Direct Usage of Occupancy Data for Multiregime Speed-Flow Rate Models

Aksoy, Göker; Öğüt, Kemal Selçuk

doi:10.1061/jtepbs.0000773

Cited by 1 publication

(1 citation statement)

References 15 publications

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“…When the traffic flow is at a high level, vehicle delay and queue length are maintained at a high level and average speed is maintained at a low level [29][30][31][32]. Observational data demonstrates that when the road is congested, the relationship between speed and traffic flow is nonlinear and the speed tends to a fluctuating value [33]. During the observation and simulation of the school road, it is found that when the TF is small, the road is smooth and the evaluation indicators change little.…”

Section: Resultsmentioning

confidence: 99%

Simulation analysis of school road traffic characteristics

Liu,

Deng,

et al. 2024

DYNA

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This study aims to identify key factors and sensitive intervals affect the school road traffic characteristics. We collect traffic data from the parking area and the school road (400-700 meters). The simulation is calibrated to ensure the error of outputs are within 1.5%. A sensitivity analysis method is proposed, it makes the multifactor comparable. The sensitivity factors of vehicle delay, queue length, and average speed are 1.44, 2.03, and 0.28 in school road, and the bottleneck road are 3.07, 4.44, and 0.65. The traffic indicators change more concentrated in bottleneck road but greater in school road. 6 scenarios are created to analyze school road traffic characteristics. Traffic flow (TF), number of parking spaces (NPS), and stopping time (ST) are selected as variables. Scenarios 1-3 are univariate, and scenarios 4-6 are bivariate. TF is the key factor with a sensitivity interval of [1300,1700].

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