This research examines the behavioral reactions to the impact of changes in the probability of non-recurrent incident and how this effects the expected costs of a commute trip. This basic approach combines the estimation of a travel demand model (estimated with data collected from a stated preference survey) with a supply side model of a congested highway. We also examine the impact of various socio-economic variables, including a detailed classification of occupational groupings. Our demand model is based on a theoretical model developed to explain how unreliability in travel times affects expected travel costs. We find that expected schedule delay (early and late), lateness probability, and expected travel time influence the expected costs of travel. Our parameter estimates confirm the anticipated values of these parameters: lateness probability has a high disutility, while expected schedule delay early is preferable to expected schedule delay late, and the disutility of expected travel time is between these two. We do not find a high level of significance for planning costs, as expressed by the variance in travel times. Our simulation model shows that schedule costs and lateness probability represent a large fraction of the total cost to the commuter; these are generally not affected by capacity increases but can be reduced by decreasing the probability of a non-recurrent incident.
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