A geometric Brownian motion car-following model
towards a better understanding of capacity drop
K. Yuan (TU Delft - Transport and Planning, Georgia Institute of Technology)
Jorge Lavala (Georgia Institute of Technology)
VL Knoop (TU Delft - Transport and Planning)
Rui Jiang (Beijing Jiaotong University)
S. P. Hoogendoorn (TU Delft - Transport and Planning)
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Abstract
Traffic flow downstream of the congestion is generally lower than the pre-queue capacity. This phenomenon is called the capacity drop. Recent empirical observations show a positive relationship between the speed in congestion and the queue discharge rate. Literature indicates that variations in driver behaviors can account for the capacity drop. However, to the best of authors' knowledge, there is no solid understanding of what and how this variation in driver behaviors lead to the capacity drop, especially without lane changing. Hence, this paper fills this gap. We incorporate the empirically observed desired acceleration stochasticity into a car-following model. The extended parsimonious car-following model shows different capacity drop magnitudes in different traffic situations, consistent with empirical observations. All results indicate that the stochasticity of desired accelerations is a significant reason for the capacity drop. The new insights can be used to develop and test new measures in traffic control.