The existing literature has confirmed that extreme weather such as wind, rain, and snow have a negative impact on cross-sectional traffic flow. However, travel activities with different destination regions, travel distances and vehicle types may have different responses to severe weather. We employ the multilevel mixed-effects negative binomial (MENB) model to explore the interaction effect of severe weather and non-weather factors on intercity origin-destination (OD) demand, based on the data from freeway toll stations in Shandong Province from March 2011 to February 2012. The MENB model is superior to the SNB model in that the former has both smaller AIC (456,645.4 < 4,586,877.2) and BIC (456,963.4 < 458,975.8) values and log-likelihood ratio tests. The results indicate that weather impact on freeway travel to the same metropolitan area is homogeneous, and the impact in different metropolitan areas is heterogeneous. Besides, there is an interaction effect between severe weather (strong wind, fog, heavy rain, snow) and travel distance on freeway OD volume. With increasing travel distance, the impact of both strong wind and heavy rain decreases gradually, while the impact of both fog and snow increases. In addition, heat (0.0351 > 0.0201), strong wind (0.0930 > 0.0454), and heavy rain (0.1245 > 0.1044) have a greater impact on passenger car volume than on truck volume, while fog (0.4340 < 0.4802) and snow (0.4383 < 0.4884) have a less significant impact on passenger car volume. The findings of this study provide some deep insights into the relationship between severe weather factors and intercity travel demand, which suggests that different strategies of travel demand management should be adopted for different travel distances and different vehicle types under various weather conditions.
Keywords: Freeway origin-destination volume; Multilevel mixed-effects negative binomial model; Severe weather; Travel distance; Vehicle type.
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