1. Computer vision-based assessment of cyclist-tram track interactions for predictive modeling of crossing success.
- Author
-
Gildea, Kevin, Hall, Daniel, Mercadal-Baudart, Clara, Caulfield, Brian, and Simms, Ciaran
- Subjects
- *
OBJECT tracking (Computer vision) , *CONVOLUTIONAL neural networks , *STREET railroads , *PREDICTION models , *TRAFFIC cameras , *ENGINEERING mathematics - Abstract
• A high incidence of bicycle crashes on Dublin tram tracks was observed in this study. • Unsuccessful crossings were common at locations with kerbs or traffic pressures. • Modelling shows that the crossing angle is a strong predictor of crossing success. • Interventions: track realignments, jughandle lanes, and traffic reduction. • This study demonstrates how video analyses help us understand bicycle crash causes. Introduction: Single Bicycle Brashes (SBCs) are common, and underreported in official statistics. In urban environments, light rail tram tracks are a frequent factor, however, they have not yet been the subject of engineering analysis. Method: This study employs video-based analysis at nine Dublin city centre locations and introduces a predictive model for crossing success on tram tracks, utilising cyclist crossing angles within a Surrogate Measure of Safety (SMoS) framework. Additionally, Convolutional Neural Networks (CNNs) were explored for automatic estimation of crossing angles. Results: Modelling results indicate that cyclist crossing angle is a strong predictor of crossing success, and that cyclist velocity is not. Findings also highlight the prevalence of external factors which limit crossing angles for cyclists. In particular, kerbs are a common factor, along with passing/approaching vehicles or other cyclists. Furthermore, results indicate that further training on a relatively small sample of 100 domain-specific examples can achieve substantial accuracy improvements for cyclist detection (from 0.31AP 0.5 to 0.98AP 0.5) and crossing angle inference from traffic camera footage. Conclusions: Ensuring safe crossing angles is important for cyclist safety around tram tracks. Infrastructural planners should aim for intuitive, self-explainable road layouts that allow for and encourage crossing angles of 60° or more – ideally 90°. Practical Applications: The SMoS framework and the open-source SafeCross 1 1 https://github.com/KevGildea/SafeCross/. application offer actionable insights and tools for enhancing cyclist safety around tram tracks. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF