transportation Network 
Design Problem: a Flexible constraints based model.
[Dag15] Chen, H., Gu, W., Cassidy, M., &amp; Daganzo, C. (2015). Optimal 
Transit Service atop Ring-radial and Grid Street Networks: A Continuum 
Approximation Design Method and Comparisons. Transportation Research 
Part B: Methodological
[Qua09] Quadrifoglio et Al. (2009) A methodology to derive the critical 
demand density for designing and operating feeder transit services. 
Transportation Research Part B: Methodological
[Sad17] Sadowsky et Al. (2017) The Impact of Ride-Hailing Services on 
Public Transportation Use: A Discontinuity Regression Analysis. 
Economics Department, Bowdoin College
[Sha16] Shahriari, B., Swersky, K., Wang, Z., Adams, R. P., &amp; De 
Freitas, N. (2016). Taking the Human Out of the Loop : A Review of 
Bayesian Optimization. Proceedings of the IEEE, 104(1), 1–24.
[Wal15] Walteros, J. L., Medaglia, A. L., &amp; Riano, G. (2015). 
Systems Hybrid Algorithm for Route Design on Bus Rapid Transit Systems. 
Transportation Science.

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