  Since 2012, in a case-study in Bucaramanga-Colombia, 179 pedestrians died in
car accidents, and another 2873 pedestrians were injured. Each day, at least
one passerby is involved in a tragedy. Knowing the causes to decrease accidents
is crucial, and using system-dynamics to reproduce the collisions' events is
critical to prevent further accidents. This work implements simulations to save
lives by reducing the city's accidental rate and suggesting new safety policies
to implement. Simulation's inputs are video recordings in some areas of the
city. Deep Learning analysis of the images results in the segmentation of the
different objects in the scene, and an interaction model identifies the primary
reasons which prevail in the pedestrians or vehicles' behaviours. The first and
most efficient safety policy to implement-validated by our simulations-would be
to build speed bumps in specific places before the crossings reducing the
accident rate by 80%.
