Determining who is at fault when an autonomous vehicle (AV) crashes is one of the most complex legal and ethical questions in modern transportation. Unlike traditional crashes—where the human driver is almost always responsible—autonomous driving involves multiple actors, each potentially sharing responsibility.

As autonomous vehicles become more common, questions about responsibility and liability in the event of a crash have become increasingly important. Unlike traditional accidents, determining fault in autonomous vehicle crashes can involve multiple parties, including the driver, manufacturer, software developer, or even infrastructure providers.

The level of autonomy in use at the time of the accident plays a crucial role in assigning responsibility. Legal systems around the world are still evolving to address these complex situations. Understanding fault in autonomous vehicle crashes is essential for ensuring safety, accountability, and public trust in self-driving technology.

1. Understanding Responsibility in Autonomous Driving

Fault depends on:

Level of autonomy (SAE Level 0–5)
Whether a human driver was required to supervise
Whether the vehicle was in autonomous mode
The type of failure (sensor, software, user misuse, etc.)
Local laws (which differ by country/state)

2. Fault Based on Autonomy Level

Level 1–2 (Driver Assistance)

Examples: Tesla Autopilot, Hyundai SmartSense, Toyota TSS

Car assists with steering or speed
Driver MUST stay alert and is legally responsible

Fault:

👉 The human driver is almost always responsible
because they are required to supervise the system.

Examples:

Driver misuses Autopilot → driver at fault
Driver reacts too late → driver at fault

Manufacturers warn that these systems are not self-driving.

Level 3 (Conditional Autonomy)

Examples: Mercedes Drive Pilot (limited areas)

Car drives itself in specific conditions
Driver may take hands off
But must be ready to take control when prompted

Fault depends on mode:

➤ If the system is active and conditions are valid:

👉 Manufacturer/system provider may be at fault.

➤ If the driver failed to take over when asked:

👉 Driver may share fault.

Level 4 (High Autonomy)

Examples: Waymo, Cruise robotaxis (in geofenced zones)

No driver needed in certified areas
Human fallback may not exist

Fault:

👉 The operating company is usually at fault, not passengers.

This is similar to blaming:

Airlines for autopilot failures
Bus companies for driverless transit issues

Passengers are treated like riders, not drivers.

Level 5 (Full Autonomy)—Future

No steering wheel, no pedals, no human involvement.

Fault:

👉 Entire responsibility falls on:

Vehicle manufacturer
Software developer
Autonomous service operator
Sensor supplier (if component failure)

No human fault, unless:

A pedestrian/jaywalker caused the crash
Another (human-driven) vehicle caused the accident

3. Who Can Be Held Liable in an AV Crash?

Below is the real-world breakdown.

1. Human Driver (if supervision required)

At fault for:

Not paying attention
Misusing the system
Ignoring take-over requests
Driving outside approved conditions
Modifying car software/hardware

2. Vehicle Manufacturer

At fault for:

Defective autonomous software
Faulty AI decisions
Sensor failures (LIDAR, camera, radar)
Poor design or warnings

Examples:

Tesla has faced multiple lawsuits for Autopilot-related crashes
Volvo has said it will take responsibility for its Level 4 AVs

3. Software Developer / AI Provider

At fault when:

Mapping errors
AI misidentifies objects
Incorrect path planning
Faulty updates cause problems

For example, if the AV fails to detect a cyclist due to:

Bad perception algorithms
Outdated neural network models

4. Fleet Operator (for robotaxis)

Companies like:

Waymo
Cruise
Zoox
Baidu Apollo

They are responsible for:

Maintenance
Proper calibration
Safe operation
Updating systems

Passengers have no driving role → not liable.

5. Component Manufacturer

If a part fails:

Faulty braking system
Steering actuator failure
Sensor malfunction

The part supplier may share liability.

6. Road or Infrastructure Authority

Sometimes the government may be partly responsible if:

Road markings are missing
Traffic lights malfunction
Construction zones are not marked
GPS/map data is inaccurate

4. How Fault Is Determined in Practice?

Investigators analyze:

✔ Black box data (vehicle logs)

✔ Sensor recordings (LIDAR/CAMERA/RADAR)
✔ Software logs
✔ Human driver behavior
✔ System alerts ignored by the driver
✔ Weather or visibility conditions
✔ Whether the AV was in proper operational mode
✔ Over-the-air update history

In many countries, AVs are required to store all data before a crash.

5. Real-World Example Cases

Tesla Autopilot crashes

Courts often ruled:

Driver was at fault
because Autopilot is only Level 2 → driver must supervise.

Waymo/Cruise robotaxi incidents

Regulators held:

The companies responsible
because these are Level 4 vehicles.

Example: Cruise’s license was suspended in California after a crash.

6. Public Opinion vs. Legal Reality

Public often blames:

The car
The manufacturer
The AI

But legally, responsibility depends on autonomy level.

For Level 2 cars:
👉 usually driver’s fault

For Level 4 robotaxis:
👉 usually company’s fault

Summary

Fault in AV crashes depends on who had control:

✔ If the car requires human supervision (Level 1–2):

👉 Driver is at fault

✔ If the car drives itself but still has optional human fallback (Level 3):

👉 Shared fault between driver and manufacturer

✔ If the car is fully autonomous in a geofenced area (Level 4):

👉 Company/manufacturer is at fault

✔ If fully autonomous everywhere (Level 5):

👉 Manufacturer + software developer + system operator
No human responsibility (unless external cause).