This article was originally published by The IP Strategist.
Autonomous vehicle technology sits at the intersection of safety-critical engineering and intensely competitive intellectual property. Companies developing this technology must satisfy safety regulations and disclose required information to regulators and the public, while also protecting the proprietary algorithms, data pipelines, and tools that give them a competitive edge—information that those companies may seek to protect as intellectual property, including trade secrets.
This article discusses the current landscape for trade secrets as they relate to autonomous vehicles, including case law and regulations. It then examines the competing objectives of requiring autonomous vehicle companies to disclose internal information for public safety demands versus vehicle companies protecting their confidential information as trade secrets and proposes some possible solutions to resolve this tension, including vehicle companies disclosing only non-confidential information on crash testing data or regulators conducting trial testing of the autonomous vehicles before deployment to avoid public disclosures of trade secrets.
Under the federal Defend Trade Secrets Act (DTSA) and the Uniform Trade Secrets Act (UTSA) adopted by most states, a trade secret encompasses information that: a) derives independent economic value from not being generally known; and b) is subject to reasonable measures that maintain its secrecy. In the autonomous vehicle context, protected trade secret information may include source code, neural network architectures, trained model weights, training datasets, labeling taxonomies, simulation engines, hardware configurations, calibration techniques, and proprietary maps or localization strategies, all of which may derive independent economic value from not being generally known by others. That is because an autonomous vehicle company’s internal technical information, including designs and schematics, may contribute to its competitive advantage in the market over other players in the industry.
Implementing reasonable measures to maintain the information’s secrecy is likewise crucial. Reasonable measures for maintaining secrecy may include labeling sensitive documents as “confidential,” requiring non-disclosure agreements, encrypting data, segregating training data and code, maintaining access logs, and documenting disclosures to regulators or third parties under protective orders. These measures are especially important in industries like the emerging autonomous vehicle industry, where technology evolves at a fast pace and extensive testing is necessary before deployment.
One area where trade secret misappropriation issues have arisen is the employment context: when an employer accuses a former employee of using confidential information that qualifies as a trade secret. In the autonomous vehicle context, the landmark court case is Waymo LLC v. Uber Techs., Inc. filed in 2017 in the United States District Court for the Northern District of California. In this case, Waymo accused Uber of stealing Waymo’s proprietary secrets relating to its laser-based sensing (LiDAR) data through a former Waymo employee. Waymo alleged that its LiDAR technology information is entitled to trade secret protection because, at a minimum, it offers independent economic value as Waymo’s advantage in the market that was not commonly known by others, and Waymo took measures to maintain its secrecy. In essence, this LiDAR technology is what enables the driverless vehicle to sense its surrounding environment as it drives, including when to brake, accelerate, turn, and perform other maneuvers. Before trial, Waymo and Uber reached a settlement agreement valued at approximately $245 million and an agreement that Uber refrain from using the information at issue. Waymo LLC v. Uber Techs., Inc. set the stage for autonomous vehicle trade secrets by solidifying the high value of proprietary technical data in the industry, including the competitiveness between the companies in the field. Moreover, protecting trade secret information is vital to established players and new entrants alike. Recent criminal trade secret prosecutions involving mobility and autonomy technologies confirm that internal technical materials can qualify as protectable trade secrets and that misappropriation carries serious consequences. These matters underscore a broader policy commitment to safeguarding confidential engineering information while permitting responsible safety oversight, including for companies not widely known for autonomous vehicles.
While trade secrets protect competitively sensitive information, federal and state regulatory bodies aim to enforce vehicle compliance standards and promote public safety. Federal regulators have required ongoing reporting of incidents involving automated systems, and they retain authority to request additional information and to pursue recalls or other corrective actions for safety defects. For example, the National Highway Traffic Safety Administration (NHTSA) requires manufacturers to report any crashes involving autonomous vehicles and compliance with the Federal Motor Vehicle Safety Standards. In addition, according to the U.S. Department of Transportation (USDOT) and NHTSA websites, the USDOT will modernize its standards to update safety guidelines for vehicles without human drivers. Autonomous vehicle companies operate under state-level permits such as in California or Arizona that adhere to the federal framework and require more detailed steps. For instance, in California, autonomous vehicle operators are required to obtain specific permits from the Department of Motor Vehicles (DMV) for testing and deploying driverless vehicles. California also requires that autonomous vehicle companies submit passenger safety plans, obtain approval from the California Public Utilities Commission (CPUC) for initial deployment phase, report all collisions to the California DMV, enable two-way communication capabilities with a remote human operator, and several others’ mandates. These rules are designed to increase transparency for the public to be informed, and to hold the vehicle companies accountable to safety protocols.
