Measuring the Impact of Motivations on Travelers’ Strategic Decisions in Different Traffic Conditions: Data Collection, Analysis, and Modeling

Continued growth in travel demand and the corresponding congestion occurrence accentuates the need for active transportation and demand management (ATDM) for predictive rather than reactive congestion mitigation strategies. These strategies (applications) reduce demand and thus improve the performance of different surface transportation facilities. Earlier research work mainly utilized simulations and field experiments to suggest improvements to ATDM applications associated with pricing and/or provision of information to travelers; however, few such studies considered the dynamics of travelers’ motivations as an essential component in the performance of a given ATDM application. In other words, how travelers’ motivations change as a function of the ATDM applications’ characteristics remains largely unexplored. This study thus examines the theory of planned behavior (TPB) to analyze travelers’ motivations associated with different mode choices and captures and measures the corresponding dynamics of motivations when facing different surrounding circumstances and ATDM regimes. Utilizing a survey and an online data collection platform to estimate motivational patterns behind travelers’ mode choices, following and extending the TPB paradigm, the study concludes that: (a) travelers’ mode choices are primarily determined by intentions (motivations); (b) income and age are two additional characteristics that influence mode choices; (c) travelers’ reasoned choices are mainly attitude-oriented; and (d) different attitudinal aspects are accentuated or compromised along with the changes of travel conditions and ATDM applications.