Optimizing bike network design: a cost-effective methodology for heterogeneous travel demands using continuous approximation techniques

Abstract

This study presents a methodological framework for determining the most cost-effective design parameters for bike networks in cities with heterogenous travel demands. The suggested model utilizes continuous approximation techniques to calculate the optimal length and spacing between bike lanes, determine the number and location of bike-sharing stations, and estimate the appropriate fleet size (number of bikes). Throughout the process, both user and agency interests are considered. To validate the effectiveness of the proposed model, an example is provided using data from the City of Guayaquil, Ecuador. Additionally, sensitivity analysis is performed to gain further insights into the impact of significant parameters on the network design. The results indicate that agency costs constitute a relatively small proportion of the overall network costs compared to user costs. This finding suggests that the initial investment in facilities has been amortized over time, highlighting the network's long-term viability. Moreover, the study demonstrates that an increase in demand does not necessarily require a corresponding increase in investment. To strike a balance, the model tends to offer a reduced number of facilities, such as bikes, stations, and kilometers of lanes per person, while simultaneously densifying the network to reduce user access times, resulting in shorter total travel times for users. The proposed optimization model serves as a valuable tool for urban planners, aiding them in strategic design decisions during the planning stage of bike mobility systems.

Peer Reviewed

Postprint (published version)