Abstract: Cities around the world are facing problems caused by transportation, which are leading to efforts to create more sustainable urban transport systems. A good example of this is the increase in active mobility options like bicycles, e-scooters, and electric bikes, along with efforts to make cities more friendly for these types of transport. The idea of the 15-minute city, where people can reach all essential services by walking within 15 minutes, also shows how cities are trying to change the way people move around. However, active mobility options, such as walking and cycling, are still affected by bad weather. Walking and cycling, in particular, are sensitive to bad weather, especially in places with long winters and heavy rain. While we know that active mobility is important for creating sustainable cities, there is not much research on which of these modes can handle bad weather better or how different groups of people change their travel choices when the weather is bad. There is also little research on how people living in 15-minute city areas change their travel habits during bad weather. This paper aims to answer the question: How does weather affect the shift to sustainable urban transport? The study will find out what makes active mobility modes different from other types of transport, rank these modes based on how much they are affected by weather, and identify which groups of people are more likely to change their transport mode because of weather. The study will also look at how people living in 15-minute city areas change their travel behavior during bad weather. The analysis will use data from the 2022 National Travel Survey of Trondheim (Norway), weather data from the same year, and land use data. The travel survey gives detailed information about the people who responded and their travel habits, and the land use data will help define the areas where services are reachable by a 15-minute walk. We will use multinomial logit model to study how people choose their transport modes under different weather conditions, starting with simple models and gradually incorporating additional relevant variables. The expected results will include comparisons of different transport modes, like cars, public transport, cycling, and walking, under various weather conditions. The study will also identify what makes active mobility modes unique and rank them based on how they perform in different weather. These results will help guide policymakers on how to support sustainable urban transport in different weather conditions.
Learning Objectives:
Attendees can expect to learn the following from this session:
Identify which active mobility modes are more resilient to adverse weather conditions
Recognize the role of demographic factors in influencing transportation mode shifts during different weather conditions
Gain insights into how people living in 15-minute city areas adapt their travel behaviors in response to weather and how this adaptation can inform future urban mobility strategies.
