Michael Pines | November 12, 2026 | Personal Injury \ Truck Accidents
For decades, investigating a serious semi-truck accident has often started with the person behind the wheel.
Was the truck driver fatigued? Were they speeding? Were they distracted? Did the trucking company pressure them to exceed safe driving hours? Was the truck properly inspected and maintained?
Autonomous long-haul trucks could fundamentally change that investigation.
As automated driving systems take on more of the driving task, an accident may have less to do with whether a human driver looked away from the road and more to do with questions such as:
What did the truck’s sensors detect? What did the software decide? Was the vehicle operating within the conditions it was designed to handle? Had its safety-critical software been updated? Were its cameras and sensors properly calibrated? Did a remote operator receive an alert?
The technology is no longer purely theoretical. Autonomous freight operations are already taking place on selected U.S. routes. In May 2026, for example, Volvo Autonomous Solutions and DSV announced autonomous freight operations between Dallas and Houston using a Volvo VNL Autonomous equipped with the Aurora Driver.
California is moving in the same direction. On April 28, 2026, the California Department of Motor Vehicles adopted regulations allowing manufacturers to apply for permits to test and eventually deploy heavy-duty autonomous commercial vehicles on California roads.
As autonomous semis become part of the nation’s freight system, serious crashes will still require someone to answer a familiar question:
Who was responsible for the harm?
The answer, however, may become considerably more complicated.
Quick Highlights
- Autonomous trucking does not eliminate personal injury liability. It may shift more attention from traditional driver negligence toward vehicle design, software, sensors, maintenance, fleet operations, remote supervision, and product defects.
- California adopted new regulations in April 2026 allowing manufacturers to seek permits for heavy-duty autonomous vehicle testing and deployment.
- Potential defendants after an autonomous truck crash could include the fleet operator, truck manufacturer, automated-driving-system developer, component suppliers, maintenance providers, cargo-loading companies, or a human or remote operator, depending on what caused the collision.
- Human negligence may remain important during the transition to greater automation, particularly when a safety driver or remote operator is responsible for monitoring the system or taking control.
- Autonomous trucks can generate extensive digital evidence, including camera footage, radar and LiDAR information, system-status logs, software versions, braking commands, localization information, and remote-operator communications.
- Preserving that electronic evidence quickly can be critical because determining fault may depend on reconstructing what the automated system detected and how it responded.
- Proprietary technology is not necessarily immune from litigation simply because a company considers it a trade secret. Discovery disputes may require courts to balance legitimate confidentiality concerns against an injured person’s need for relevant evidence.
- Federal and state rules governing autonomous vehicles continue to evolve. There is not one comprehensive federal civil-liability law that automatically determines who pays whenever an autonomous truck crashes.
- Insurance may increasingly involve a combination of commercial auto, product liability, professional liability, and cyber coverage rather than focusing almost exclusively on a human truck driver’s liability.
Autonomous Trucking Is Moving from Testing Toward Real-World Freight Operations
The term “autonomous truck” can describe vehicles with very different capabilities.
Some trucks use advanced driver-assistance systems while requiring a human driver to continuously monitor the road. Others are being developed to perform the entire driving task within a specific operational design domain, or ODD.
An ODD defines the circumstances in which an automated driving system is designed to operate. Those limits might involve:
- Specific highways
- Defined geographic routes
- Maximum speeds
- Weather conditions
- Road types
- Lighting conditions
- Construction conditions
- Terminal-to-terminal routes
A Level 4 autonomous truck, for example, might be capable of driving itself on a particular interstate corridor under specified conditions but not be designed to navigate every neighborhood street, snowstorm, construction detour, or unusual roadway situation.
That distinction matters greatly after an accident.
Instead of asking only whether a truck driver made a mistake, investigators may need to determine whether the truck was operating somewhere – or under conditions – the automated system should never have been operating in the first place.
California Opened the Door to Heavy-Duty Autonomous Trucks in 2026
California’s regulatory landscape changed significantly in 2026.
