Parametric modeling of the heteroscedastic traffic speed variance from loop detector data

摘要

Traffic speed variance is defined as a measure of the dispersion of space mean speeds among drivers. Empirical speeda??density observations exhibit a structured traffic speed variance, which has been found to be associated to the roadway crash rate, the fatality rate, and travel time variability. The objective of this paper is to propose a generalized traffic speed variance function to describe this structured variance. The proposed speed variance function is a response of the speeda??density curve with two additional parameters. The estimation of the model parameters in the proposed traffic speed variance function can be carried out through an iterative nonlinear leasta??square algorithm (i.e., LevenbergMarquardt). A series of logistic speeda??density curve with varying parameters are used in the proposed traffic speed variance function with different levels of performance. The proposed traffic speed variance model can potentially help to unveil the underlying mechanism of empirical traffic phenomenon such as spontaneous congestion or capacity reduction. Copyright ?? 2013 John Wiley & Sons, Ltd.