Solving the Direction Field for Discrete Agent Motion

TL;DR

This paper introduces an algorithm for calculating direction fields on a grid that accurately reproduces the shortest Euclidean paths for agents navigating around obstacles, enhancing microscopic pedestrian models.

Contribution

The paper presents a novel algorithm for computing direction fields on a grid that exactly reproduces shortest Euclidean paths considering obstacles.

Findings

Algorithm accurately reproduces shortest Euclidean paths.

Direction field effectively guides agent navigation around obstacles.

Method improves microscopic pedestrian dynamics models.

Abstract

Models for pedestrian dynamics are often based on microscopic approaches allowing for individual agent navigation. To reach a given destination, the agent has to consider environmental obstacles. We propose a direction field calculated on a regular grid with a Moore neighborhood, where obstacles are represented by occupied cells. Our developed algorithm exactly reproduces the shortest path with regard to the Euclidean metric.