On April 28, the California DMV announced adoption of new autonomous vehicle regulations that removed the prior prohibition against autonomous vehicles with a gross vehicle weight rating of 10,001 pounds or more.
Manufacturers may now seek permits to test and deploy heavy-duty autonomous freight vehicles in California.
That does not mean a manufacturer can simply place an untested driverless semi on I-5 tomorrow.
The regulations establish a staged process.
For heavy-duty autonomous commercial vehicles, manufacturers must accumulate substantial testing mileage before progressing from testing with a driver to driverless testing and, eventually, deployment. California’s adopted regulatory text requires 500,000 autonomous miles under a drivered testing permit and another 500,000 miles under a driverless testing permit as part of the requirements for heavy-duty deployment.
The regulations also require manufacturers to prepare a structured safety case addressing the vehicle’s hardware, software, and operations. California’s rules include reporting requirements concerning system failures, hard-braking events, immobilizations, collisions, and vehicle miles traveled.
For personal injury attorneys, those requirements potentially create additional sources of evidence when investigating a serious autonomous vehicle accident.
How Does Autonomous Trucking Change the Question of Fault?
Traditional truck accident litigation frequently focuses on several familiar parties.
A driver may be negligent for speeding, distracted driving, fatigue, impairment, unsafe lane changes, or following too closely.
A motor carrier may face questions concerning:
- Hiring
- Training
- Supervision
- Hours-of-service compliance
- Maintenance
- Vehicle inspections
- Cargo practices
Autonomous trucking adds another layer.
Instead of one relatively straightforward chain between the driver and trucking company, an accident could involve numerous companies responsible for different components of the vehicle’s operation.
The investigation becomes less about asking “What did the truck driver do?” and more about asking:
“Which person, company, component, or system caused the truck to behave the way it did?”
The Fleet Operator May Still Be Responsible
Removing the human driver does not remove the trucking company’s responsibility to operate commercial vehicles safely.
The Federal Motor Carrier Safety Administration has emphasized that both autonomous commercial vehicles and the motor carriers responsible for operating them remain subject to federal safety oversight. FMCSA has specifically identified inspection, maintenance, loading, operational limitations, and safety-critical software as important considerations for autonomous commercial fleets.
A fleet operator could potentially face liability if it:
- Failed to maintain cameras, radar, LiDAR, or other sensors
- Ignored sensor-calibration requirements
- Failed to install required safety-critical software updates
- Continued operating a truck despite known system warnings
- Dispatched the truck outside its approved ODD
- Operated during weather the system was not designed to handle
- Failed to maintain brakes, tires, steering, or other conventional truck components
- Improperly loaded or secured cargo
- Ignored known cybersecurity vulnerabilities
- Failed to properly monitor autonomous operations
- Failed to respond appropriately to repeated system failures
Autonomous technology therefore does not make fleet maintenance less important.
It may actually make maintenance more technically complex.
A traditional truck may be unsafe because its brake pads are worn. An autonomous truck might be unsafe because a camera is obstructed, a LiDAR sensor is misaligned, a software update failed, or a localization system is operating with outdated information.
Vehicle Manufacturers Could Face Product Liability Questions
Some autonomous truck crashes may raise product liability issues.
California recognizes product liability claims involving manufacturing defects, design defects, and inadequate warnings.
Consider a scenario in which an autonomous truck approaches stopped traffic.
The cameras recognize the vehicles, but a defective braking component fails to activate despite the system issuing the correct command.
That could lead investigators toward the manufacturer or supplier of the defective hardware.
A different case might involve an automated braking system that consistently fails to recognize certain roadway conditions.
That could raise questions about the design of the system itself.
Potentially relevant components could include:
- Automated braking systems
- Steering systems
- Radar units
- LiDAR sensors
- Cameras
- GPS hardware
- Vehicle control modules
- Computing hardware
- Electrical systems
- Communication systems
- Trailer interfaces
Determining whether a defect legally caused the accident would generally require technical investigation and often expert analysis.
