Human perceptions play a significant role in traveler decisions, and therefore are a corner stone inthe feasibility of traveler information systems. Traveler information systems are only valuable if:a) drivers are incapable of accurately acquiring the provided information on their own, and b) theprovided information is relevant for the drivers’ decision criteria. Accuracy of travelerperceptions has been repeatedly researched in public transportation, and has been found to varyaccording to different reasons. However, in spite of the clear significance of traveler perceptions,minimal effort has been put into modeling it. Almost all travel behavior models are based ontraveler experiences, which are assumed to reflect traveler perceptions via the addition of somerandom error component. This work introduces an alternative approach: instead of adding anerror component to represent driver perceptions, it proposes to model driver perceptions. Thiswork is based on a real-world route choice experiment of a sample of 20 drivers who collectivelymade more than 2,000 real-world route choices. Each of the drivers’ experiences, perceptions,and choices were recorded, analyzed and cross examined. The paper demonstrates that: i) driverperceptions are different from driver experiences, ii) driver perceptions explain driver choicesbetter than driver experiences, iii) it is possible to model and predict driver perceptions of traveldistance, time and speed, and iv) in addition to signal strength, driver perceptions are alsoinfluenced by personal characteristics and personality traits.
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