Heather Kaths

E-bike sales have been growing strongly across the globe in recent years. Despite the differences between e-bikes and conventional bicycles, bicycle traffic is typically considered a uniform mode in macroscopic transport modeling. This is problematic because such models do not allow for dedicated e-bike analysis and could therefore have adverse impacts on accuracy. In this study, we therefore investigated whether and how e-bikes are presently modeled in practice and how e-bikes should be modeled to improve data validity and usefulness. To this end, we conducted a review of 14 exemplary strategic transport models and carried out a structured exploratory literature review of existing empirical research. We queried four fields of research and investigated 29 relevant and unique sources covering influences on e-bike ownership and use as well as the characteristics of e-bike mode and route choice. Based on this work, we identified three key findings: (1) purchase choice and mode choice models must allow for scenario setting; (2) generalized costs should also include factors other than travel time, and the factors’ weighting parameters should be estimated separately between conventional bicycles and e-bikes; and (3) it is especially important for e-bike modeling to differentiate between person groups. Future research is needed to investigate route choice parameters for e-bike users, especially concerning the aversion to slopes, and methods to collect e-bike-specific data. Our findings demonstrated that, although modeling e-bikes is worthwhile, appropriate modeling approaches still need to be developed and applied to demonstrate their practicability and usefulness.