What About the Company That Developed the Software?
Software creates one of the more complicated legal questions surrounding autonomous trucks.
The automated driving system may combine:
- Perception software
- Object detection
- Machine-learning models
- Mapping
- Localization
- Route planning
- Predictive modeling
- Motion planning
- Vehicle-control software
Imagine a truck’s sensors correctly identify a motorcycle in the adjacent lane, but the automated system incorrectly predicts the motorcycle’s trajectory and changes lanes anyway.
Investigators may need to examine whether the problem involved:
- Defective software
- An inadequate algorithm
- Bad sensor fusion
- Incorrect mapping information
- A system integration failure
- An inappropriate software update
- Failure to properly validate a new software release
- A hardware limitation
- Some combination of these factors
Whether a particular software-related failure supports a strict product liability claim, negligence claim, or another legal theory can depend on the facts and how the technology was designed, supplied, and integrated into the truck.
The important point is that software developers may become part of an investigation that historically would have focused primarily on the truck driver and carrier.
Component Suppliers Could Also Matter
Modern autonomous trucks are unlikely to be created entirely by one company.
A truck manufacturer may build the vehicle while another company develops its automated driving platform. Separate suppliers might manufacture cameras, radar equipment, LiDAR units, processors, braking systems, steering components, or communication hardware.
That means the chain of potential responsibility can become complicated.
An investigation may need to determine whether the failure occurred in:
the truck → the autonomous-driving platform → a sensor → software → a supplier’s component → fleet maintenance → or the way those systems interacted.
Several parties may share responsibility.
Human Safety Drivers Have Not Disappeared From the Equation
Autonomous trucking is developing in stages.
During testing and transitional operations, some trucks may still have a trained safety driver behind the wheel.
In those circumstances, fault may involve both automation and human conduct.
For example, investigators could ask:
- Was the safety driver required to monitor the roadway continuously?
- Did the system issue a takeover request?
- How much time did the driver have to respond?
- Was the driver distracted?
- Did the driver recognize a malfunction?
- Should the driver have intervened earlier?
- Did the automated system give adequate warning that intervention was necessary?
The fact that automated technology was engaged does not necessarily eliminate a human operator’s duties.
NHTSA distinguishes full automated driving systems from Level 2 driver-assistance systems. Level 2 technology can provide both steering and speed assistance, but the human driver remains responsible for continuously monitoring the driving environment.
Determining exactly which level of automation was active at the time of a crash can therefore be an important early question.
Remote Operators Create Another Potential Layer of Liability
An autonomous truck may not necessarily operate without human involvement simply because nobody is sitting in the cab.
Some systems use remote personnel who can monitor vehicles, provide assistance, or potentially control certain functions.
California’s new regulations specifically establish standards for remote operations personnel, including licensing, permitting, and training requirements.
If remote supervision played a role in an accident, attorneys might investigate:
- Whether an alert was transmitted
- When the remote operator received it
- How quickly the operator responded
- How many vehicles the operator was monitoring
- What information was displayed
- Whether communications failed
- Whether the operator was properly trained
- Whether the operator gave an unsafe command
- Whether the system allowed adequate time for intervention
The “driver” in tomorrow’s truck accident case may therefore be hundreds of miles from the crash scene.
Improper Cargo Loading Could Still Cause Autonomous Truck Accidents
Automation does not repeal the laws of physics.
A tractor-trailer can still become unstable when cargo is overloaded, improperly distributed, or insufficiently secured.
If freight shifts during a turn, the truck’s center of gravity can change dramatically. An improperly loaded trailer could contribute to a rollover or make the vehicle harder to control during emergency braking.
An automated driving system might make mathematically correct decisions based on expected vehicle characteristics while the actual truck behaves differently because its cargo was improperly loaded.
Liability could potentially involve:
- The motor carrier
- Shipper
- Loading company
- Warehouse
- Maintenance contractor
- Other parties responsible for the load
Autonomous technology may change how the truck responds, but traditional trucking safety issues will remain relevant.
