Entries Tagged "cars"

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Prompt Injection Via Road Signs

Interesting research: “CHAI: Command Hijacking Against Embodied AI.”

Abstract: Embodied Artificial Intelligence (AI) promises to handle edge cases in robotic vehicle systems where data is scarce by using common-sense reasoning grounded in perception and action to generalize beyond training distributions and adapt to novel real-world situations. These capabilities, however, also create new security risks. In this paper, we introduce CHAI (Command Hijacking against embodied AI), a new class of prompt-based attacks that exploit the multimodal language interpretation abilities of Large Visual-Language Models (LVLMs). CHAI embeds deceptive natural language instructions, such as misleading signs, in visual input, systematically searches the token space, builds a dictionary of prompts, and guides an attacker model to generate Visual Attack Prompts. We evaluate CHAI on four LVLM agents; drone emergency landing, autonomous driving, and aerial object tracking, and on a real robotic vehicle. Our experiments show that CHAI consistently outperforms state-of-the-art attacks. By exploiting the semantic and multimodal reasoning strengths of next-generation embodied AI systems, CHAI underscores the urgent need for defenses that extend beyond traditional adversarial robustness.

News article.

Posted on February 11, 2026 at 7:03 AMView Comments

AI vs. Human Drivers

Two competing arguments are making the rounds. The first is by a neurosurgeon in the New York Times. In an op-ed that honestly sounds like it was paid for by Waymo, the author calls driverless cars a “public health breakthrough”:

In medical research, there’s a practice of ending a study early when the results are too striking to ignore. We stop when there is unexpected harm. We also stop for overwhelming benefit, when a treatment is working so well that it would be unethical to continue giving anyone a placebo. When an intervention works this clearly, you change what you do.

There’s a public health imperative to quickly expand the adoption of autonomous vehicles. More than 39,000 Americans died in motor vehicle crashes last year, more than homicide, plane crashes and natural disasters combined. Crashes are the No. 2 cause of death for children and young adults. But death is only part of the story. These crashes are also the leading cause of spinal cord injury. We surgeons see the aftermath of the 10,000 crash victims who come to emergency rooms every day.

The other is a soon-to-be-published book: Driving Intelligence: The Green Book. The authors, a computer scientist and a management consultant with experience in the industry, make the opposite argument. Here’s one of the authors:

There is something very disturbing going on around trials with autonomous vehicles worldwide, where, sadly, there have now been many deaths and injuries both to other road users and pedestrians. Although I am well aware that there is not, senso stricto, a legal and functional parallel between a “drug trial” and “AV testing,” it seems odd to me that if a trial of a new drug had resulted in so many deaths, it would surely have been halted and major forensic investigations carried out and yet, AV manufacturers continue to test their products on public roads unabated.

I am not convinced that it is good enough to argue from statistics that, to a greater or lesser degree, fatalities and injuries would have occurred anyway had the AVs had been replaced by human-driven cars: a pharmaceutical company, following death or injury, cannot simply sidestep regulations around the trial of, say, a new cancer drug, by arguing that, whilst the trial is underway, people would die from cancer anyway….

Both arguments are compelling, and it’s going to be hard to figure out what public policy should be.

This paper, from 2016, argues that we’re going to need other metrics than side-by-side comparisons: Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?“:

Abstract: How safe are autonomous vehicles? The answer is critical for determining how autonomous vehicles may shape motor vehicle safety and public health, and for developing sound policies to govern their deployment. One proposed way to assess safety is to test drive autonomous vehicles in real traffic, observe their performance, and make statistical comparisons to human driver performance. This approach is logical, but it is practical? In this paper, we calculate the number of miles of driving that would be needed to provide clear statistical evidence of autonomous vehicle safety. Given that current traffic fatalities and injuries are rare events compared to vehicle miles traveled, we show that fully autonomous vehicles would have to be driven hundreds of millions of miles and sometimes hundreds of billions of miles to demonstrate their reliability in terms of fatalities and injuries. Under even aggressive testing assumptions, existing fleets would take tens and sometimes hundreds of years to drive these miles—­an impossible proposition if the aim is to demonstrate their performance prior to releasing them on the roads for consumer use. These findings demonstrate that developers of this technology and third-party testers cannot simply drive their way to safety. Instead, they will need to develop innovative methods of demonstrating safety and reliability. And yet, the possibility remains that it will not be possible to establish with certainty the safety of autonomous vehicles. Uncertainty will remain. Therefore, it is imperative that autonomous vehicle regulations are adaptive­—designed from the outset to evolve with the technology so that society can better harness the benefits and manage the risks of these rapidly evolving and potentially transformative technologies.

