Self-driving cars and autonomous vehicles are no longer a thing of the future—they are next to us on the Texas roads. In Austin, parts of Houston, and Dallas, Waymo (Robotaxis) are riding Texas roads without anyone behind the wheel. Moreover, other vehicles such as Tesla are running Full Autopilot and share the same lanes as the rest of us on I-45, 290, as well as the Katy Freeway.

As an attorney and engineer however, I also take interest in what’s happening inside the processors that control these vehicles when they steer, brake, and or change lanes—and what happens, legally, when the technology controlling these vehicles gets it wrong, and someone gets seriously injured.

To provide context—in just June of this year in Katy, Texas, a Tesla (Model 3) ran off the road and crashed through the wall of a home, killing a 76-year-old woman, Martha Avila, inside her own living room. The driver stated that he activated the car’s automated driving system; however, Tesla claimed that the driver manually overrode it and pressed the accelerator to the floor—that’s, 73 mph in a residential neighborhood. The family in that case has since filed suit against both Tesla and the driver, alleging in the original petition filed June 23, 2026, Tesla’s Autopilot had been involved in at least 736 crashes since 2019—far more than any other automaker’s driver-assistance systems, and far more than previously disclosed, citing 17 fatal incidents linked to Tesla’s Autopilot feature.

In another widely covered case in a 2021 crash near Spring, Texas, two men died when a Tesla struck a tree with, investigators initially believed, no one in the driver’s seat—fueling speculation early that the autopilot had failed catastrophically. Federal investigators concluded later that the driver was behind the wheel and that autopilot was not engaged at the time. However, the reversal doesn’t mean these autonomous systems are blameless; it does bolster the presumption that these cases enlist evidence, live and die on data, e.g., event data recorders, sensor logs, and the vehicle’s own software black box—and on lawyers who know how to read it.

So, What or Who Is Actually Driving My Car

A modern autonomous or driver assisted vehicle isn’t simply one system, it’s a stack of sensors feeding data to a set of processors that vote in real time on—what the car should do next. All of that data gets fed into a processor that has to make a decision, in an instant, “is that a plastic bag or a child in the road,” and then hand its answer to another processor which decides what the vehicle does about it.

Even compared to Wikipedia’s definition of an “automobile,” none of that seems exotic anymore. Now, it’s just called driving; among hundreds of other drivers which vehicles have:

• Self-parking systems that process ultrasonic sensor data to steer into a spot without their hands being on the wheel;
• Automatic lane-centering and lane-change assist microcontrollers that read lane markings and adjacent-lane traffic and the turn the wheel automatically for them;
• Automatic emergency braking systems that interpret radar and camera data to—slam on their brakes before they’ve identified any danger;
• Adaptive cruise control systems that dynamically adjusts their following distance without their input;
• And even something as mundane as: a memory seat that repositions itself electronically when it recognizes NFC/RFID and or their key fob.

No matter how you look at it, this isn’t something that’s coming soon. It is current and actively deployed patented technology. For example:

• Google/Waymo holds the patent US 9,187,117 B2 an “Autonomous lane control system”—which covers how a vehicle’s processors decide to hold or change lanes autonomously.
• TuSimple, Inc., a California company, owns Patent US 10,953,880 B2 which covers automated lane-change control for autonomous vehicles —The logic that decides when a car is safe to merge, autonomously, and
• Google/Waymo holds US9,315,178 B1 “Model checking for autonomous vehicles”—which is a patent on the very process of “verifying” that the vehicle’s control logic behaves correctly.

The point: Vehicles are inherently dangerous. Now, they incorporate a rolling network of special-purpose computer processors; several of those processors are now allowed to steer, accelerate, and or brake without human input or control.

Why Doesn’t More Testing Fix The Problem

So, here’s the part most people never hear explained plainly. Before any of the vehicle’s control logic ships “tapes out” to customers in a production cycle, hardware and software engineers put it through extensive design verification—where they diligently exercise the hardware logic and the software to confirm every combination of inputs produces the correct, safe output. This involves expensive formal verification tools, simulation, emulation, and massive testing suites, precisely because—in a millisecond, a single undetected logic error in a microprocessor state machine, or a single missed case in the software, can propagate into real-world complications for vehicles deciding whether to brake, swerve, or simply do nothing.

However, a modern automotive processor and its software have an effectively unbounded number of possible logic combinations—e.g., a construction zone with an unusual lane-shift pattern, an e-scooter weaving unpredictably between a bike lane and traffic, a semi-truck’s trailer casting a shadow that confuses another car’s camera at dusk—these are just some of the low probability yet high risk examples that fall through cracks of even a well-run verification program.

When that missed test combination produces a failure—e.g., a lane-keeping program that doesn’t see a merging semi-truck, a braking processor that misclassifies a marathon runner, or a defective planning processor that suddenly misdirects a forklift in a work zone—the result is rarely a near-miss. It’s a multi-ton vehicle making the wrong decision at 80 mph, with a high potential to kill or seriously injure everyone in the vehicle, in other vehicles, motorcycles, e-scooter riders, and or pedestrians with essentially no warning.

In other words, this is extremely dangerous technology when defective, and the fact that it’s wrapped in erudite technical language doesn’t make it less dangerous when it fails. If anything, it makes the defects harder to identify and prove after the fact.

You Have Remedies Under Texas Law

However, Texas law actually works in your favor in these cases. Under the Texas Civil Practice and Remedies Code Chapter 82, a manufacturer or seller can be held strictly liable for a defective product — meaning you don’t have to prove that the car, truck, bus, motorcycle, e-bike or e-scooter, manufacturer or seller was careless—only that the defective product was unreasonably dangerous and that it caused your injury. Further, considering the driver-assist case, you may also have a case against the driver or other party, if they were also negligent.

An experienced injury attorney knows how to obtain the vehicle’s black-box data, software logs, and the manufacturer’s internal testing records to show who or what was actually in control when things went wrong. However, these cases however move fast in terms of evidence. Vehicle data, LiDAR and camera recordings, and software version histories can be overwritten or become difficult to obtain the longer you wait. Also, despite the immense corporate and insurance company resources arrayed against injured clients, the same injured clients attempting to prove a defect inside a black box (that they don’t control)—they move slow.

Just remember, despite who or what is the cause of your injuries, you don’t have to fight the responsible parties alone, and you don’t have to understand microprocessor architecture or verification methodology to get the compensation you deserve. Just call us at X Bennett Law. We’ll dig into the data, identify what actually failed, and we will hold all responsible parties accountable.