What Happens if an Autonomous Truck Is Hacked?
Cybersecurity introduces another potential source of risk.
Autonomous vehicles depend heavily on electronic systems and communications. Depending on the architecture, vulnerabilities could potentially affect software updates, remote communications, navigation, sensors, fleet-management platforms, or vehicle-control systems.
A cyber incident could create difficult causation questions.
Was the vulnerability known?
Was a security patch available?
Did the fleet operator fail to install it?
Did the manufacturer inadequately protect a safety-critical system?
Did an outside criminal actor intentionally interfere with the truck?
Those questions could involve cybersecurity experts in addition to accident reconstructionists and automotive engineers.
The insurance implications are also significant. Deloitte has noted that autonomous trucking could shift exposures across commercial auto insurance, product liability, professional liability, and cyber coverage as software and technology become increasingly responsible for vehicle operation.
The Most Important Witness May Be the Truck’s Data
One of the biggest changes autonomous trucking could bring to personal injury litigation is the amount of electronic evidence generated before an accident.
Today’s conventional commercial truck case may already involve:
- Electronic logging devices
- Engine-control modules
- GPS records
- Dashcams
- Telematics
- Dispatch records
An autonomous truck can potentially generate far more information.
Depending on the system, relevant data might include:
- Forward-facing camera footage
- Side and rear camera footage
- Radar returns
- LiDAR information
- Vehicle speed
- Steering commands
- Braking commands
- Acceleration
- Object classifications
- Lane detection
- Following distance
- Vehicle location
- System warnings
- Automated-driving-system status
- Software version
- Recent software updates
- Hardware errors
- Remote-operator communications
- System fallback events
- Cybersecurity logs
- Vehicle diagnostic data
NHTSA notes that automated-driving systems generally have sophisticated sensing, recording, and telemetry capabilities, allowing manufacturers or operators to obtain detailed information about crashes relatively quickly.
That data could fundamentally change accident reconstruction.
The “Black Box” May Reveal What the Automated System Detected
People sometimes describe autonomous vehicle data as a “black box.”
That comparison is useful, but the reality can be considerably more complicated.
There may not be one single device containing everything necessary to reconstruct the crash. Evidence may instead be distributed among:
- The truck
- Onboard computing systems
- Cloud servers
- Fleet-management software
- The ADS developer
- The vehicle manufacturer
- Component suppliers
- Remote-operation centers
The data could potentially help investigators answer questions such as:
Did the truck detect the stopped vehicle ahead?
When did it classify the object as a hazard?
Did the automated system command braking?
Did the brakes respond?
Was the truck inside its approved operational design domain?
Did a sensor fail?
Was an error message generated?
Did a remote operator intervene?
Electronic records do not necessarily provide a simple or uncontested answer. The parties may disagree over what the data means, whether information is complete, or how a particular system functioned.
Experts may therefore be needed to interpret it.
Digital Evidence Can Disappear
The existence of extensive data does not mean it will remain available forever.
Different systems may have different retention practices. Some information may be overwritten as new data is created. Vehicles may be repaired, software may be updated, damaged components may be replaced, and cloud records may be subject to routine retention policies.
A serious autonomous truck crash may therefore require rapid evidence preservation.
An attorney may seek to preserve:
- The truck itself
- The trailer
- ADS hardware
- Sensors and cameras
- Onboard computers
- Event and telemetry data
- Software versions
- Update histories
- Raw sensor information
- Video
- Remote-operation logs
- Fleet communications
- Maintenance records
- Cybersecurity records
Preservation letters, formal discovery, subpoenas, inspections, and court orders may become appropriate depending on the case and the entities holding the information.
It would not necessarily be accurate to describe these as “federal subpoenas.” A personal injury attorney would generally use the discovery and subpoena procedures applicable to the particular lawsuit and jurisdiction.
What if a Tech Company Says the Data Is a Trade Secret?
This could become one of the major litigation battles surrounding autonomous vehicles.
