Enhancement of short path algorithm for finding optimal path in cycling navigation

ABSTRACT: Cycling navigation systems often face difficulties in balancing route accessibility, safety, and efficiency due to oversimplified path selection algorithms. This study presents an enhancement to the shortest path algorithm originally developed by Koritsoglou and colleagues, addressing key limitations such as binary edge accessibility evaluation, redundant processing loops, and inefficient memory usage. The original algorithm applies a strict binary access penalty, which frequently leads to suboptimal routing by deprioritizing shorter or higher-quality paths. The enhanced algorithm introduces a weighted scoring system that assigns proportional values to road characteristics, including surface type, slope, and smoothness, enabling a more refined assessment of route suitability. In addition, the optimization process merges threshold filtering and penalty computation into a single iteration loop, reducing execution time by 28.68%. Memory efficiency is further improved through the replacement of dual list structures with a heap queue, resulting in a 55.57% reduction in memory consumption. Experimental evaluations demonstrate that the proposed enhancements lead to more accurate and context-aware route rankings while also improving computational performance. These improvements render the algorithm more suitable for integration into real-world cycling navigation systems, offering a user-centered approach that supports responsive and efficient route planning. By incorporating both route quality and system efficiency, the enhanced algorithm better addresses the practical needs of cyclists navigating complex and dynamic urban environments.

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