Autonomous vehicles: Potential benefits, challenges, and risks


Optimists predict that by 2030, autonomous vehicles (AVs) will be reliable, affordable, and common enough to supplant most human driving, resulting in significant cost savings and benefits. However, there are valid grounds for skepticism. People with vested financial interests in the industry make the most optimistic predictions based on previous experience with disruptive technologies such as digital cameras, smartphones, and personal computers. They frequently overlook major roadblocks to autonomous vehicle development while exaggerating future benefits.

There is a lot of uncertainty regarding autonomous vehicle development, benefits and costs, travel impacts, and consumer demand. Before AVs can operate reliably in mixed urban traffic, heavy rain and snow, unpaved and unmapped roads, and areas where wireless access is unreliable, significant progress is required. Before being commercially available in most jurisdictions, years of testing and regulatory approval will be required. The first commercially available autonomous vehicles will certainly be expensive and have limited capabilities. They will bring with them new costs and risks. These limitations will stifle sales. Many drivers will be hesitant to pay thousands of dollars more for vehicles that may not reach their destination due to bad weather or unmapped roads.

Autonomous vehicles cost more than human-driven private vehicles and public transportation, but they are less expensive than ride-hailing and human-driven taxis. Because shared autonomous vehicles will be less expensive but less convenient and comfortable than private autonomous vehicles, many households, particularly in the suburbs and rural areas, will own autonomous vehicles.

Autonomous vehicles will have various benefits and cost challenges, including many external costs (costs imposed on other people). Below, we discuss some of the key benefits and challenges.

Benefits of AVs

  • Reduced drivers’ stress and increased productivity. While traveling, motorists can rest, play, and work.
  • Reduces costs for taxis services and commercial transport drivers.
  • May reduce crash risks and insurance costs. May reduce high-risk driving.
  • Reduces demand for parking at destinations.
  • May increase fuel efficiency and reduce emissions.
  • More independent mobility for non-drivers can reduce motorists’ chauffeuring burdens and transit subsidy needs.
  • More efficient vehicle traffic may reduce congestion and roadway costs.
  • Could facilitate carsharing and ridesharing, reducing total vehicle ownership and travel and associated costs.


  • Increased vehicle costs: AV requires additional equipment, services, and fees.
  • Additional user risks: Additional crashes caused by system failures, platooning, higher traffic speeds, additional risk-taking, and increased total vehicle travel.
  • Reduced security and privacy: AVs may be vulnerable to information abuse (hacking), and features such as location tracking and data sharing may reduce privacy.
  • Increased infrastructure costs: AVs may require higher roadway design and maintenance standards.
  • Additional risks: AVs may increase risks to other road users and may be used for criminal activities.
  • Increased traffic problems: Increased vehicle travel may increase congestion, pollution, and costs associated with sprawl.
  • Social equity concerns: AVs may reduce affordable mobility options like walking, bicycling, and public transportation.
  • Reduced employment: Jobs for drivers may decline.
  • Reduced support for other solutions: Optimistic autonomous driving predictions may discourage other transportation improvements and management strategies.

Optimists claim that because human error is responsible for 90% of crashes, autonomous vehicles will reduce crash rates and insurance costs by 90%, but this ignores the additional risks that these technologies may bring, such as:

  • Hardware and software failures: Complex electronic systems frequently fail due to false sensors, distorted signals, and software errors. Failures in self-driving vehicles will almost certainly result in crashes, though their frequency is difficult to predict.
  • Malicious hacking: Self-driving technologies can be used for criminal activity.
  • Increased risk-taking: When people feel safer, they take more risks, known as offsetting behavior or risk compensation. Passengers in autonomous vehicles, for example, may use fewer seatbelts, and other road users may be less cautious, a phenomenon known as “over-trusting” technology.
  • Platooning risks: Many potential benefits, such as reduced traffic and pollution emissions, necessitate platooning (vehicles traveling at high speeds in dedicated lanes), introducing new risks, such as human drivers joining platoons and increased crash severity.
  • Increased total vehicle travel: Autonomous vehicles may increase travel and crash exposure by improving convenience and comfort.
  • Additional risks to non-auto travelers: Pedestrians, bicyclists, and motorcycles may be difficult to detect and accommodate for autonomous vehicles.
  • Reduced investment in conventional safety strategies: Future efforts to improve driver safety may be hampered by the prospect of autonomous vehicles.
  • Higher vehicle repair costs due to additional equipment: Collision repair costs are likely to rise significantly as more sensors and control systems are added and increased quality control.

As a result of these new risks, autonomous vehicles are unlikely to achieve the 90 percent crash reductions predicted by proponents. According to an analysis of factors contributing to traffic crashes, autonomous vehicles could prevent up to 34% of crashes with improved sensing and response, even more, if the technology eliminates all traffic violations. Still, predictions of 90% crash reductions are exaggerated. Many researchers believe that autonomous vehicles will have crash rates similar to that of a typical driver and that total crashes will rise if autonomous and human-driven vehicles coexist.

Even if autonomous vehicles only reduce crash rates by 10%, their deployment is justified. Still, if autonomous operation increases total vehicle travel, total crashes, including risks to other road users, may increase. For example, if per-mile crash rates are reduced by 10% but vehicle travel increases by 12%, total crashes, including risks to other road users, may increase. Hackers can gain access to autonomous vehicles. Researchers demonstrated that adding graffiti-like marks to a roadside stop sign caused the software to read “Speed Limit 45” incorrectly in one experiment. Over autonomous vehicle control, there will be an ongoing arms race between hackers and software designers, adding costs and risks.

At the moment, autonomous vehicles have a high rate of operational failure. The best test vehicles had one disengagement (when human drivers overrode automated systems) every 16,666 miles in 2019, but the majority had more frequent disengagements. Many disengagements occurred on lower-speed surface streets and involved non-critical risks. Although disengagement rates have decreased, this indicates that autonomous vehicle operating technologies, particularly in mixed urban traffic, will not be ready for implementation by 2020. Shared autonomous vehicles can reduce collisions by making higher-risk drivers more affordable alternatives. Efforts to reduce higher-risk driving can be more effective and publically acceptable if those affected have convenient and affordable transportation options. Parents might buy autonomous vehicles for their teenagers, and travelers might use them after consuming alcohol or drugs.

Many factors, including how vehicles are programmed and affect total vehicle travel, will impact these effects. For example, autonomous vehicles can be programmed to drive faster, take shortcuts through neighborhoods, and take more risks to increase travel speeds; to reduce traffic congestion, autonomous vehicles can be programmed to be more cautious, drive slower, and avoid driving on congested roads or neighborhood streets.