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A mathematical model for moving bottlenecks in road traffic

Serious traffic gridlocks, like the jam on Beijing’s national expressway a few months ago which brought vehicles to a halt for days, are a real-world issue needing attention. In a paper published this month in the SIAM Journal on Mathematical Analysis, authors Corrado Lattanzio, Amelio Maurizi and Benedetto Piccoli propose a mathematical model of vehicular traffic based on the study of a moving bottleneck caused by a slow-moving vehicle within the flow of cars.

The effect of moving bottlenecks on flow of traffic is an important factor in evaluating travel times and traveling paths for commuters.

Many different mathematical models have been proposed to study traffic, including models that use second-order equations for mass and momentum, multipopulation models that factor in the varying characteristics of different kinds of vehicles, and dynamic models that consider traffic flows.

Most of the models so far proposed, however, solve the problem of a single vehicle independently of the entire traffic flow, and so are not completely coupled. An example is a PDE-ODE model that used a partial differential equation to model the flow of traffic while using an ordinary differential equation to determine the position of a single vehicle. Since both could be solved independently, the system did not take into account the influence of the single car on the entire traffic flow.

The paper by Lattanzio et al. provides a fully coupled, multi-scale model in which the microscopic position of a single car is taken together with the macroscopic car density on the road. In this micro-macro model, the dynamics of a moving bottleneck caused by a slow-moving vehicle on a street are used to study the effects of disruptions on the flow of traffic.

Mathematically, the problem is solved using the fractional step method. In successive time steps, a PDE is first solved for the density of traffic and then the ODE is solved for the position of the slow-moving vehicle.

By solving the bottleneck problem in a coupled fashion, better transportation designs can be made in anticipation of such inevitable traffic congestion.


  • Corrado Lattanzio, Amelio Maurizi, and Benedetto Piccoli (2011) Moving Bottlenecks in Car Traffic Flow: A PDE-ODE Coupled Model. SIAM Journal on Mathematical Analysis, 43, pp 50-67 doi: 10.1137/090767224



Toronto installed a similar computerized system with 600+ cameras in 1993 and it accelerated the traffic flow in the dedicated area by about 17%. With recent improvements it may produce up to 20+%.

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