The impact of self-driving cars is anticipated to be wide-ranging in many areas of daily life. Self-driving cars have been the subject of significant research on their environmental, practical, and lifestyle consequences.
One significant predicted impact of self-driving cars is a substantial reduction in traffic collisions and resulting severe injuries or deaths. United States government estimates suggest 94% of traffic collisions are caused by human error, with a 2020 study estimating that making 90% of cars on US roads self-driving would save 25,000 lives per year. While this has significant benefits, other health downsides of self-driving cars are predicted; self-driving cars are suggested to worsen air pollution, noise pollution, and sedentary lifestyles.
Self-driving cars are anticipated to increase productivity and housing affordability, as well as reclaim land used for parking. However, they are also predicted to cause greater energy use, traffic congestion and sprawl. The impact of self-driving cars on absolute levels of individual car use is not yet clear, with commentators alternatively predicting increases and decreases. Self-driving cars are one of several potential autonomous vehicles, and other forms of self-driving vehicles, such as self-driving buses, may decrease car use and congestion in ways self-driving cars are unlikely to.
The effect of self-driving cars on various employment fields is predicted to be wide-ranging. Impacts are anticipated in the healthcare, insurance, travel, and logistics fields. Auto insurance costs are expected to decrease, and the burden of cars on the healthcare system to reduced. Self-driving cars are predicted to have substantial and wide-ranging effects on transportation industries, with significant job losses in these fields.
Automobile industry
The traditional automobile industry is subject to changes driven by technology and market demands. These changes include breakthrough technological advances and when the market demands and adopts new technology quickly. In the rapid advance of both factors, the end of the era of incremental change was recognized. When the transition is made to new technology, new entrants to the automotive industry present themselves, which can be distinguished as mobility providers such as Uber and Lyft, as well as tech giants such as Google and Nvidia. As new entrants to the industry arise, market uncertainty naturally occurs due to the changing dynamics. For example, the entrance of tech giants, as well as the alliances between them and traditional car manufacturers causes a variation in the innovation and production process of autonomous vehicles. Additionally, the entrance of mobility providers has caused ambiguous user preferences. As a result of the rise of mobility providers, the number of vehicles per capita has flatlined. In addition, the rise of the sharing economy also contributes to market uncertainty and causes forecasters to question whether personal ownership of vehicles is still relevant as new transportation technology and mobility providers are becoming preferred among consumers.
To help reduce the possibility of safety issues, some companies have begun to open-source parts of their driverless systems. Udacity for instance is developing an open-source software stack, and some companies are having similar approaches.
Health
According to a 2020 Annual Review of Public Health review of the literature, self-driving cars "could increase some health risks (such as air pollution, noise, and sedentarism); however, if properly regulated, AVs will likely reduce morbidity and mortality from motor vehicle crashes and may help reshape cities to promote healthy urban environments." Driving safety experts predict that once driverless technology has been fully developed, traffic collisions (and resulting deaths and injuries and costs) caused by human error, such as delayed reaction time, tailgating, rubbernecking, and other forms of distracted or aggressive driving should be substantially reduced. With the increasing reliance of autonomous vehicles on interconnectivity and the availability of big data which is made usable in the form of real-time maps, driving decisions can be made much faster in order to prevent collisions.