An extended macro model accounting for acceleration changes with memory and numerical tests

Rongjun Cheng, Hongxia Ge, Fengxin Sun and Jufeng Wang

Physica A: Statistical Mechanics and its Applications, 2018, vol. 506, issue C, 270-283

Abstract: Considering effect of acceleration changes with memory, an improved continuum model of traffic flow is proposed in this paper. By applying the linear stability theory, we derived the new model’s linear stability condition. Through nonlinear analysis, the KdV–Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the extended traffic flow model, which explores how acceleration changes with memory affected each car’s velocity, density and fuel consumption and exhaust emissions. Numerical results demonstrate that acceleration changes with memory have significant negative effect on dynamic characteristic of traffic flow. Furthermore, research results verify that the effect of acceleration changes with memory will deteriorate the stability of traffic flow and increase cars’ total fuel consumptions and emissions during the whole evolution of small perturbation.

Keywords: Traffic flow; Continuum model; Acceleration changes with memory; Fuel consumption; Emissions (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:506:y:2018:i:c:p:270-283

DOI: 10.1016/j.physa.2018.04.060

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