The information needed to understand why an automated system made a particular decision may include proprietary software architecture, technical documentation, algorithms, testing information, or other confidential business information.
California Evidence Code § 1060 recognizes a trade-secret privilege, but the privilege is not unlimited; the statute expressly conditions it on disclosure not being necessary to prevent fraud or injustice.
That does not mean an injured plaintiff automatically receives a technology company’s source code or every proprietary record.
Courts can be asked to balance legitimate confidentiality interests against the need for relevant evidence, and protective orders may restrict how sensitive material is reviewed or disclosed.
The practical issue is significant:
A manufacturer should not necessarily be able to make an autonomous driving decision central to the case and then make meaningful investigation impossible simply by labeling every relevant record proprietary.
NHTSA Is Already Requiring Certain Automated-Vehicle Crash Reports
Federal regulators are also collecting information about crashes involving automated driving technology.
NHTSA’s Standing General Order requires certain manufacturers and operators to report qualifying crashes when an automated driving system was in use within 30 seconds before the collision.
For ADS-equipped vehicles, reportable events include crashes resulting in specified property damage or outcomes such as a fatality, a vulnerable road user being struck, airbag deployment, towing, or transportation to a hospital.
NHTSA uses those reports to evaluate potential safety defects and determine whether investigation or enforcement is warranted.
For a personal injury case, however, a government crash report is not necessarily a substitute for obtaining the underlying vehicle and system data.
There Is No Single Nationwide Rule for Autonomous Truck Liability
Autonomous trucking sits at the intersection of federal regulation and state law.
NHTSA regulates motor vehicle safety and retains defect and recall authority over automated vehicle technology. FMCSA regulates the safety of commercial motor carriers and commercial vehicle operations in interstate commerce.
States also regulate autonomous vehicle testing and operation.
California, for example, has developed its own detailed permitting system for autonomous vehicles and heavy-duty commercial AV operations.
But there is no single federal statute that simply says:
“When an autonomous truck crashes, Party X is automatically liable.”
Personal injury cases can therefore continue to involve state negligence law, product liability doctrines, comparative fault, agency principles, and other established legal rules applied to rapidly changing technology.
What Is a “Reasonable” Autonomous Driver?
One of the more interesting questions is whether courts will eventually develop a distinct legal standard for automated driving systems.
Suppose an autonomous truck obeys the speed limit, stays within its lane, and follows every formal traffic rule – but fails to anticipate something an experienced human truck driver might recognize.
Imagine debris begins falling from a vehicle several hundred feet ahead.
A human driver might recognize the developing danger from subtle movement and begin slowing early.
The autonomous system may not classify the debris as dangerous until several seconds later.
Who is at fault?
Rather than literally placing the “AI” on trial as if it were a person, litigation may focus on the humans and companies responsible for creating, validating, deploying, maintaining, and operating the system.
For a design-defect claim under California law, for example, relevant questions can include whether the design caused the injury and whether the benefits of that design outweigh its risks. California’s product liability instructions identify considerations such as the gravity and likelihood of harm and the feasibility, cost, and disadvantages of a safer alternative design.
Autonomous vehicle cases may eventually test how traditional legal doctrines apply to decisions made by complex software.
Insurance Could Change Along with Liability
Traditional trucking insurance is heavily focused on commercial auto liability.
Autonomous trucks may redistribute some of that risk.
A collision caused by speeding or driver fatigue fits naturally into traditional commercial vehicle liability.
A collision caused by faulty perception software may look different.
So might one caused by:
- Defective LiDAR hardware
- A failed software update
- Cyber intrusion
- Remote-operation negligence
- Cloud-service failure
- Defective automated braking
Deloitte has predicted that growth in autonomous trucking could shift insurance exposure among commercial auto, product liability, professional liability, and cyber insurance.
For an injured person, that could mean several sophisticated insurers dispute which policy – or which company – ultimately bears responsibility.
That may make some autonomous truck claims more complex rather than less.
Autonomous Trucks Could Eliminate Some Risks While Creating Others
The potential safety benefits of autonomous trucking should not be overlooked.