The competing goals underlying trade secret protection, on one hand, and transparency and safety, on the other, result in a tension. Trade secret law protects companies from publicly disclosing their confidential information and, in many cases, information that gives them a competitive advantage in the marketplace. Trade secret law incentivizes companies to develop products and services knowing that they need not share that information with competitors. This protection is especially valuable in quickly developing fields with rapid technological advancement and employees that may move between companies. In these circumstances, alternatives to trade secret protection—such as filing patent applications that may take years to mature into enforceable rights—may not make sense or serve the company’s business interests.
But as regulators may point out, the legal frameworks for trade secret protection or other forms of intellectual property were not intended to jeopardize human safety. Autonomous vehicle companies therefore must demonstrate strong safety outcomes while complying with federal and state regulations before their vehicles can operate on public roads, for example. State regulations surrounding autonomous vehicles, such as California, aim to track safety-relevant information, including crash data from the testing and safety plans.
Tensions arise when the need for secrecy and transparency conflict. As one example, Waymo sued the California DMV in 2022 to refrain from publicly disclosing its alleged trade secrets, which was information included in its autonomous vehicle deployment permit to the California DMV and subject to public records requests. The California Superior Court granted Waymo’s injunction to redact specific portions of its permit application from public disclosure of its confidential operations and design information and to maintain the privacy of its trade secrets. Other potential disputes involve, for example, the weight that should be given to high-level metrics and whether companies can underreport or frame data in ways that obscure risk. In many cases, trade secret and confidential business information exemptions built into federal and state disclosure regimes lack specificity and appropriate guidelines.
It remains to be seen how the balance will be struck between allowing companies to maintain secrecy and requiring transparency for purposes of regulations—especially as autonomous vehicles continue to develop, expand into more states, and deploy on highways. One proposal is to enable regulatory bodies to conduct testing trials that satisfy the safety requirements, allow for direct review of companies’ technology and vehicles, and not require companies to publicly disclose confidential information relating to the operations or designs of their products. In other words, regulators can conduct their own trials to determine whether the outcomes are not sufficient for vehicles on the road, such as crash testing. This includes analyzing vehicle crash safety data, how the vehicle functions on the road, and whether the vehicle and its safety support systems have adequate fallback procedures in case of emergency or malfunction. These testing trials help regulators and the public evaluate safety measures without requiring vehicle companies to disclose internal implementation details that endanger trade secret protection.
Another proposal is to permit autonomous vehicle operators to submit applications only including non-confidential information. This would avoid the disclosure of trade secret information in the applications themselves, as those applications may not remain confidential and may be subject to public records requests. It would also provide regulatory bodies flexibility to comply with public records requests without confidentiality obligations. And at the same time, autonomous vehicle operators can concentrate on building better models that include improved safety measures, rather than risk sacrificing trade secrets to competitors in the market.
Autonomous vehicle technology will continue to test the boundaries between protecting high-value technology and meeting public safety demands. Trade secret law—grounded in safeguarding information that derives economic value from being kept confidential—remains a critical tool for companies seeking to preserve their competitive advantages while pushing technical boundaries. At the same time, regulators have a mandate to ensure that safety-critical systems are rigorously vetted before deployment on public roads. As this field continues to develop at an accelerated rate, finding a balance between these competing objectives, while allowing companies to navigate regulatory requirements and protect valuable intellectual property, is imperative.
Reprinted with permission from the February 2026 edition of the “The Intellectual Property Strategist” © 2026 ALM Global Properties, LLC. All rights reserved. Further duplication without permission is prohibited, contact 877-256-2472 or asset-and-logo-licensing@alm.com.