What Military Drones Can Teach Self-Driving Cars

The Unseen Dangers of Self-Driving Cars: Lessons from Military Drone Operations

As the self-driving car industry continues to gain momentum, concerns about safety and reliability have grown. While companies like Waymo and Tesla tout their autonomous vehicles as the future of transportation, a closer look at the technology reveals a troubling pattern: the industry is repeating many of the mistakes made in early military drone operations. These errors, which led to accidents, fatalities, and costly setbacks, can have devastating consequences on our roads.

Latency: The Silent Killer of Self-Driving Cars

One of the most critical challenges in remote vehicle control is latency – the delay between sending and receiving information due to distance or poor network quality. This is a problem that the military has faced for decades, and it's one that self-driving car companies are struggling to overcome. In fact, a study by the U.S. Air Force found that teleoperation of drones with a two-second delay resulted in an accident rate 16 times higher than fighter jets conducting the same missions.

Self-driving car companies typically rely on cellphone networks to deliver commands, which are unreliable in cities and prone to delays. This is one reason many companies prefer remote assistance instead of full teleoperation. However, even remote assistance can go wrong. In one incident, a Waymo operator instructed a car to turn left when a traffic light appeared yellow in the remote video feed – but the network latency meant that the light had already turned red in the real world.

Workstation Design: The Forgotten Factor in Self-Driving Car Safety

Poor interface design has caused many drone accidents, and it's a problem that self-driving car companies are ignoring. The military learned the hard way that confusing controls, difficult-to-read displays, and unclear autonomy modes can have disastrous consequences. In fact, the FAA attributed between 20% and 100% of Army and Air Force UAV crashes caused by human error through 2004 to poor interface design.

Self-driving car companies are making similar mistakes. Some autonomous shuttles use off-the-shelf gaming controllers, which – while inexpensive – were never designed for vehicle control. The off-label use of such controllers can lead to mode confusion, which was a factor in a recent shuttle crash.

Operator Workload: The Hidden Threat to Self-Driving Car Safety

Drone missions typically include long periods of surveillance and information gathering, occasionally ending with a missile strike. These missions can sometimes last for days, and the remote operators experience extreme swings in workload – sometimes overwhelming intensity, sometimes crushing boredom. Both conditions can lead to errors.

Self-driving car operators are likely experiencing similar issues for tasks ranging from interpreting confusing signs to helping cars escape dead ends. In simple scenarios, operators may be bored; in emergencies – like driving into a flood zone or responding during a citywide power outage – they can become quickly overwhelmed.

Training: The Missing Link in Self-Driving Car Safety

Early drone programs lacked formal training requirements, with training programs designed by pilots, for pilots. Unfortunately, supervising a drone is more akin to air traffic control than actually flying an aircraft, so the military often placed drone operators in critical roles with inadequate preparation. This caused many accidents.

Self-driving companies do not publicly share their training standards, and no regulations currently govern the qualifications for remote operators. On-road safety depends heavily on these operators, yet very little is known about how they are selected or taught.

Contingency Planning: The Forgotten Safety Net

Aviation has strong protocols for emergencies, including predefined procedures for lost communication, backup ground control stations, and highly reliable onboard behaviors when autonomy fails. In the military, drones may fly themselves to safe areas or land autonomously if contact is lost. Systems are designed with cybersecurity threats – like GPS spoofing – in mind.

Self-driving cars appear far less prepared. The 2025 San Francisco power outage left Waymo vehicles frozen in traffic lanes, blocking first responders and creating hazards. These vehicles are supposed to perform “minimum-risk maneuvers” such as pulling to the side – but many of them didn’t.

The Future of Self-Driving Cars: A Lesson from Military Drone Operations

The history of military drone operations offers crucial lessons for the self-driving car industry. Decades of experience show that remote supervision demands extremely low latency, carefully designed control stations, manageable operator workload, rigorous, well-designed training programs, and strong contingency planning.

Self-driving companies appear to be repeating many of the early mistakes made in drone programs. Remote operations are treated as a support feature rather than a mission-critical safety system. But as long as AI struggles with uncertainty, which will be the case for the foreseeable future, remote human supervision will remain essential.

The military learned these lessons through painful trial and error, yet the self-driving community appears to be ignoring them. The self-driving industry has the chance – and the responsibility – to learn from our mistakes in combat settings before it harms road users everywhere.

As the self-driving car industry continues to evolve, it's essential that companies prioritize safety and reliability. By learning from the mistakes of the past and incorporating the lessons of military drone operations, we can create a safer, more reliable future for transportation.

Source: https://spectrum.ieee.org/military-drones-self-driving-cars