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Driving to a future without accidents? Connected automated vehicles impact on accident frequency and motor insurance risk

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Show simple item record Pütz, Fabian Murphy, Finbarr Mullins, Martin 2019-08-16T10:54:27Z 2019-08-16T10:54:27Z 2019
dc.description peer-reviewed en_US
dc.description.abstract Road traffic accidents are largely driven by human error; therefore, the development of connected automated vehicles (CAV) is expected to signiicantly reduce accident risk. However, these changes are by no means proven and linear as diferent levels of automation show risk-related idiosyncrasies. A lack of empirical data aggravates the transparent evaluation of risk arising from CAVs with higher levels of automation capability. Nevertheless, it is likely that the risks associated with CAV will profoundly reshape the risk proile of the global motor insurance industry. This paper conducts a deep qualitative analysis of the impact of progressive vehicle automation and interconnectedness on the risks covered under motor third-party and comprehensive insurance policies. This analysis is enhanced by an assessment of potential emerging risks such as the risk of cyber-attacks. We ind that, in particular, primary insurers focusing on private retail motor insurance face signiicant strategic risks to their business model. The results of this analysis are not only relevant for insurance but also from a regulatory perspective as we ind a symbiotic relationship between an insurance-related assessment and a comprehensive evaluation of CAV’s inherent societal costs en_US
dc.language.iso eng en_US
dc.publisher Springer en_US
dc.relation.ispartofseries Environment Systems and Decisions; 39, PP. 383-395
dc.subject Connected automated vehicles en_US
dc.subject Motor insurance en_US
dc.subject Automated driving accident risk en_US
dc.title Driving to a future without accidents? Connected automated vehicles impact on accident frequency and motor insurance risk en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1007/s10669-019-09739-x
dc.contributor.sponsor VI-DAS Horizon 2020 en_US
dc.relation.projectid 690772 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

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