Published

2014-01-01

Looking ahead: a vision-based software for predicting pedestrian movement

Ver no es mirar: el desarrollo de un programa computacional basado en la visión, para predecir el movimiento de los peatones

DOI:

https://doi.org/10.15446/ing.investig.v34n1.42792

Keywords:

pedestrian movement, drift-based movement, agents, vision (en)
movimiento peatonal, movimiento basado en Drift, agentes, visión (es)

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Authors

  • Rodrigo Mora Universidad Diego Portales
  • Hernán Astudillo Universidad Técnica Federico Santa María
  • Samuel Bravo Pontificia Universidad Católica

This paper presents ongoing research on the use of agents equipped with "exomatic visual architecture" (Turner et al., 2001). The main objective was to test whether some rarely explored isovist measures, like drift and longest line of sight, are associated with aggregated movement patterns of downtown Santiago, Chile. To test this idea, a series of algorithms were created and compared with observed data recorded at approximately 200 points during an entire workday. The main results show that drift-based algorithms were better suited to predict aggregated patterns than random behavior, although the extent of such relation is still weak (r2 = 0.27). From a theoretical point of view, these results seem to be in accordance with current cognitive theories (Clark, 2009; Thompson, 2007) stressing the dynamic nature of human behavior.

Este artículo presenta una investigación en curso sobre el uso de agentes provistos de visión exomática (Turner et al 2001). El objetivo principal es evaluar si algunas medidas, raramente examinadas, como las isovistas: líneas de visión más extendida, están asociadas a flujos de movimiento existentes en el centro de Santiago de Chile. Para ello, se crearon una serie de algoritmos que guían a los agentes y se compararon con los flujos detectados en cerca de 200 puntos, durante un día hábil completo. Los resultados principales, mostraron que los algoritmos basados en el Drift fueron más efectivos en reproducir los flujos de movimientos, comparados con los algoritmos basados en un movimiento aleatorio de los agentes, aunque esta correlación es aún débil (r2 = 0,27). Desde un punto de vista teórico, estos resultados parecen estar en línea con las teorías de cognición contemporáneas (Clark, 2009; Thompson, 2007) que tienden a enfatizar la naturaleza dinámica del comportamiento humano.

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Looking ahead: a vision-based software for predicting pedestrian movement. (2014). Ingeniería E Investigación, 34(1), 79-82. https://doi.org/10.15446/ing.investig.v34n1.42792