Planning Optimal Path Networks Using Dynamic Behavioral Modeling

EasyChair Preprint 91

Abstract

Mistakes in pedestrian infrastructure design in modern cities decrease transfer comfort for people, impact greenery due to appearance of desire paths, and thus increase the amount of dust in the air because of open ground. These mistakes can be avoided if optimal path networks are created considering behavioral aspects of pedestrian traffic, which is a challenge. In this article, we introduce Ant Road Planner, a new method of computer simulation for estimation and creation of optimal path networks which not only considers pedestrians' behavior but also helps minimize the total length of the paths so that the area is used more efficiently. The method, which includes a modeling algorithm and its software implementation with a user-friendly web interface, makes it possible to predict pedestrian networks for new territories with high precision and detect problematic areas in existing networks. The algorithm was successfully tested on real territories and proved its potential as a decision making support system for urban planners.

Keyphrases: Human Trail System, Pedestrian Infrastructure, Pedestrian Network, agent-based modeling, ant road planner, group behavior, optimal path network, path formation, path network, pedestrian behavior, pedestrian flows simulation, stigmergy, urban planning, urban territory

@booklet{EasyChair:91,
  author    = {Sergei Kudinov and Egor Smirnov and Gavriil Malyshev and Ivan Khodnenko},
  title     = {Planning Optimal Path Networks Using Dynamic Behavioral Modeling},
  doi       = {10.29007/ptfv},
  howpublished = {EasyChair Preprint 91},
  year      = {EasyChair, 2018}}