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April 18, 2022

Autonomous Vehicles: Mortality & Insurance Implications

In 1908, Henry Ford profoundly changed the automotive industry by developing and manufacturing automobiles at scale. The Ford Model T is generally considered to have been the first affordable car, subsequently ushering in the era of mass-market transportation and leading to widespread societal changes around the world.

111 years later, in 2019, the recent advances in computing power and artificial intelligence have made the previously science-fiction idea of living among unmanned vehicles, capable of navigating their landscapes without human input, a reality. A number of companies are already testing their vehicles in various locations and, since 2009, Google-owned Waymo has already driven more than five million (real road) miles, using self-driving technology (Waymo, 2018).

In a similar fashion to Ford’s global impact, autonomous vehicles will also change society, by significantly altering how we travel.

The areas of potential impact are wide and far-reaching and could include:

  • reduced car ownership
  • radically different car design geared more towards comfort and luxury
  • more older drivers, fewer taxi/bus/truck/delivery drivers
  • lighter burden on hospital and emergency services from fewer road accident injuries
  • significant improvements to rush-hour traffic

However, perhaps the most significant and important implications, at least to the actuarial profession, is the potential for reduced mortality and morbidity from traffic-related accidents and an overhaul of personal auto-insurance risks.

Mortality & morbidity implications

Previous research has indicated that over 90% of road accidents today result from human error. For example, the National Motor Vehicle Crash Causation Survey conducted between 2005 and 2007 attributed critical crash causation as follows:

Vehicle cr​​​​ash attribution

mortality statistics

As we try to forecast and imagine the future driverless world implications, we should first note that nearly 1.3 million people die globally in road crashes each year and an additional 20 to 50 million people worldwide are injured or disabled (Association for Safe International Road Travel, 2013). Indeed, road traffic injuries are currently estimated to be the ninth leading cause of death across all age groups globally and the leading cause of death among people aged 15-29 years (World Health Organisation, 2015). Given the potential for driverless cars to reduce accidents caused by human error the mortality and morbidity implications from autonomous vehicles are profound.

It is of particular interest to consider where these mortality effects are likely to have most impact. Unsurprisingly, traffic related deaths are not uniform across geographic location, socio-economic status, gender and age groups.

The World Health Organisation (WHO) highlights some of these disparities:

  • Income: The global average number of deaths per 100,000 population is 17.4. However, the breakdown between low income, middle-income and high-income is 24.1, 18.4 and 9.2 respectively (WHO, 2015).
  • Location: The African region has the highest fatality rates (26.6 per 100,000 population) and Europe has the lowest (9.3 per 100,000 population) (WHO, 2015).
  • Age: 60% of road traffic deaths are among 15-44 year olds (WHO, 2013).
  • Gender: 77% of all road traffic deaths are men (WHO, 2013).

Proportion of road traffic deaths by age range and country income status

WHO statistics

In terms of the potential for improvements in vehicle accident related mortality and morbidity, this may depend on the degree to which drivers in society can and wish to transition from fully operating vehicles to vehicles that are completely automated. Despite recent advances, there are still many hurdles and obstacles to overcome, and like any innovation there will be a prolonged period of transitional change before autonomous vehicles become mainstream. According to the Society of Automotive Engineers’ (SAE) J3016 standard there are six different levels of automation from level 0 (no automation) to level 6 (full automation), as shown below:

Insurance implications

Inevitably, the motor insurance world will change drastically as we move through the six levels of autonomy. As previously discussed, it is estimated that over 90% of road accidents today result from human error. Hence, personal car insurance will be redefined as risk moves from vehicle users to vehicle manufacturers and software/hardware suppliers.

Attribution of liability will become a much more grey area as discussed in AIG’s 2017 report, ‘The Future of Mobility and Shifting Risk’. In a survey they carried out asking “who is liable in a fully driverless world?” respondents identified various parties that might be liable in crash scenarios involving driverless cars. The parties identified included (AIG, 2017):

  • the car manufacturer,
  • software programmer,
  • vehicle occupant,
  • vehicle owner,
  • parts manufacturer,
  • internet service provider,
  • pedestrian and road manufacturer.

As the inevitable driverless world takes over, many traditional auto-related risks will no longer be as prevalent. Risks such as those caused by reckless or distracted driving, speeding, ignoring stop signs/red lights, unsafe lane changes, tailgating and road rage will be replaced by new, emerging risks such as malfunctioning software and cyber security.

The migration and ensuing calculation of risk will be particularly challenging during what has been called the ‘chaotic middle’ transition period where vehicle owners and the AI software share responsibility for the vehicle’s operation and any resulting liability.

Clearly, we are entering a new era of transportation. Despite the many challenges ahead, it appears that significant changes will be increasingly felt across many different aspects of society, as autonomous vehicles make their way into our everyday lives.


AIG (2017). The future of mobility and shifting risk. (Innovation + Risk series; 8). December 2017.

Association for Safe International Road Travel ([2013]). ‘Annual global road crash statistics’; ‘Annual United States road
crash statistics’. http://asirt.org/initiatives/informing-road-users/road-safetyfacts/road-crash-statistics

Society of Automotive Engineers (2014; 2016). Taxonomy and definitions for terms relating to driving automation systems for on-road motor vehicles. J3016_201609. https://www.sae.org/standards/content/j3016_201609/

Singh, S. (2018). Critical reasons for crashes investigated in the National Motor Vehicle Crash Causation Survey. (Traffic Safety Facts: Crash; Stats. Report No. DOT HS 812 506). March 2018. Washington, DC: National Highway Traffic Safety Administration. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812506

Waymo (2018). Waymo safety report: On the road to fully self-driving. https://waymo.com/safety

World Health Organization (2013). Global status report on road safety 2013: supporting a decade of action. http://www.who.int/violence_injury_prevention/road_safety_status/2013/en/

World Health Organization (2015). Global status report on road safety 2015. http://www.who.int/violence_injury_prevention/road_safety_status/2015/en/


A version of this article was originally published in the Institute and Faculty of Actuaries Longevity Bulletin (Issue 11, September 2018) and reproduced here with kind permission. The original article can be downloaded here.

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Mark Farrell FIA PhD

I'm a UK qualified Actuary and currently a Senior Lecturer of Actuarial Science at Queen's University Belfast. Prior to academic life, I spent 10 years working as a consulting actuary.

Mark Farrell

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