Open Access

Pablo S. Löw, Jukka M. Krisp, Andreas Keler

• Current bicycle routing applications often rely on numerical metrics. These offer limited support for users seeking more nuanced, human-readable route assessments. This paper explores the use of a fuzzy inference system to enhance route selection. The idea is to model subjective and qualitative characteristics with fuzzy logic. By comparing routes from a set of alternatives for a given origin–destination pair, we demonstrate how fuzzy set theory can translate complex quantitative information into intuitive verbal descriptors (e.g. “long” or “uneven”). A case study in the city of Augsburg exemplarily shows how a fuzzy inference system helps to make a selection from three alternative bike routes. These are based on three exemplary measures (length, elevation and pavement roughness length). The results document a defuzzyfied measure helping to select the most suitable route. This approach intends to reduce cognitive load, supports informed selection of routes, and aligns more closely withCurrent bicycle routing applications often rely on numerical metrics. These offer limited support for users seeking more nuanced, human-readable route assessments. This paper explores the use of a fuzzy inference system to enhance route selection. The idea is to model subjective and qualitative characteristics with fuzzy logic. By comparing routes from a set of alternatives for a given origin–destination pair, we demonstrate how fuzzy set theory can translate complex quantitative information into intuitive verbal descriptors (e.g. “long” or “uneven”). A case study in the city of Augsburg exemplarily shows how a fuzzy inference system helps to make a selection from three alternative bike routes. These are based on three exemplary measures (length, elevation and pavement roughness length). The results document a defuzzyfied measure helping to select the most suitable route. This approach intends to reduce cognitive load, supports informed selection of routes, and aligns more closely with how users perceive real-world biking conditions. Our work contributes a methodological foundation for integrating fuzzy logic into route selection. We thereby intend to offer an alternative to conventional route selection strategies dominated by rigid cost-based models.…