Building a planning tool for the E-Bike City

Abstract

Urban areas are increasingly prioritizing bike lanes as many cities reconsider the dominant role of cars and aim to repurpose existing road space for bike lanes [1]. While many initiatives progress incrementally, the E-bike City offers a more integrated vision that includes radical reconstruction of urban areas and considers the impact of large-scale bike networks on car transportation [2]. However, user-friendly solutions to interact and compare more complex optimization approaches for bike network planning are scarce and primarily remain in scholarly work. There is a clear need for accessible, user-friendly tools that enable planners to evaluate both iterative and global strategies to support the vision of a bike-friendly city better. Our objective is to develop an interactive web application that enables users to reallocate road space to bike lanes with multiple optimization strategies and evaluate their effects using metrics that reflect bike and car network efficiency and user perception [3]. The project will begin with creating a user interface that can visualize bike network configurations resulting from optimization implementation running on the backend, based on user-defined parameters: area of interest and the desired number of bike lanes. In addition, we design a dashboard for evaluating outcomes using Pareto optimality between bike and car travel times, among other metrics, and allow for pairwise comparison of different scenarios. The developed web application allows flexible testing of road space reallocation from specific areas to entire city networks. It showcases network scenarios derived from both iterative and global optimization methods. Initially tested in Zurich, the tool uses Open Street Map (OSM) data, making it adaptable to different locations. The application also collects user feedback to refine its features and usability. This user-friendly web interface simplifies interaction with complex mathematical models for bike network optimization, improving the anticipation of impacts on other transportation modes.