Modeling Context-Sensitive, Dynamic Activity-Travel Behavior, By Linking Short and Long-Term Responses to Accumulated Stress: Results of Numerical Simulations

摘要

Whereas existing activity-based models of travel demand simulate activity-travel patterns for a typical day, dynamic models simulate behavioral response to endogenous or exogenous change along various time horizons. Prior research predominantly addressed a specific kind of change, usually affecting a specific time-horizon. In contrast, the current study aims at developing a dynamic model of activity-travel decisions, which links short and long-term adaptation decisions in a hierarchical manner. Specifically, it focuses on the bottom-up process of influence, where problems with rescheduling on a daily basis may induce a long-term change. It is assumed that travelers will first explore short-term adjustments of their habitual activity-travel patterns, in order to cope with change and increasing stress. Only when such adaptation strategies turn out to be ineffective, they will consider long-term decisions. The proposed framework integrates three key concepts: aspiration, activation and expected utility. Moreover, both rational and emotional mechanisms are taken into account. We demonstrate model properties using numerical simulation. Individual travelers are represented as agents, each with their cognition of the environment, habits, preferences and aspirations. The results offer insight into the dynamics of traveler learning/adaptation and into the evolution of long-term decisions.