Redefining activity types: Who participates in which leisure activity?

This paper analyzes the activity choices of individuals and the links between socio-demographics, daily schedules and activity attributes using a new activity choice framework. Activities are first clustered into groups based on their salient attributes, such as duration, frequency, flexibility, planning times, and number of involved persons, rather than their functional types (work, leisure and household obligations), using a K-means cluster technique. This led to the creation of several new activity groups such as “long, temporally fixed, personally flexible activities”, “short and flexible activities”. These activity groups form the choice set for the mixed logit activity choice modeling structure developed for the leisure activities in the second part of the paper. The model results reveal the significant relationships between socio-demographics, temporal characteristics, and characteristics of the schedules on leisure activity choice. The results demonstrate how changing demographics and other activities in individuals’ schedules may affect the nature of the leisure activities and present the substitution and complimentary effects that these new activity groups have on one another.     

Severity of injury resulting from pedestrian–vehicle crashes: What can we learn from examining the built environment?

This paper examines the impact of personal and environmental characteristics on severity of injuries sustained in pedestrian–vehicle crashes using a generalized ordered probit model. The data covers 2000–2004 of pedestrian–vehicle crashes taken from police incident reports for Baltimore City and supplemented with local land use, urban form and transportation information specific to the individual crash locations. The results on personal and behavioral variables confirm previous findings. Women pedestrians involved in crashes tend to be injured less frequently than their male counterparts; children have an increased likelihood of sustaining injuries and older persons are more likely to be fatally injured. Pedestrians who cross against the traffic signal, are not in a crosswalk and are involved in a crash after dark are associated with greater injury risk. Of the built environment policy variables of interest, transit access and greater pedestrian connectivity, such as central city areas, are significant and negatively associated with injury severity. These results suggest that the environmental conditions should be given more scrutiny and be an important consideration when evaluating and planning for pedestrian safety.     

Discretionary activity location choice: in-home or out-of-home?

This paper examines the location choice associated with discretionary activities (in-home vs. out-of-home). These substitution patterns are important in terms of travel demand as in-home activities do not necessitate travel while out-of-home activities incur travel. Mixed logit models are estimated using an activity dataset (2003 CHASE data) to analyze the factors associated with this choice at the individual activity-level. Results suggest that the attributes of an activity significantly contribute to understanding the likelihood of engaging in out-of-home activities. Activity type interaction terms reveal the varying influence that socio-demographics, activity attributes and travel have over four different activity types modeled. The results reveal that the location choice (in-home vs. out-of-home) is sensitive to travel characteristics. As the travel time and cost increases, an individual is less likely to engage in an activity out-of-home. Compared to passive and social activities, the location of active activities is more sensitive to changes in travel attributes.     

Effects of neighborhood environments on perceived risk of self-driving: evidence from the 2015 and 2017 Puget Sound Travel Surveys

Autonomous vehicles (AVs), with an expectation of improving road safety, are closer to becoming a reality. A large number of people are still concerned about how AVs would operate in real-life driving environments. The present paper investigates the factors that affect people’s views of the interactions between AVs and other road users based on a large sample from the 2015 and 2017 Puget Sound Travel Surveys. We specifically highlight the effects of the neighborhood environment and road infrastructure. We estimate a generalized ordered logit model to demonstrate the extent to which certain neighborhood environment and road infrastructure features affect individuals’ safety perceptions of AVs, controlling for demographics, daily travel patterns, and general interest in riding AVs. The results reveal that designated bicycle facilities are positively associated with individuals’ safety perceptions related to AVs. We find that residents from neighborhoods with more pedestrian facilities are more likely to express higher levels of concern on AVs’ capabilities to react to the environment. Our results also suggest that people living in mixed-use neighborhoods are more confident in sharing the road with AVs. The findings provide useful implications for effective policy interventions and infrastructure provisions that may affect the market penetration rates of AVs while keeping up the standards for other road users, such as bicyclists and pedestrians.