Enhancing Safety and Multifaceted Preferences to Optimise Cycling Routes for Cyclist-Centric Urban Mobility

Abstract

In order to optimise bicycle routes across a variety of multiple parameters, including safety, efficiency and subtle rider preferences, this work explores the difficult domain of the Bike Routing Problem (BRP) using a sophisticated Simulated Annealing approach. In this innovative structure, a wide range of limitations and inclinations are combined and carefully calibrated to create routes that skillfully meet the varied and changing needs of cyclists. Extensive testing on a dataset representing a range of rider preferences demonstrates the effectiveness of this novel approach, resulting in significant improvements in route selection. This research is a significant resource for urban planners and politicians. Its data-driven solutions and strategic recommendations will help them strengthen bicycle infrastructure, even beyond its immediate applicability in resolving the BRP.