Workshop "Road Traffic Flow: Analysis, Optimization and Control"
Oct 21 - Oct 22
Road Traffic Flow - Analysis, Optimization and Control
Transportation plays a pivotal role in a society's economic and social welfare. Overly congested road traffic networks account for several billions of euros in cost, in the Netherlands alone. Since congestion itself can have many different causes (e.g., too much traffic, accidents, and bad network design), it is an inherently interesting and important topic for multiple scientific research areas, ranging from social sciences to civil engineering, mathematics and physics. Each area focuses on their favorite topics and yields interesting and important insights that lead to effective measures to control traffic flows and optimize transportation network performance.
To encourage interaction and collaboration between road-traffic researchers, we are hosting an engaging two-day workshop entitled "Road Traffic Flow: Analysis, Optimization, and Control" at the workshop institute Eurandom at Eindhoven University of Technology on October 21st and 22nd. The main goal of this workshop is to stimulate the cross-disciplinary collaboration between scientific areas that focus on similar problems, like civil engineering and operations research, which can lead to a synergy that is beneficial for all road traffic research.
The presentations during the workshop will mostly be given by researchers from the Netherlands, ranging from PhD students to full professors, supplemented with keynote and tutorial presentations from internationally renowned scientists.
With more and more Covid-related restrictions in the Netherlands being eased or abandoned, we expect that the workshop can take place physically at Eurandom in October and that we can all meet one another in person. Therefore, we aim for such a fully on-campus event. In the case that governmental measures and/or measures from the TU/e that are in place by that time do not allow for such an event, the workshop format will either be changed to a hybrid or a fully online event. We will of course keep you up-to-date on those matters and relevant changes in the format.
|Marko Boon||TU Eindhoven|
|Sindo Núñez Quijea||University of Amsterdam|
|Jan-Kees van Ommeren||University of Twente|
|Jaap Storm||TU Eindhoven|
|Rik Timmerman||TU Eindhoven|
|Carolina Osorio||HEC Montreal|
|Eddie Wilson||University of Bristol|
|Peter Wagner||DLR (Deutsches Zentrum für Luft- und Raumfahrt)|
Invited speakers (confirmed)
|Simeon Calvert||Delft University of Technology|
|Saif Jabari||NYU Abu Dhabi|
|Rens Kamphuis||University of Amsterdam|
|Victor Knoop||Delft University of Technology|
|Nikki Levering||University of Amsterdam|
|Michel Mandjes||University of Amsterdam|
|Anna Oblakova||University of Twente|
|Maaike Snelder||Delft University of Technology|
|Erik Verhoef||Vrije Universiteit Amsterdam|
Thursday October 21 Friday October 22
|10.00 - 10.30||Welcome and Opening||09.00 - 09.45||Tutorial 2|
|10.30 - 11.15||Tutorial 1||09.45 - 10.15||Break|
|11.15 - 11.30||Break||10.15 - 10.45||Talk 6|
|11.30 - 12.00||Talk 1||10.45 - 11.15||Talk 7|
|12.00 - 12.30||Talk 2||11.15 - 11.45||Break|
|12.30 - 13.30||Lunch||11.45 - 12.15||Talk 8|
|13.30 - 14.00||Talk 3||12.15 - 13.15||Lunch|
|14.00 - 14.30||Talk 4||13.15 - 13.45||Talk 9|
|14.30 - 15.00||Break||13.45 - 14.15||Talk 10|
|15.00 - 15.45||Keynote 1||14.15 - 14.45||Break|
|15.45 - 16.15||Break||14.45 - 15.30||Keynote 2|
|16.15 - 16.45||Talk 5||15.30 -||Farewell & Drinks|
|18.00 -||Conference Dinner|
Contemporary Techniques for Urban Transport Operations Management
I will discuss two techniques that solve real-time transport operations in urban network settings. The first part of my talk will present a modeling technique used to translate any (ridge) regression problem into a matrix completion problem that can be solved efficiently using block-coordinate descent techniques. We apply this to forecasting high-resolution traffic states from point sensors in signalized networks. The approach is particularly suitable for large datasets. I will discuss some of the modeling advantages and guarantees of performance in the form of generalization errors. The second part of my talk will focus on lightweight algorithmic approaches for managing two types of systems: (1) urban network traffic signal control and (2) carsharing operations. I will show how to attack both types of problems using Lyapunov optimization techniques, which ensure stability at the network level while employing simple localized solution approaches.
A diffusion-based analysis of a multi-class road traffic network
In this talk I'll discuss a stochastic model that describes the evolution of vehicle densities in a road network. It is consistent with the class of (deterministic) kinematic wave models, which describe traffic flows on the basis of conservation laws that incorporate the macroscopic fundamental diagram (a functional relationship between vehicle density and flow). The setup used is capable of handling multiple types of vehicle densities, with general macroscopic fundamental diagrams, on a network with arbitrary topology.
Interpreting our system as a spatial population process, it turns out that, under a natural scaling, fluid and diffusion limits can be derived. This means that the vehicle density process can be approximated with a suitable Gaussian process, which yield accurate normal approximations to the joint (in the spatial and temporal sense) vehicle density process. The corresponding means and variances allowing efficient computation by solving specific differential equations, we provide insight into the underlying computational complexity.
Time permitting, I also show how the limit results give rise to an approximation to the vehicles' travel-time distribution between any given origin and destination pair.
(joint work with Jaap Storm)
High-dimensional traffic control through Bayesian optimization
In this talk, we consider high-dimensional traffic signal control problems that arise in congested metropolitan areas. We focus on the use of high-resolution urban mobility stochastic simulators and formulate the control problems as high-dimensional continuous simulation-based optimization (SO) problems. We discuss the opportunities and challenges of designing SO algorithms for these problems. An important component in high-dimensional problems is the exploration-exploitation tradeoff. We discuss work that has focused on improving the exploitation capabilities of SO algorithms. We then present novel exploration techniques suitable for high-dimensional spaces. We consider a Bayesian optimization setting, and propose the use of a simple analytical traffic model to specify the covariance function of a Gaussian process. We show how this enables the Bayesian optimization method to more efficiently sample in high-dimensional spaces. We present validation experiments on synthetic low-dimensional problems. We then apply the method to a high-dimensional traffic control problem for Midtown Manhattan, in New York City.
Registration is free, but compulsory. Please follow this link