A 7-day multiagent model of travel demand is presented. Multiday modeling has several strong points and expands the applicability of travel demand models. It allows for incorporating the interrelationship of individual budgets and travel behavior, and the model output provides high flexibility for the further use of the data. Multiday models allow simulation of individual mode use over time and identification of mode clienteles. The challenge of multiday modeling is the realistic representation of behavioral variability and stability and dealing with a large number of possible combinations when generating activity schedules. The presented activity generation approach has two steps: ( a) deriving agendas of intended activities from observed activity schedules and assigning the agendas to the agents in the model and ( b) transforming these agendas to feasible activity schedules with specific activity start times and activity destinations by using a greedy algorithm. This activity generation module was incorporated in a 7-day travel demand model. The model was applied for predicting changes in mode use in the German city of Erlangen caused by demographic development and growth in car ownership within the next decade.


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    Title :

    Multiday Multiagent Model of Travel Behavior with Activity Scheduling


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2009-01-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English