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A finite difference approximation of the kinematic wave model of traffic flow

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  • Daganzo, Carlos F.

Abstract

This article shows that if the kinematic wave model of freeway traffic flow in its general form is approximated by a particular type of finite difference equation, the finite difference results converge to the kinematic wave solution despite the existence of shocks in the latter. This result, which applies to initial and boundary condition problems with and without discontinuous data, is shown not to hold for other commonly used finite difference schemes. In the proposed approximation, the flow between two neighboring lattice points is the minimum of the two values returned by: 1. (a) a "sending" function evaluated at the density prevailing at the upstream lattice point and2. (b) a "receiving" function evaluated at the downstream lattice point. The sending and receiving functions correspond to the increasing and decreasing branches of the freeway's flow-density curve. The article presents an asymptotic formula for the errors introduced by the proposed finite difference approximation and describes quantitatively the finite difference's shock-capturing behavior. Errors are shown to be approximately proportional to the mesh spacing with a coefficient of proportionality that depends on the wave speed, on its rate of change with density, and on the slope and curvature of the initial density profile. The asymptotic errors are smaller than those of Lax's first-order, centered difference method which is also convergent. More importantly though, the proposed procedure never yields negative flows, and this makes it attractive in practical engineering applications when the mesh cannot be made arbitrarily small.

Suggested Citation

  • Daganzo, Carlos F., 1995. "A finite difference approximation of the kinematic wave model of traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 29(4), pages 261-276, August.
  • Handle: RePEc:eee:transb:v:29:y:1995:i:4:p:261-276
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    References listed on IDEAS

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    1. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part III: Multi-destination flows," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 305-313, August.
    2. Michalopoulos, Panos G. & Beskos, Dimitrios E. & Yamauchi, Yasuji, 1984. "Multilane traffic flow dynamics: Some macroscopic considerations," Transportation Research Part B: Methodological, Elsevier, vol. 18(4-5), pages 377-395.
    3. Daganzo, Carlos F., 1995. "The cell transmission model, part II: Network traffic," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 79-93, April.
    4. Newell, G. F., 1989. "Comments on traffic dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 23(5), pages 386-389, October.
    5. N/A, 1989. "Comments," ILR Review, Cornell University, ILR School, vol. 43(1), pages 89-102, October.
    6. Daganzo, Carlos F., 1994. "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transportation Research Part B: Methodological, Elsevier, vol. 28(4), pages 269-287, August.
    7. Michalopoulos, Panos G. & Beskos, Dimitrios E. & Lin, Jaw-Kuan, 1984. "Analysis of interrupted traffic flow by finite difference methods," Transportation Research Part B: Methodological, Elsevier, vol. 18(4-5), pages 409-421.
    8. Newell, G. F., 1993. "A simplified theory of kinematic waves in highway traffic, part I: General theory," Transportation Research Part B: Methodological, Elsevier, vol. 27(4), pages 281-287, August.
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