Emotional Agents: Modeling Travel Satisfaction, Affinity, and Travel Demand  Using a Smartphone Travel Survey

This dissertation seeks to understand travel satisfaction, travel affinity, and other psychological factors in relation to travel demand, such as the desire for trip making, willingness to spend time traveling, and choice of travel mode. The research was based on the Mood State in Transport Environments survey of 247 Android users (about 6,000 completed trip surveys) in the Blacksburg-Roanoke, VA, Washington, DC, and Minneapolis, MN metropolitan areas from fall 2016 to spring 2018. Respondents answered an entry survey, tracked their travel for 7 days, and answered a trip survey associated with each trip. The dataset provides opportunities to examine travel and activities during travel at the within- and between-person levels.

Three studies in this dissertation examined three measures of the positive utility of travel and their relationship with travel behavior. I quantified (1) the desirability of trip making, (2) the ideal travel time related to different travel characteristics, and (3) the effect of satisfaction on commute mode choice. The first study examines the patterns of travel affinity with various travel modes, trip purposes, and activities during the trip. Travel affinity was measured by asking the willingness to forgo a trip when there is an opportunity to do so. I found that this is a valid and strong measure of the positive utility of travel. Travelers were more willing to make trips when they traveled on foot or bicycle, talked with someone during the trip, and took shorter trips. Additionally, commute trips were less likely to be enjoyed as compared to other, non-commute trips.

The second study focused on (1) testing the validity of the "ideal travel time" measurement and (2) measuring factors associated with the willingness to spend time traveling. I found that although ideal travel time was a strong measure of the positive utility of travel, it was very weakly associated with the desirability of trip making and satisfaction with trips. Although few people wanted zero commute time (3%), the number of trips that had zero ideal travel time was much higher (16%), indicating that the desired travel amount may vary across different trip and environmental characteristics and purpose. Ideal travel time was longer for active travel trips, leisure trips, when conducting activities during trips (e.g., talking, using the phone, looking at the landscape), when traveling with companions and during the weekend.

The third study investigated the role of travel satisfaction and attitude in mode choice behavior. This is one of the very few studies that have considered the role of these psychological factors in multimodal mode choice based on revealed preference data. I found that satisfaction and attitude toward modes and travel played a significant role in the choice model; it also modified the role of travel time in the models. However, the perception of travel time usefulness was insignificant in the model. Scenario analyses based on the model results showed that it is optimal to invest in active transportation and public transit at the same time in order to shift car drivers to these sustainable modes.

These studies contribute to the small but growing body of literature on the positive utility of travel and transrational decision making in transportation. It is the only study that employed a smartphone survey with a repeated measure of trips over the course of 1-2 weeks. The third study is among the earliest attempts to include satisfaction and attitude together into mode choice models.

This dissertation has several implications for research and practice. First, it calls for better measurements of well-being and satisfaction. Second, models with appropriate psychological factors would more realistically resemble actual travel behavior. Including satisfaction in the choice model changes the coefficient of travel time (and potentially cost), which modifies the value of travel time savings, a basis of most benefit-cost analyses in transportation planning and engineering. Better mode choice and trip generation models will generate more reliable predictions of future infrastructure use and investment. Third, studies of travel affinity (positive utility of travel) have implications for demand modeling and management practice. Practitioners should reevaluate the effectiveness of travel demand management strategies aimed at reducing travel time and trips, such as congestion pricing (e.g., tolls), online shopping, and telecommuting.