Empiric design evaluation in urban planning

We propose a system to simulate, analyze and visualize occupant behavior in urban environments by combining parametric modeling and agent-based simulation. A procedurally generated 3D city model, with semantic information about the functions and behaviors of buildings, is automatically populated with artificial agents (i.e. pedestrians, cars, and public transport vehicles). In a simulation the built environment and the agents interact with each other. The system identifies empiric correlations between properties such as: functions of buildings and other urban elements, population density, utilization and capacity of the public transport network, and congestion effect on the street network. Practical applications include the assessment of a) bottlenecks, b) public transit efficiency, c) accessibility of amenities, d) quality of service of public transport and the traffic network, as well as e) the stress level and exhaustion of pedestrians. All these aspects ultimately relate to the quality of life within the given urban areas.

Research Highlights
► We simulated movement patterns within synthetic urban scenarios and their impact on green house gas emission.
► We examined the impact of urban planning on the use of different modes of transportation.
► In the course of the investigation we showed that dispersed allocation of individual functions leads to more pedestrians walking or use public transportation and also reduces traffic jams and emissions from individual transportation.