How can macroscopic models reveal self-organization in traffic flow?
Emiliano Cristiani, Benedetto Piccoli, Andrea Tosin

TL;DR
This paper introduces a multiscale modeling approach for traffic flow that captures microscopic granularity effects at a macroscopic level, revealing self-organization phenomena like oscillatory patterns at intersections.
Contribution
It adapts a measure-theoretic multiscale method to traffic networks, allowing simultaneous microscopic and macroscopic descriptions without classical network constraints.
Findings
Model captures self-organization effects such as oscillatory traffic patterns.
Method handles multi-dimensional junctions naturally.
Simulations show realistic traffic behaviors at intersections.
Abstract
In this paper we propose a new modeling technique for vehicular traffic flow, designed for capturing at a macroscopic level some effects, due to the microscopic granularity of the flow of cars, which would be lost with a purely continuous approach. The starting point is a multiscale method for pedestrian modeling, recently introduced in Cristiani et al., Multiscale Model. Simul., 2011, in which measure-theoretic tools are used to manage the microscopic and the macroscopic scales under a unique framework. In the resulting coupled model the two scales coexist and share information, in the sense that the same system is simultaneously described from both a discrete (microscopic) and a continuous (macroscopic) perspective. This way it is possible to perform numerical simulations in which the single trajectories and the average density of the moving agents affect each other. Such a method is…
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