Bicycle Flows

 

 Improving bicycle flows through the city

Background

While many cities are struggling to increase cycle usage by citizens and other city centre users, being successful in encouraging adoption of cycling has its own problems. Such ‘cycling cities’ can become victims of their own success, as demand for bike storage and usage of bike routes exceeds provision. How can cities continue to support the achievements of their own policies, and create a blueprint for cities at the beginning of their cycling journeys? 

    Description

    In Delft the rate of bicycle use is very high, due to a number of factors. Firstly, the growth of the TU Delft student population is stronger than expected. As a result, heavier bicycle flows can be seen on the cycling routes already used most often by student cyclists.

    In addition, more students continue to live at their parental home outside the city, meaning that they daily commute between Delft and their place of residence. They therefore depend on the train and bicycle as their means of transportation to get to the campus putting extra strain on the cycling routes between the train station and the TU Delft. 

    Lastly, the growth of the general population and the corresponding increase in bicycles put extra load on the already heavy bicycle flows on some of the cycling routes. These cycling routes often run through residential areas causing negative effects to other road users. The municipality wants to spread these cycling flows across the cycling network in order to alleviate pressure from current cycling routes. For this idea to be further developed, two questions need to be developed:

    1. how do we gain proper insight into the current bicycle flows and the best available alternative routes to spread the bicycle flows across the city?;
    2. how do we encourage cyclists to choose alternative routes even when they are longer in distance?

    Expected Outcomes

    • An instrument that provides policy makers with insight into real-time bicycle flows;
    • A predictive model that can anticipate the effect on the cycling network if specific alternative routes are used more often;
    • An experimental tool for managing bicycle flows dynamically.

    Expected Impacts

    • Increased use of alternative cycling routes as a result of an improved spread of cyclists across the cycling network. 
      • In concrete terms this means: an increase of cyclists on currently less busy cycling routes that are suited to accommodate this increase, so the problem is not relocated to other neighbourhoods.
    • Improved accessibility of residential areas between the TU Delft and the central train station for all means of transport.