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Acceleration Profile Models for Vehicles in Road Traffic

Author

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  • R. Akcelik

    (Australian Road Research Board, Vermont South, Victoria, Australia)

  • D. C. Biggs

    (Australian Road Research Board, Vermont South, Victoria, Australia)

Abstract

Three new models of acceleration profile (a two-term sinusoidal, a three-term sinusoidal, and a polynomial model) are described. These models yield the S-shaped speed-time trace indicated by data from driving in real-life traffic conditions, satisfy the realistic conditions of zero jerk (except the two-term sinusoidal model) and zero acceleration at the start and end of the acceleration, and allow for the position and the value of the maximum acceleration to vary for a given average acceleration rate. A comparative evaluation of these three models and the previously known constant and linear-decreasing acceleration models is reported. The evaluation criteria are distance traveled and fuel consumed during acceleration. The performances of the five models are compared under three sets of conditions: acceleration time and distance known, time known but distance unknown, and both time and distance unknown. The comparisons are made separately for central business district (CBD), other urban and nonurban traffic conditions. The polynomial model has been found to be the best overall for predicting acceleration distance and fuel consumption. Similar results have been found for deceleration profiles. Dependence of fuel consumption on acceleration rate and profile is also discussed. Suggestions for further work using the results of this report are included.

Suggested Citation

  • R. Akcelik & D. C. Biggs, 1987. "Acceleration Profile Models for Vehicles in Road Traffic," Transportation Science, INFORMS, vol. 21(1), pages 36-54, February.
  • Handle: RePEc:inm:ortrsc:v:21:y:1987:i:1:p:36-54
    DOI: 10.1287/trsc.21.1.36
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    Cited by:

    1. Junhyung Lee, 2022. "Acceleration and Deceleration Rates in Interrupted Flow Based on Empirical Digital Tachograph Data," Sustainability, MDPI, vol. 14(18), pages 1-16, September.

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