Reconsidering the Safety in Numbers Effect for Vulnerable Road Users: An Application of Agent-Based Modeling

Authored by Jason Thompson, Giovanni Savino, Mark Stevenson

Date Published: 2015

DOI: 10.1080/15389588.2014.914626

Sponsors: European Union

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

Objective: Increasing levels of active transport provide benefits in relation to chronic disease and emissions reduction but may be associated with an increased risk of road trauma. The safety in numbers (SiN) effect is often regarded as a solution to this issue; however, the mechanisms underlying its influence are largely unknown. We aimed to (1) replicate the SiN effect within a simple, simulated environment and (2) vary bicycle density within the environment to better understand the circumstances under which SiN applies. Methods: Using an agent-based modeling approach, we constructed a virtual transport system that increased the number of bicycles from 9\% to 35\% of total vehicles over a period of 1,000 time units while holding the number of cars in the system constant. We then repeated this experiment under conditions of progressively decreasing bicycle density. Results: We demonstrated that the SiN effect can be reproduced in a virtual environment, closely approximating the exponential relationships between cycling numbers and the relative risk of collision as shown in observational studies. The association, however, was highly contingent upon bicycle density. The relative risk of collisions between cars and bicycles with increasing bicycle numbers showed an association that is progressively linear at decreasing levels of density. Conclusions: Agent-based modeling may provide a useful tool for understanding the mechanisms underpinning the relationships previously observed between volume and risk under the assumptions of SiN. The SiN effect may apply only under circumstances in which bicycle density also increases over time. Additional mechanisms underpinning the SiN effect, independent of behavioral adjustment by drivers, are explored.
Tags
Simulation Infrastructure Microsimulation Risk preferences Animal groups Route choice Traffic fatalities Bicyclists California