Focus on a joint research project: ORESTE

ORESTE (2012-2017)

Optimal reroute strategies for traffic management

Principal Investigators: 

  • Dr. Paola Goatin, ACUMES team, Inria Sophia Antipolis Méditerranée
  • Prof. Alexandre Bayen, University of California Berkeley

Research objectives:

The problem of road traffic, and its effects on pollution, time-consumption and their social and economical consequences, require an accurate policy and planning of road networks. The recent advances in technology and Internet can provide low-cost and reliable solutions to the collection of traffic data. GPS-equipped mobile devices can contribute to reduce traffic and the amount of time spent on the road by providing more accurate sources of travel information. ORESTE tackles a problem that has become fundamental in congested areas: flow reroutes. It looks for optimal strategies for rerouting some of the highway traffic flow into the secondary network, to decongest the freeways without congesting the arterials. This requires the construction of adapted macroscopic models of road traffic on networks, which are based on partial differential equations and result in optimization problems that are extremely hard to solve in a continuous setting. Therefore, ORESTE approaches the problem from a discrete (numerical) standpoint, to provide constructive results (in a discrete setting), which can be implemented in practice.

Scientific achievements:

Contributions span: (1) A continuous junction model with on-ramp buffer, (2) Coordinated ramp-metering for road networks via adjoint-based optimization, and (3) Optimal dynamic traffic assignment with partial compliance for horizontal queuing networks.

Publications and Awards:

Selected publication:

M.L. Delle Monache, J. Reilly, S. Samaranayake, W. Krichene, P.Goatin and A. Bayen. A PDE-ODE model for a junction with ramp buffer, SIAM J. Appl. Math., 74(1) (2014), 22-39.

Follow up:

The team has been renewed for 3 years in 2015 and further extends the collaboration to Rutgers University (PI Prof. Benedetto Piccoli), with the aim to develop a unified macroscopic approach for traffic management by providing analytical and numerical tools for traffic monitoring, prediction and control, based on real-time sensing.

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