Human Centric Routing Algorithm for Urban Cyclists and the Influence of Street Network Spatial Configuration

Abstract

Understanding wayfinding behavior of cyclist aid decision makers to design better cities in favor of this sustainable active transport. Many have modelled the physical influence of building environment on wayfinding behavior, with cyclist route choices and routing algorithm. Incorporating cognitive wayfinding approach with Space Syntax techniques not only adds the human centric element to model routing algorithm, but also opens the door to evaluate spatial configuration of cities and its effect on cyclist behavior. This thesis combines novel Space Syntax techniques with Graph Theory to develop a reproducible Human Centric Routing Algorithm and evaluates how spatial configuration of cities influences modelled wayfinding behavior. Valencia, a concentric gridded city, and Cardiff with a complex spatial configuration are chosen as the case study areas. Significant differences in routes distribution exist between cities and suggest that spatial configuration of the city has an influence on the modelled routes. Street Network Analysis is used to further quantify such differences and confirms that the simpler spatial configuration of Valencia has a higher connectivity, which could facilitate cyclist wayfinding. There are clear implications on urban design that spatial configuration with higher connectivity indicates legibility, which is key to build resilience and sustainable communities. The methodology demonstrates automatic, scalable and reproducible tools to create Human Centric Routing Algorithm anywhere in the world. Reproducibility self-assessment (https://osf.io/j97zp/): 3, 3, 3, 2, 1 (Input data, Preprocessing, Methods, Computational Environment and Results).