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A Godunov type scheme for a class of LWR traffic flow models with non-local flux

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arxiv 1802.07484 v2 pith:7IRX4EFX submitted 2018-02-21 math.NA cs.NA

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keywords schemetypeclassgodunovnon-localconservationflowflux
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abstract

We present a Godunov type numerical scheme for a class of scalar conservation laws with non-local flux arising for example in traffic flow models. The proposed scheme delivers more accurate solutions than the widely used Lax-Friedrichs type scheme. In contrast to other approaches, we consider a non-local mean velocity instead of a mean density and provide $L^\infty$ and bounded variation estimates for the sequence of approximate solutions. Together with a discrete entropy inequality, we also show the well-posedness of the considered class of scalar conservation laws. The better accuracy of the Godunov type scheme in comparison to Lax-Friedrichs is proved by a variety of numerical examples.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting

    cs.LG 2025-08 conditional novelty 5.0 of 10

    DETNO couples a transformer neural operator with a diffusion refiner, achieving lower rollout error and better high-frequency fidelity on synthetic LWR traffic forecasts than ONTraffic and GNOT.

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