Assessing the impact of interzonal migration on travel demand in Flanders using an Activity-based model.
Assessing the impact of interzonal migration on travel demand in Flanders using an Activity-based model
Following the considerable attention of activity-based models in transportation planning and forecasting, and the necessity to understand and reveal the impacts of transportation policies, this paper aims to simulate and examine a population policy scenario. It explicitly uses FEATHERS, a demand-side activity-based model, operational for Flanders, Belgium. The ABM is required to estimate how the interzonal migration of Flanders’ population from small, rural towns into large, urbanised city areas closely affects the daily activity and travel choices of the individuals. The methodology consists of a classification of FEATHERS zoning system based on the urbanisation degree of Flanders, where the traffic analysis zones (TAZs) belonging to the Flemish Diamond, (comprising Brussels, Ghent, Antwerp, and Leuven) are categorised as urban and others as rural. This categorisation is used to spatially redistribute the population of Flanders from rural to urban zones by 2%, 5% and 10% with equal proportions.
Then, the FEATHERS simulation framework is exploited for executing a current baseline scenario and three migration scenarios. It simulates resident’s activity and travel decisions in a day unit and provides the results in the form of activity-travel diaries. They suggest a noticeable impact on the activity- travel related attributes of both zones after the implementation of the policy scenarios. There is a prominent modal shift toward car as the main mode of travel in urban zones and during peak hours, whereas a slight increase in public transport and car sharing is found in rural zones. Changes in the activity choice are deemed as well. There is an increase in the frequency of trips for home-based activities in urban areas and work-based activities in rural zones. Nevertheless, car remains the dominant mode for all types of activities. Last but certainly not least, the vehicle kilometres and hours travelled are scrutinised as well. Following the patterns of the modal shift and trip frequency analysed, there is an increment of VKT and VHT in urban zones whilst the opposite takes place in rural zones.
Intuitively, one could have expected the opposite to happen in both zones after the execution of the migration scenarios. Furthermore, the findings in the literature also indicate a reverse effect on the transportation demand of rural and urban zones when more individuals are relocated to large, urbanised zones. Therefore, many of the results from this research are indicative rather than conclusive. To ultimately improve the quality of this research and provide conclusive results of a greater extent, more cross-validation needs to be done by further validating the FEATHERS model calibration and output stability.
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