摘要：AbstractMeteorological conditions have considerable impact on freeway free-flow characteristics, several empirical studies have stated that precipitation, snow, and visibility loss may cause reductions in speed and capacity. However, relative few have considered the potential time-lagged effect of weather conditions on free-flow, while more attention should also now be paid to the trend, cycle, and irregular fluctuations inherent in temporally aggregated observed data. Therefore, a detailed investigation in this paper was carried out to quantify the impact of multiple meteorological factors on key traffic stream parameters, including free-flow speed and volume. The study was based on recent archived data from sensor devices, such as inductive loop detectors and weather sensors, located on provincial highways of Jilin Province in China. In order to analyze relativity between meteorological factors and traffic parameters from dynamic point of view, Granger causality theory was adopted to examine the existence of a systemic causal relationship. Moreover, impulse response function based on the vector autoregression model was proposed to provide insight into the cross-effects of the traffic parameters and their responses to weather conditions. Some interesting results can be concluded from our study, including the description of the dynamic interplay among variables, as well as the possible variations in hourly freeway traffic activity with respect of weather trends. It is hoped that this study will shed light on a fully understanding of how weather factors affect freeway traffic conditions.
关键词：Meteorological factors;Freeway free-flow;Time series;Granger causality test;Vector autoregression model;Impulse response function
