The influence of weather characteristics variability on individual’s travel mode choice in different seasons and regions in Sweden

• Main Authors: Liu, Chengxi, Susilo, Yusak O., Karlström, Anders
• Format: Article in Journal/Newspaper
• Language: unknown
• Subjects: Northern Sweden
• Online Access: http://www.sciencedirect.com/science/article/pii/S0967070X15000037

This paper investigates the influence of weather on the Swedish people’s mode choice decision in different seasons and regions using a long term series of the Swedish National Transport Survey datasets (NTS) and weather data from the Swedish Meteorological and Hydrological Institute (SMHI). The weather data includes mean of daily temperature, amount of rain precipitation and road surface condition. The daily mean temperature is normalised based on each region and season and classified into five categories as ‘very cold’, ‘cold’, ‘normal’, ‘warm’, and ‘very warm’. This normalisation approach enables us to investigate the impact of individual’s heterogeneity in perceiving regional and seasonal variability of temperature. The impacts of these weather indicators’ variability on individual’s mode choice is investigated with multinomial logit models. The results show that the impacts of weather differ in different seasons and different regions. Pedestrians’ perception of variation of temperature differs between those in the northern Sweden and those in the central and southern Sweden. Such perception also differs in summer and in spring and autumn. Similarly, northern Sweden cyclists are more aware of temperature variation than cyclists in the central and southern Sweden in spring and autumn when temperature changes significantly. The influence of temperature variation on motorised modes also varies among seasons and regions. However, the trend is less straightforward than that on non-motorised modes. The findings highlight the importance to incorporate individual and regional unique anticipation and adaptations behaviours within our policy design and infrastructure management. Weather changes; Regional and seasonal variability; Travel mode choice; Marginal effects;