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King Abdulaziz University provides its educational services to over 180 thousand students. The number of vehicles entering and existing the university’s reached 350 thousand vehicles per day; Based on that, the transportation network within and around the campus experiences high vehicles delay. The first step to deal with the issue is by developing a conceptual travel demand modelling framework, which set the map for developing the travel demand models. This research presents a conceptual travel demand modelling framework, which is divided into four stages: define the evaluation time period (short, mid, long time span), establish a data collection program, prioritize transportation issues at campus, and model the transportation issues and propose solutions. The university has various departments. Each one contributes to the transportation movement by one way or the other. The framework incorporates these departments in the modelling framework with the aid of technology with the aim of relieving the pressure on the university’s transportation network in a timely manner and with minimum cost. Implementation of this modelling framework showed that management strategies supported with specialized transportation studies will accomplish that aim, while in the same time, it will ensure a sustainable transportation system, and improve the quality of life.

One of the advanced methods of modeling activity duration is the multiple discrete-continuous extreme value (MDCEV) model. The translating satiation parameter of the model is intended to capture the constant marginal utility effect, but model testing shows that it does not do so. In this paper, the structure of the translating satiation parameter was modified to incorporate an additional parameter that enables the model to capture this effect. Two datasets from cities in Saudi Arabia and Germany were used to test the applicability of the modified model for any dataset. The results showed that the proposed model structure increased the accuracy of activity duration prediction by up to 74%. The modified model represents an improvement to the conventional MDCEV model in terms of accuracy and flexibility, and as such should be a valuable tool in transportation planning and management.Key words: activity duration model, translating satiation parameter, constant marginal utility.Une des methodes avancees de modelisation de duree d'activite est le modele de valeurs extremes multiples discretes continues (<< MDCEV >>). Le parametre de traduction de satiete du modele est destine a capturer l'effet de l'utilite marginale constante, mais les essais du modele montrent qu'il ne fait pas ainsi. Dans le cadre de cette etude, la structure du parametre de traduction de satiete a ete modifiee afin d'incorporer un parametre supplementaire qui permet au modele de reproduire cet effet. Deux ensembles de donnees de villes en Arabie Saoudite et en Allemagne ont ete utilises afin de verifier l'applicabilite du modele modifie dans le contexte de n'importe quel ensemble de donnees. Les resultats ont revele que la structure du modele propose a donne lieu a une augmentation de l'exactitude de prediction de duree d'activite par au-dela de 74%. Le modele modifie represente une amelioration du modele de MDCEV traditionnel en matiere d'exactitude et de flexibilite et comme tel devrait etre un outil precieux dans la planification et la gestion du transport. [Traduit par la Redaction]Mots-cles: modele de duree d'activite, parametre de traduction de satiete, utilite marginale constante., IntroductionThe multiple discrete-continuous extreme value (MDCEV) model proposed by Bhat (2005) is an advanced model that uses random utility maximization theory and the Kuhn-Tucker demand system model to estimate activity [...]