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Riding the emotional roller-coaster: Using the circumplex model of affect to model motorcycle riders’ emotional state-changes at intersections
Journal article   Peer reviewed

Riding the emotional roller-coaster: Using the circumplex model of affect to model motorcycle riders’ emotional state-changes at intersections

Olugbenga Samuel, Guy Walker, Paul M Salmon, Ashleigh Filtness, Nicholas J Stevens, Christine Mulvihill, Sarah Payne and Neville A Stanton
Transportation Research Part F: Traffic Psychology and Behaviour, Vol.66, pp.139-150
2019
url
https://doi.org/10.1016/j.trf.2019.08.018View
Published Version

Abstract

motorcycles riding circumplex model of affect intersection emotion verbal protocol
This study uses Russell's Circumplex Model of Affect to examine whether motorcycle rider emotion is contingent on the environment and behavior. If it is contingent then it becomes predictable. If it is predictable it becomes potentially usable for innovating new ways to improve the safety and utility of this important transport mode. Eighteen motorcyclists took part in a 15 km on-road study during which they were videoed, tracked via GPS, and followed by a 'chase vehicle' as they negotiated intersections, all the while providing a concurrent verbal commentary. The verbal commentary was content analysed using a novel method for mapping the verbalized emotional themes to the Circumplex Model. Network analysis was then used to explore the state changes between affective zones in the model. Riders' emotions at intersections were found to vacillate between negative and positive affect, demonstrating high degrees of emotional dynamism. Many of these transitions occur in and out of the dominant positive state of calmness, with non-calm states appearing to be aversive and those which riders were seeking to avoid. Knowing this brings forward interesting new approaches for safe intersection design.

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Domestic collaboration
International collaboration
Web Of Science research areas
Psychology, Applied
Transportation

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#11 Sustainable Cities and Communities

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