Abstract
Although the four-step model is the most common method in transportation demand modelling, it is exposed to a considerable criticism in terms of representing the actual choice behaviours of travellers. For example, the four steps are presented in a fixed sequence and independently from each other. Such assumption may be correct in case of obligatory trips (e.g. work trips) where travellers’ behaviour has usually no effect on trip generation or trip distribution stages. However, in discretionary trips, they may simultaneously decide on various trip dimensions. This paper tries to overcome the limitations of traditional four-step model associated with discretionary trips by using a joint discrete choice modelling approach that represents destination, departure time and travel mode choices under a unified framework. The proposed model to be used is the Ordered Generalized Extreme Value model where potential spatial correlation among discretionary destinations can be considered as well. The research methodology has been tested by using shopping and entertainment trips data of Eskisehir city in Turkey. The proposed framework seemed to be more effective and offered an accurate alternative to the first three stages of the traditional four-step model in a setting with a limited number of discretionary destinations.
Highlights
Since the four-step model was developed in the 1960s, the sequence of the steps has remained unchanged [1]
That sequence may be violated in discretionary trips where travellers may simultaneously decide on destination, travel mode and other considered travel dimensions such as departure time [2]
As there is a gap in the literature about representing a unified model that connects destination choice with other travel dimension choices, this research contributes to filling this gap through applying the Ordered Generalized Extreme Value (OGEV) model
Summary
Since the four-step model was developed in the 1960s, the sequence of the steps has remained unchanged [1]. For discretionary trips and in case of a congested network, most destination distribution models assume compensations between closer destinations depending on the relative origin - destination impedance function (e.g.travel time) This assumption ignores the fact that individuals may shift their departure time or change the travel mode to travel to their desired destination. As there is a gap in the literature about representing a unified model that connects destination choice with other travel dimension choices, this research contributes to filling this gap through applying the Ordered Generalized Extreme Value (OGEV) model Such a model will account for spatial correlation among different discretionary destinations along with considering simultaneous choices of two of the most significant travel dimensions which are departure time and travelling mode. Approach can be seen as a more accurate and efficient alternative for the first three steps of the traditional four-step model in forecasting and planning issues especially when the scale is small or medium sized (e.g. small and medium sized cities)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
