A multi-city study on structural characteristics of bicycle networks

Bicycle networks are made up of different types of infrastructure for cars, bikes and mixed use, which has resulted in various definitions being used to describe them. However, it’s crucial to bring these definitions together to understand the structural differences among them and the impact of choices and investments in bike infrastructure....

A Multiscale View on Bikeability of Urban Networks

Although many agree that the use of bicycles improves mobility and quality of life in a city, much less clear is how to assess the progress being made in this direction and how to plan bikeable cities. The bikeability of a city depends on many diverse and interrelated factors such as the land use and transport system, culture and social norms,...

Bicycle network needs, solutions, and data collection systems: A theoretical framework and case studies

Similarly to Maslow’s pyramid of human needs, we theorize that cities have a pyramid of bicycle network needs that depends on their level of bicycle culture. As an increasing number of data sources emerge for bicycle data collection, transport authorities face the challenge of understanding how to use the data and which data sources are fit for...

Understanding bikeability: a methodology to assess urban networks

A fully separated bicycle network from vehicular traffic is not realistic even for the most bicycle-friendly cities. Thus, all around the world urban cycling entails switching between streets of different safety, convenience, and comfort levels. As a consequence, the quality of bicycle networks should be evaluated not based on one but multiple...

Exploring the Potential of Neural Networks for Bicycle Travel Time Estimation

A tool for travel time estimation of cyclists approaching a traffic light can monitor level of service of intersections in bike crowded cities. This work represents a first step in developing such a tool. Neural Network models are evaluated on how they perform in estimating individual travel time of cyclists approaching a signalized...

Clustering-based methodology for estimating bicycle accumulation levels on signalized links: A case study from the Netherlands

The number of queued bicycles on a signalised link is crucial information for the adoption of intelligent transport systems, aiming at a better management of cyclists in cities. An unsupervised machine learning methodology is deployed to produce estimations of accumulation levels based on data retrieved from a bicycle street of the Netherlands....