Project

MoCho: Mobility Choices and Societal Impacts

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MoCho (short for "Mobility Choices") is a CityScope module focused on mobility choices and societal impacts. This tool allows prediction of the choices of mobility modes made at the individual level throughout the entire Boston Metro area.    

>>> Check out a live demo of MoCho predictions here <<<

MoCho (short for "Mobility Choices") is a CityScope module focused on mobility choices and societal impacts. This tool allows prediction of the choices of mobility modes made at the individual level throughout the entire Boston Metro area.    

>>> Check out a live demo of MoCho predictions here <<<

What is MoCho? 

The individual choices people make about their mobility behavior have profound impacts on their own lives as well as society as a whole. This is particularly true with regard to their chosen mode of urban transportation. Motorized transportation leads to negative external impacts such as carbon emissions and air pollution, whereas active modes such as walking and cycling improve the physical and mental health of the travelers. Urban planning can influence these mobility choices and their societal impacts by organizing land uses in space in such a way as to encourage short trips using active modes. 

The CityScope MoCho  module uses tangible user interface that allows planners, engineers, and community members alike to experiment with urban interventions and see the predicted impacts on individual mode choice behavior as well as the resulting societal impacts. The first prototype of this module is being used to show the potential impacts of the new Volpe development in Kendall Square. The behavioral models have been calibrated using a combination of individual- and aggregate-level census data for the greater Boston area.

Users interact with the tool by designing the city district using LEGO blocks. Each time the spatial organization and/or density of land uses changes, a three-step prediction process takes place.  

In the first step, simulated individuals are added or removed or change their residential location based on conditional probabilities of living and/or working in each zone. In the second step, the modes of transportation for each commuter in the simulated population are predicted using a logit-based discrete choice model. This prediction model takes into account the personal characteristics of each individual, the attributes of the available commute options, and interactions between the individual characteristics and choice attributes. For example, we all tend to prefer modes which cost less money and take less time, but the time-money trade-off will look different for different people's profiles.

In the third step, some of the health and environmental impacts of the current patterns of mobility behaviour are predicted. The physical activities of walking and cycling have strong impacts on the risk of  all-cause mortality as shown in numerous epidemiological studies. The impacts of any levels of walking and cycling on mortality in a population can be quantified using the World Health Organization's HEAT approach. The CO2 emissions of private cars and public transit can also be estimated using average emission rates. 

By collaboratively experimenting with urban layouts and using the projected societal impacts as a guide, diverse groups of people can contribute to the design of their new community.