solution-oriented collaborative computational planning for smoother decision-making

Social Distancing Streets

The COVID-19 health crisis has brought back into the debate the forgotten issue of managing epidemics in cities, and made decision-makers aware of the need to enforce physical distancing between individuals in order to stem the spread. virus. For example, many cities have put in place temporary arrangements influenced by tactical town planning, such as reducing or stopping automobile traffic on certain parts of the network, in order to give more space to pedestrians. Indeed, in certain urban configurations, such as those of the dense urban centers of European cities, the sidewalks are generally too narrow to guarantee a sufficient distance between people.

This agent-based model simulates the close contacts that some individuals may have while walking in town, and thus makes it possible to empirically and quantitatively measure the potential of each street in terms of physical distancing.

The simulation offers real-time interactivity as well as all the adjustments necessary to make it a participatory, intuitive and comprehensive decision-making tool. Indeed, on the basis of the simulation results, decisions can be taken collectively on which streets to close to traffic and at what times of the day, in order to guarantee the optimal potential of pedestrian accessibility and social distancing.

Try the model yourself by clicking on this link.

This example, although designed on a detailed scale for demonstrative reasons, is reproducible on a larger scale, for a whole neighbourhood or a whole city. In order to increase the realism and reliability of the simulation, data from pedestrian counts are desirable.

Do not hesitate to contact us to assess the feasibility of this model in your city and to obtain a detailed estimate for design services, but also advice and facilitation of participatory workshops.


Paris, France

Model try-out