Shared spaces for active mobility prioritize the safety and comfort of vulnerable road users by segregating them from motorized vehicles. However, the diverse speed regimes of pedestrians and cyclists can lead to encounters that may affect their comfort. In addition, the very perception of comfort may vary across individuals depending on their demographics, and therefore the determinants of comfort and their effects may not be fixed across all individuals. Despite these complexities, there is limited research in understanding the heterogeneous interactions between cyclists and other road users in shared spaces. To bridge this gap, we conducted an intercept survey complemented by an experimental section involving 594 cyclists in Sweden. This study focuses on gaining insights into cyclists' experiences, particularly their comfort levels during 'passing' and 'meeting' events with other road users in shared spaces. We then used the collected data to develop a random effect latent class ordered probit model to scrutinize the determinants of cycling comfort in passing and meeting scenarios. The latent class specification is employed to account for unobserved heterogeneity in the data. Findings reveal that female cyclists generally perceive less comfort compared to their male counterparts in both scenarios. Passing events have a more negative impact on older adults, leading to less comfort compared to younger cyclists. We also found that previous cycling experience increases comfort in shared facilities, particularly for older adults. These results highlight the intricate nature of perceived comfort in interactions, particularly concerning demographic characteristics, contributing to the promotion of user diversity in shared spaces.@en

Shared spaces for active mobility prioritize the safety and comfort of vulnerable road users by segregating them from motorized vehicles. However, the diverse speed regimes of pedestrians and cyclists can lead to encounters that may affect their comfort. In addition, the very perception of comfort may vary across individuals depending on their demographics, and therefore the determinants of comfort and their effects may not be fixed across all individuals. Despite these complexities, there is limited research in understanding the heterogeneous interactions between cyclists and other road users in shared spaces. To bridge this gap, we conducted an intercept survey complemented by an experimental section involving 594 cyclists in Sweden. This study focuses on gaining insights into cyclists' experiences, particularly their comfort levels during 'passing' and 'meeting' events with other road users in shared spaces. We then used the collected data to develop a random effect latent class ordered probit model to scrutinize the determinants of cycling comfort in passing and meeting scenarios. The latent class specification is employed to account for unobserved heterogeneity in the data. Findings reveal that female cyclists generally perceive less comfort compared to their male counterparts in both scenarios. Passing events have a more negative impact on older adults, leading to less comfort compared to younger cyclists. We also found that previous cycling experience increases comfort in shared facilities, particularly for older adults. These results highlight the intricate nature of perceived comfort in interactions, particularly concerning demographic characteristics, contributing to the promotion of user diversity in shared spaces.@en

Although the enforcement of seatbelt use is considered to be an effective strategy in reducing road injuries and fatalities, lack of seatbelt use still accounts for a substantial proportion of fatal crashes in Tennessee, United States. This problem has raised the need to better understand factors influencing seatbelt use. These factors may arise from spatial/temporal characteristics of a driving location, type of vehicle, demographic and socioeconomic attributes of the vehicle occupants, driver behaviours, attitudes, and social norms. However, the above factors may not have the same effects on seatbelt use across different individuals. In addition, the behavioural factors are usually difficult to measure and may not always be readily available. Meanwhile, residential locations of vehicle occupants have been shown to be associated with their behavioural patterns and thus may serve as a proxy for behavioural factors. However, the suitability of geographic and residential locations of vehicle occupants to understand the seatbelt use behaviour is not known to date. This study aims to fill the above gaps by incorporating the residential location characteristics of vehicle occupants in addition to their demographics and crash characteristics into their seatbelt use while accounting for the varying effects of these factors on individual seatbelt use choices. To achieve this goal, empirical data are collected for vehicular crashes in Tennessee, United States, and the home addresses of vehicle occupants at the time of the crash are geocoded and linked with the census tract information. The resulting data is then used as explanatory variables in a latent class binary logit model to investigate the determinants of vehicle occupants’ seatbelt use at the time of the crash. The latent class specification is employed to capture the unobserved heterogeneity in data. Results show that Tennessean drivers belong to two general categories—conformist and eccentric—with gender, vehicle type, and income per capita determining the likelihood of these categories. Overall, male drivers, younger drivers, and drivers who have consumed drugs are less likely to wear a seatbelt, whereas drivers who come from areas with higher population density, travel time, and income per capita are more likely to wear a seatbelt. In addition, driving during the day and in rainy weather are associated with an increased likelihood of seatbelt use. The findings of this study will help developing effective policies to increase seatbelt use rate and improve safety.

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