An urban driving simulator is used to generate a data base for calibrating and testing a causal path model for subjective time estimates. The model specifies the determinants of subjective time through a web of direct and indirect interactions confirming a positive relationship between the density of urban environmental stimuli (e.g., traffic lights, turns) and time estimates. The results suggest that subjective time is predictable on the basis of time distance, physical distance, and obstacle-like variables. Some implications of the results of urban travel modeling are put forward.
ASJC Scopus subject areas
- Environmental Science (all)
- Earth and Planetary Sciences (all)