Return to Assoc. Team


The Associated Team ORESTE (2012-2017) with UC Berkeley is now closed.

The collaboration is now carried on as an Inria International Partner:


Optimal REroute Strategies for Traffic managEment (ORESTE)

Presentation of the partners

Permanent researchers:

  • Paola GOATIN is Senior Researcher at Inria Sophia Antipolis – Méditerranée (SAM). She is an internationally recognized mathematician with background in functional analysis (partial differential equations and control theory) with focus on macroscopic traffic modeling. Expertise: hyperbolic systems of conservation laws, finite volume schemes, PDE constrained optimization, traffic flow modeling.
  • Alexandre M. BAYEN is Chancellor Associate Professor in the Department of Civil and Environmental Engineering and the Electrical Engineering and Computer Science Department, and Director of the Institute for Transportation Studies at UC Berkeley. Expertise: mobile internet applications (location based services), participatory sensing, inverse modeling and data assimilation, control, estimation and optimization of distributed parameter systems.


Non-permanent members:

  • Alexander KEIMER is currently post-doc fellow at UC Berkeley, under the supervision of Prof. A. Bayen, and former member of the Associated Team ORESTE. He works on non-local conservation laws on networks and applications to traffic assignment.
  • Nicolas LAURENT_BROUTY was PhD student at Inria Sophia Antipolis (2016-2019) under the direction of Dr. P. Goatin, and former member of the AT ORESTE. He worked on macroscopic traffic flow models for pollution estimation and control.
  • Shuxia TANG held an Inria@SiliconValley post-doctoral fellowship at Inria Sophia Antipolis (2018-2019) under the joint supervision of Dr. P. Goatin and Prof. A. Bayen. She worked on real time decision making in traffic management.


Work program

The rapidly changing transportation ecosystem opens new challenges in traffic modeling and optimization approaches. We will focus in particular on the two following aspects:

Route choice apps impact. The vast use of personal route choice systems through phone applications or other devices is modifying the traditional flow of networks, requiring new models for accounting of the guidance impact [R1]. Indeed, routing apps have changed traffic patterns in the US and Europe, leading to new congestion patterns where previously no traffic was observed. Over the last decade, GPS enabled smart phones and connected personal navigation devices have disrupted the mobility landscape. Initially, the availability of traffic information led to better guidance of a small portion of motorists in the system. But as the majority of the driving public started to use apps, the systematic broadcasting of “selfish” best routes led to the worsening of traffic in numerous places, ultimately leading to the first lawsuit against one specific company in particular (Waze) accused to be the cause of these problems. This is just the beginning of an evolution, which, if not controlled and regulated, will progressively asphyxiate urban landscapes (already nearly hundreds of occurrences of this phenomenon are noticed by the popular media, which indicates the presence of probably thousands of such issues in the US alone). Traffic managers are typically not equipped to fix these problems, and typically do not fund this research, as in order to be able to regulate and fix the problem, fundamental science needs to be advanced, modeling and game theory in particular, so remediation can happen (for which the traffic managers are equipped). In this project, we will mainly focus on the development and study of new macroscopic dynamical models to describe the aforementioned phenomena [R2, R3], and we will explore control strategies to mitigate their impact.

Autonomous vehicles. Besides, the foreseen deployment of connected and autonomous vehicles (CAVs) opens new perspectives both in traffic modeling and control. Indeed, CAVs are expected to modify the classical macroscopic traffic dynamics due to their peculiar motion laws, which are more uniform than human drivers’ and follow different rules. Besides, due to their extended information on neighboring traffic conditions, the resulting dynamics would have a non-local character, justifying the use of rapidly developing non-local models [R4, R5]. In any case, the different behavior of autonomous vehicles requires the design of new multi-class models capable of accounting for different vehicle classes characteristics and mutual interactions [R6]. Moreover, CAVs could be used as endogenous variable speed limiters, thus providing new action points to control traffic flow. Preliminary results show that the presence of few controlled vehicles can positively affect traffic conditions [R7]. In this setting, the interaction of AVs with the surrounding traffic can be described by strongly coupled PDE-ODE systems, which have been largely studied by the ACUMES team [R8, R9]. Yet, the study of CAVs impact in realistic situations requires further research, in particular towards model validation, for which the Berkeley team will provide the necessary data.



[R1] A. Keimer, N. Laurent‐Brouty, F. Farokhi, H. Signargout, V. Cvetkovic, A. Bayen, K. H. Johansson. Integration of information patterns in the modeling and design of mobility management services, Proceedings of the IEEE, vol. 106, no. 4, pp. 554-576, April 2018.

[R2] A. Keimer, N. Laurent-Brouty, P. Goatin, A. Bayen. A macroscopic traffic flow model with finite buffers on networks: Well-posedness by means of Hamilton-Jacobi equations, Comm. Math. Sci., to appear.

[R3] A. Festa and P. Goatin, Modeling the impact of on-line navigation devices in traffic flows, 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France (2019), 323-328.

[R4] S. Blandin, P. Goatin. Well-posedness of a conservation law with non-local flux arising in traffic flow modeling, Numer. Math.,132(2) (2016), 217-241.

[R5] F.A. Chiarello, P. Goatin. Global entropy weak solutions for general non-local traffic flow models with anisotropic kernel, ESAIM: M2AN, 52 (2018), 163-180.

[R6] F.A. Chiarello and P. Goatin, Non-local multi-class traffic flow models, Netw. Heterog. Media, 14(2) (2019), 371-387.

[R7] G. Piacentini, P. Goatin, A. Ferrara, Traffic control via moving bottleneck of coordinated vehicles,IFAC PapersOnLine, 51(9) (2018), 13-18. Proceedings of the 15th IFAC Symposium on Control in Transportation Systems.

[R8] M.L. Delle Monache, P. Goatin. Scalar conservation laws with moving constraints arising in traffic flow modeling: an existence result, J. Differential Equations, 257 (2014), 4015-4029.

[R9] M.L. Delle Monache, P. Goatin. Stability estimates for scalar conservation laws with moving flux constraints, Netw. Heterog. Media, 12(2) (2017), 245-258.