Abstract Advanced traveler information systems (ATISs) have attracted a considerable amount of attention in recent years. By providing drivers with traffic information, these information systems are likely to help in reducing travel time, traffic-related congestion and consequently lead to reduced levels of vehicle emissions. With the presence of in-car navigation and communication systems, the ATIS can benefit commuters as well as unfamiliar drivers. However, in the absence of in-car navigation systems – the case in most developing countries, familiar drivers are likely to use these information systems more effectively and hence are likely to make well-informed route-diversion and other travel-oriented decisions. This paper is devoted to developing driver familiarity models to identify the factors that influence drivers' familiarity with the urban route network layout. A number of non-linear familiarity models are developed and coefficients are estimated. Estimation results indicate that travel characteristics such as familiarity with one alternative route, residence leaving times, travel time to job location and the presence of young children have a profound impact on the driver's level of familiarity. Separate familiarity models for male and female drivers are also specified and estimated. When subjected to the same set of predictors, the familiarity of male drivers turned out to be more responsive than the familiarity of female drivers. This result could reflect, among other things, the fact that male drivers have more frequent and diverse activity stops that expose them to different sections of the transportation network layout.
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