Research on Drivers' Understanding to Traffic State Information According to Their Individual Identities

When operating traffic route guidance systems (TRGS) and providing road users information about traffic state through VMS (variable message signs) systems, most operators and engineers, with their experience and using aggregate statistic data, suppose that all drivers share the same standard for understanding and assessing traffic state. However, each receiver actually has his/her own standard to differentiate one traffic state from another. Different receivers may understand the same traffic situation differently due to their dissimilar individual characteristics. Ignoring this dissimilarity and blindly supplying the same traffic state information to all receivers cause TRGS hard to work well. This dissimilarity was firstly analyzed in this paper using statistic and regressive technique with SP (stated preference) and RP (revealed preference) survey data, then, a model was established to demonstrate the relationship between traffic-state-division-speed and information-receivers' individual identities including gender, age, driving years, familiarity with road network and trip purpose.