Modelling Cyclist Delay at Intersections from GNSS Trajectories: Underlying Factors and Behavioural Characteristics

Abstract

Cyclist delays at intersections strongly affect perceived trip quality and network performance through interruptions, i.e. slowing, stopping, negotiating conflicts, and re-accelerating. We aim to measure these delays consistently through GNSS trajectories by taking into account the cruising conditions of each situation and analysing factors affecting them. Steady-state cruising segments are identified, and a mixed-effects model predicts cyclist-specific cruising speeds based on infrastructure, slope, environment, and rider heterogeneity. Intersection delays are then defined as the ratio of observed crossing time to this personalised cruising-time baseline, with crossing distance extracted through a consistent geometric method. Results of a mixed-effects delay ratio model show that traffic signals, left turns, and peak periods are the dominant sources of delay, whereas right turns and off-peak times reduce them. These findings point to clear intervention priorities: reducing signal-related waiting through improved phase coordination, simplifying left-turn movements, and minimising conflict points through improved intersection layouts.