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@telecom-sudparis.eu
Prof. D. Feillet, feillet@emse.fr
Assoc. Prof. V. Gauthier, vincent.gauthier@telecom-sudparis.eu
*References*
[Alo17] Alonso-mora, J., Samaranayake, S., Wallar, A., Frazzoli, E.,
& 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., & 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., & 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., & Riano, G. (2015).
Systems Hybrid Algorithm for Route Design on Bus Rapid Transit Systems.
Transportation Science.
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