How is liability exposure calculated when AVs crash?

A summary of a paper from Cruise’s VP of risk management

Mohsen Khalkhali

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Source: Forbes

A complex and evolving topic but a paper I read this week, by Tetteh Otuteye et al, tries to quantify it. It is titled “Projection of On-Road Liability Losses for Autonomous Driving” written by Cruise’s risk team. I provided my summary below (full paper on the Casualty Actuarial Society website).

The paper starts with the usual SAE classification for automated driving which ranges from L0, no automation, to L5, fully autonomous. It mentions that there is already a large body of research for ADAS with a focus on human-centered risk frameworks, while L4, L5 autonomy evaluation lacks actuarial methods.

Liability Exposure

AVs operating as part of a commercially owned and operated fleet of robotaxis are exposed to many of the same risks faced by privately owned rideshare vehicles with human drivers. The involvement of an AV in a collision may add some uncertainty to the task of assigning liability given the current lack of legal precedents to inform these analyses.

When accidents happen, the two most likely outcomes are (i) damage to property; and (ii) bodily injury. For a fleet of robotaxis, below are examples of the types of outcomes for which coverages would…

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