01626039

Component

https://doi.org/10.3141/2647-11

Despite the wide use of Robertson’s platoon dispersion model, few studies have calibrated this model under different traffic conditions at signalized intersections. This study calibrated the platoon dispersion model on the basis of field data collected from Beijing; the impact of the percentage of buses was considered in the calibration. First, a video was made of the platoon dispersion at an intersection. The link travel time of the vehicles in the platoon was extracted from the video. Then, the parameters of the platoon dispersion model were estimated with the average and standard deviations of the fleet link travel times. It was found that the derived parameters varied, with the observed percentage of buses ranging from 0% to 6% or 15% to 22%. This factor showed the impact of the percentage of buses on platoon dispersion under specific conditions. Regression models were developed to reflect such an impact. To evaluate the effectiveness of the calibrated platoon dispersion model, the downstream flow profiles derived from the calibrated model were compared with the field-observed downstream flow profiles within the dispersion process. Finally, the influence of the time step on the calibrated platoon dispersion model was analyzed. The results show that the calibrated model has high accuracy. The calibrated platoon dispersion model can be used to represent the process of platoon dispersion at signalized intersections where the impact is affected by the percentage of buses. It can contribute to signal timing optimization of the intersections.

01624542

17-02358

English

pp 93–99

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309442121

Digital/other

Figures (7) ; References (12)

Calibration; Mathematical models; Optimization; Signalized intersections; Traffic platooning; Traffic signal control systems; Transit buses; Validation; Vehicle mix

Traffic dispersion

Beijing (China)

Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation

PRP, TRIS, TRB, ATRI

Dec 8 2016 10:52AM

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