Space and Motion: Data-Driven Model of 4D Pedestrian Behavior (2017)
article⁄Space and Motion: Data-Driven Model of 4D Pedestrian Behavior (2017)
abstract⁄The understanding of space relies on motion, as we experience space by crossing it in time, space’s fourth dimension. However, architects lack the necessary tools to incorporate people’s motion into their design of space. As a consequence, architects fail to connect space with the motion of the people that inhabit their buildings, creating disorienting environments. Further, what if augmentation technology changes how we inhabit space and the static built environment does not fit people anymoreThis paper explores the problem of developing a model from people’s motion, to inform and augment the architecture design process in the early stages. As an outcome, I have designed a model based on data from humanspace interaction obtained through field work. First, relevant behavior was identified and recorded. Second, a metric was extracted from the data and composed by speed, the 4th D dimension as time, and gestures. Third, the original behavior was rebuilt, producing a set of rules. The rules were combined to form the model of humanspace interaction. This generalizable model provides a novel approach to designing space based on data from people. Moreover, this paper presents a means of incorporating inhabitants’ behavior into digital design.Finally, the model contributes to the advancement of people’s motion research for general applications, such as in transport engineering, robotics, and cognitive sciences.
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| Year |
2017 |
| Authors |
Gonzalez Rojas, Paloma. |
| Issue |
ACADIA 2017: DISCIPLINES & DISRUPTION |
| Pages |
266-273 |
| Library link |
N/A |
| Entry filename |
space-motion-data-driven-model-4d |
