Edinburgh Napier University

  Random utility models are often used to model traveler mode choice behavior in the demand analysis of a transit system. Transit operators might base their policy and operations planning on these estimates. The choice probability of these models is expressed in terms of utility for all transit modes, which is in turn associated with the characteristics or attribute values perceived by each traveler. In practice, however, often observed or published attribute values (e.g., fare) rather than perceived attribute values are used to estimate the utility. In reality, perception biases of the actual attribute values are likely to happen due to lack of convenient access to information. Fare and travel time, for example, are often not precisely known to all travelers. Therefore, there are variations in the perceived transit service attributes among travelers. How these perception variations affect the choice behavior is not generally understood. Will the provision of perfect information, and therefore the removal of these biases in attribute perceptions, be beneficial to travelers, operators and the overall system? This study conducts some simulation experiments to explore these issues.