Human truck drivers can become:
- Fatigued
- Distracted
- Impaired
- Angry
- Impatient
- Inattentive
Software does not fall asleep after a long shift or look down to answer a text message.
Autonomous technology may therefore eventually prevent many crashes associated with human error.
But removing one category of risk does not eliminate risk altogether.
Autonomous vehicles introduce different potential failure points:
- Sensor failures
- Software defects
- Inadequate object recognition
- Mapping errors
- Localization problems
- Communication failures
- Cyberattacks
- Poorly designed fallback procedures
- Maintenance failures
- Operating outside an approved ODD
The legal system’s challenge will be identifying which failure actually caused a particular crash.
What Evidence Should Be Investigated After an Autonomous Truck Crash?
A serious autonomous truck collision may require preserving both traditional trucking evidence and entirely new categories of electronic information.
Potential evidence could include:
- Police reports
- 911 calls and dispatch records
- Witness statements
- Dashcam video
- Nearby surveillance footage
- Vehicle event data
- Automated-driving-system logs
- Raw camera, radar, or LiDAR data
- System alerts
- Object-detection records
- Braking and steering commands
- Software versions
- Software update histories
- Remote-operator logs and communications
- Fleet dispatch information
- GPS and localization records
- Operational design domain documentation
- Maintenance and sensor-calibration records
- Cybersecurity records
- Cargo and weight information
- Inspection records
- Vehicle damage
- Physical ADS hardware
The truck itself can also be crucial evidence.
Repairing or altering damaged sensors and computers before they can be inspected may eliminate information needed to determine why the system behaved as it did.
Autonomous Truck Cases May Require a Different Team of Experts
Traditional trucking cases may involve accident reconstructionists, mechanics, medical specialists, or commercial trucking experts.
Autonomous vehicle cases could require additional specialists, including:
- Software engineers
- Robotics specialists
- Artificial intelligence experts
- Automotive engineers
- Electrical engineers
- Sensor specialists
- Cybersecurity professionals
- Human-factors experts
- Digital forensic analysts
- Commercial trucking experts
The challenge will often be translating enormous quantities of technical information into a relatively straightforward question:
Why did this truck crash?
What Autonomous Trucking Could Mean for San Diego Drivers
California’s 2026 regulations make autonomous heavy-duty trucking increasingly relevant throughout the state.
Long-haul freight routes connecting Southern California could eventually place autonomous semis on corridors such as I-5, I-8, I-15, and other highways traveled by San Diego motorists.
The technology may ultimately reduce some forms of human-caused truck accidents.
But when an autonomous truck does cause a serious collision, injured motorists may face a very different investigation than they would after a traditional tractor-trailer crash.
Instead of one truck driver and one trucking company, the evidence could lead to:
the carrier, truck manufacturer, ADS developer, software provider, component supplier, remote operator, maintenance contractor, cargo company – or several of them at once.
That makes early investigation especially important.
Injured in an Autonomous or Commercial Truck Accident in San Diego?
The technology controlling commercial trucks may change, but people injured in crashes will still need answers.
When an autonomous or highly automated commercial vehicle is involved, determining what happened may require much more than reviewing the police report.
Attorneys may need to preserve the truck, obtain electronic data, analyze automated-driving-system logs, determine which software was operating, investigate sensor and maintenance records, identify remote operators, examine the vehicle’s operational design domain, and determine which companies controlled each part of the system.
At Pines Salomon Personal Injury Lawyers, our San Diego truck accident injury attorneys investigate serious truck and commercial vehicle accidents and pursue compensation from responsible parties when negligence or defective products cause injuries.
If you or a loved one was seriously injured in a truck accident in San Diego or elsewhere in Southern California, contact Pines Salomon Personal Injury Lawyers for a free consultation to discuss your legal options.
As autonomous trucks become more sophisticated, personal injury cases may become more technologically complex – but the central question will remain the same:
What caused the crash, and who should be held responsible for the harm that followed?
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