The safety in numbers (SiN) effect is often invoked as a mechanism by which increasing numbers of vulnerable road users introduced into a transport network can result in reduced per-capita risk of collision resulting in injury or death. Mechanisms underlying SiN’s function, however, have not been well described. Extending previous agent-based modelling work, this study explored the potential role of behavioural adaptation of drivers to the presence of cyclists that followed patterns of Rescorla–Wagner (R–W) learning models. Results indicated that SiN effects consistent with those present in real-world studies were replicable in a simulated environment, and that R–W model input settings were able to control the strength of the SiN effect in combination with the influence of increased cyclist density. The combined theoretical and simulation model presented here provides a novel means by which the potential safety effects of cycling policy settings and interventions may be academically and practically explored.

A model of behavioural adaptation as a contributor to the safety-in-numbers effect for cyclists / Thompson, Jason; Savino, Giovanni; Stevenson, Mark. - In: TRANSPORTATION RESEARCH. PART A, POLICY AND PRACTICE. - ISSN 0965-8564. - STAMPA. - 85:(2016), pp. 65-75. [10.1016/j.tra.2015.12.004]

A model of behavioural adaptation as a contributor to the safety-in-numbers effect for cyclists

SAVINO, GIOVANNI;
2016

Abstract

The safety in numbers (SiN) effect is often invoked as a mechanism by which increasing numbers of vulnerable road users introduced into a transport network can result in reduced per-capita risk of collision resulting in injury or death. Mechanisms underlying SiN’s function, however, have not been well described. Extending previous agent-based modelling work, this study explored the potential role of behavioural adaptation of drivers to the presence of cyclists that followed patterns of Rescorla–Wagner (R–W) learning models. Results indicated that SiN effects consistent with those present in real-world studies were replicable in a simulated environment, and that R–W model input settings were able to control the strength of the SiN effect in combination with the influence of increased cyclist density. The combined theoretical and simulation model presented here provides a novel means by which the potential safety effects of cycling policy settings and interventions may be academically and practically explored.
2016
85
65
75
Thompson, Jason; Savino, Giovanni; Stevenson, Mark
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1061281
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