One problem, of course, is that we treat death by human driver differently than we do death by autonomous computer driver. This is likely to change as we get more experience with AI accidents—and AI-caused deaths.

Posted on December 9, 2025 at 7:07 AMView Comments

Flok License Plate Surveillance

The company Flok is surveilling us as we drive:

A retired veteran named Lee Schmidt wanted to know how often Norfolk, Virginia’s 176 Flock Safety automated license-plate-reader cameras were tracking him. The answer, according to a U.S. District Court lawsuit filed in September, was more than four times a day, or 526 times from mid-February to early July. No, there’s no warrant out for Schmidt’s arrest, nor is there a warrant for Schmidt’s co-plaintiff, Crystal Arrington, whom the system tagged 849 times in roughly the same period.

You might think this sounds like it violates the Fourth Amendment, which protects American citizens from unreasonable searches and seizures without probable cause. Well, so does the American Civil Liberties Union. Norfolk, Virginia Judge Jamilah LeCruise also agrees, and in 2024 she ruled that plate-reader data obtained without a search warrant couldn’t be used against a defendant in a robbery case.

Posted on October 8, 2025 at 12:10 PMView Comments

Hacking Digital License Plates

Not everything needs to be digital and “smart.” License plates, for example:

Josep Rodriguez, a researcher at security firm IOActive, has revealed a technique to “jailbreak” digital license plates sold by Reviver, the leading vendor of those plates in the US with 65,000 plates already sold. By removing a sticker on the back of the plate and attaching a cable to its internal connectors, he’s able to rewrite a Reviver plate’s firmware in a matter of minutes. Then, with that custom firmware installed, the jailbroken license plate can receive commands via Bluetooth from a smartphone app to instantly change its display to show any characters or image.

[…]

Because the vulnerability that allowed him to rewrite the plates’ firmware exists at the hardware level­—in Reviver’s chips themselves—Rodriguez says there’s no way for Reviver to patch the issue with a mere software update. Instead, it would have to replace those chips in each display.

The whole point of a license plate is that it can’t be modified. Why in the world would anyone think that a digital version is a good idea?

Posted on December 17, 2024 at 12:04 PMView Comments

Friday Squid Blogging: Safe Quick Undercarriage Immobilization Device

Fifteen years ago I blogged about a different SQUID. Here’s an update:

Fleeing drivers are a common problem for law enforcement. They just won’t stop unless persuaded­—persuaded by bullets, barriers, spikes, or snares. Each option is risky business. Shooting up a fugitive’s car is one possibility. But what if children or hostages are in it? Lay down barriers, and the driver might swerve into a school bus. Spike his tires, and he might fishtail into a van­—if the spikes stop him at all. Existing traps, made from elastic, may halt a Hyundai, but they’re no match for a Hummer. In addition, officers put themselves at risk of being run down while setting up the traps.

But what if an officer could lay down a road trap in seconds, then activate it from a nearby hiding place? What if—­like sea monsters of ancient lore­—the trap could reach up from below to ensnare anything from a MINI Cooper to a Ford Expedition? What if this trap were as small as a spare tire, as light as a tire jack, and cost under a grand?

Thanks to imaginative design and engineering funded by the Small Business Innovation Research (SBIR) Office of the U. S. Department of Homeland Security’s Science and Technology Directorate (S&T), such a trap may be stopping brigands by 2010. It’s called the Safe Quick Undercarriage Immobilization Device, or SQUID. When closed, the current prototype resembles a cheese wheel full of holes. When open (deployed), it becomes a mass of tentacles entangling the axles. By stopping the axles instead of the wheels, SQUID may change how fleeing drivers are, quite literally, caught.

Blog moderation policy.

Posted on December 6, 2024 at 5:05 PM

Are Automatic License Plate Scanners Constitutional?

An advocacy groups is filing a Fourth Amendment challenge against automatic license plate readers.

“The City of Norfolk, Virginia, has installed a network of cameras that make it functionally impossible for people to drive anywhere without having their movements tracked, photographed, and stored in an AI-assisted database that enables the warrantless surveillance of their every move. This civil rights lawsuit seeks to end this dragnet surveillance program,” the lawsuit notes. “In Norfolk, no one can escape the government’s 172 unblinking eyes,” it continues, referring to the 172 Flock cameras currently operational in Norfolk. The Fourth Amendment protects against unreasonable searches and seizures and has been ruled in many cases to protect against warrantless government surveillance, and the lawsuit specifically says Norfolk’s installation violates that.”

Posted on October 23, 2024 at 2:16 PMView Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.