An online calibration approach that jointly estimates demand and supply parameters of dynamic traffic assignment (DTA) systems is presented and empirically validated through an extensive application. The problem can be formulated as a nonlinear state-space model. Because of its nonlinear nature, the resulting model cannot be solved by the Kalman filter, and therefore, nonlinear extensions need to be considered. The following three extensions to the Kalman filtering algorithm are presented: 1) the extended Kalman filter (EKF); 2) the limiting EKF (LimEKF); and 3) the unscented Kalman filter. The solution algorithms are applied to the on-line calibration of the state-of-the-art DynaMIT DTA model, and their use is demonstrated in a freeway network in Southampton, U.K. The LimEKF shows accuracy that is comparable to that of the best algorithm but with vastly superior computational performance. The robustness of the approach to varying weather conditions is demonstrated, and practical aspects are discussed.

This paper addresses the urban transit sector investigating variables affecting the habitual modal choices of commuters aiming to gain insight into the key factors affecting these choices and the reasons that discourage them from using public transport services. Probit and structural equation models have been estimated, while additional statistical analysis was performed to gain better insight of the commuters’ mobility behavior. The analysis showed that the main factor affecting the preference of commuters toward passenger car is the availability of parking space. A preference of female respondents towards public transport was also evident, while, compared to the other age groups, respondents between the ages of 35 and 44 show a higher preference for car. Furthermore, crowding is the factor that most discourages respondents from the use of public transport. High fare, lack of public transport information and bad accessibility to the transit network do not seem to discourage respondents’ use of public transport in the particular situation that was analyzed in this research. The paper demonstrated how the results drawn from the analysis can be used for tactical and strategic planning. For example, the fact that high fare levels do not discourage commuters from using public transport, may allow policy makers to slightly increase fares and redirect additional revenue to improve other public transport services. Therefore, such findings may be quite useful for policy makers to better tackle commuters’ perception and to define the appropriate urban mobility management actions and policies.