Computational Desire Line Analysis of Cyclists on the Dybb{\o}lsbro Intersection in Copenhagen

TL;DR

This paper introduces a computational method to analyze cyclist behavior at intersections, revealing that cyclists often deviate from designed paths due to inadequate infrastructure, which can inform better street planning.

Contribution

The study develops a novel video-based trajectory detection method and applies it to Copenhagen, uncovering cyclist behaviors that challenge current street design assumptions.

Findings

Hundreds of cyclist trajectories contradict intersection design.

Cyclists prefer straightforward, uninterrupted routes.

Street design neglects actual cyclist behavior.

Abstract

Contemporary street design prioritizes vehicular traffic flow and assumes compliant road users. However, actual human behavior is typically neglected, especially of cyclists, leading to streets with inadequate wayfinding and protection from vehicular traffic. To improve planning, here we develop a computational method to detect cyclist trajectories from video recordings and apply it to the Dybb{\o}lsbro intersection in Copenhagen, Denmark. In one hour of footage we find hundreds of trajectories that contradict the design, explainable by the desire for straightforward, uninterrupted travel largely not provided by the intersection. This neglect and the prioritization of vehicular traffic highlight opportunities for improving Danish intersection design.