The most common travel demand model type is the trip-based model, despite major shortcomings due to its aggregate nature. Activity-based models overcome many of the limitations of the trip-based model, but implementing and calibrating an activity-based model is labor-intensive and running an activity-based model often takes long runtimes. This paper proposes a hybrid called MITO (Microsimulation Transport Orchestrator) that overcomes some of the limitations of trip-based models, yet is easier to implement than an activity-based model. MITO uses microsimulation to simulate each household and person individually. After trip generation, the travel time budget in minutes is calculated for every household. This budget influences destination choice; i.e., people who spent a lot of time commuting are less likely to do much other travel, while people who telecommute might compensate by additional discretionary travel. Mode choice uses a nested logit model, and time-of-day choice schedules trips in 1-minute intervals. Three case studies demonstrate how individuals may be traced through the entire model system from trip generation to the assignment.
The United Nations have developed Sustainable Development Goals (SDG) to guide countries’ development in the next decades. In this paper, we first propose a set of measurable indicators that define the degree of achievement of SDG. Secondly, we use a microscopic integrated land use and transportation model to define future scenarios and measure SDG in the future with radical policies. The model is implemented in Munich and Kagawa. The results are not uniform across policies: while the core cities scenario limits urban sprawl and consumption of greenfield land, traffic conditions and GHG emissions worsened. Furthermore, the scenarios also show the relevance of testing policies in different study areas: the core city scenario and the draconic resettlement scenario showed some impact on vehicle-kilometers traveled in Munich, while the impact in the Kagawa region was almost negligible. In general, only strong (and perhaps implausible) relocation policies result in overall significant changes in the SDG indicators.
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