tragic setback

Fatal Tesla crash reported to be using self-driving system

Chinese officials told Tesla that Beijing has tentatively approved the automaker's plan to launch its “Full Self-Driving,” or FSD, software feature in the country. Photo via tesla.com

Authorities in Washington have determined that a Tesla that hit and killed a motorcyclist near Seattle in April was operating on the company's “Full Self Driving” system at the time of the crash.

Investigators from the Washington State Patrol made the discovery after downloading information from the event-data recorder on the 2022 Tesla Model S, agency spokesman Capt. Deion Glover said Tuesday.

“The investigation is still ongoing in this case,” Glover said in an email to The Associated Press. The Snohomish County Prosecutor will determine if any charges are filed in the case, he said.

Tesla CEO Elon Musk said last week that “Full Self Driving” should be able to run without human supervision by the end of this year. He has been promising a fleet of robotaxis for several years. During the company’s earnings conference call, he acknowledged that his predictions on the issue “have been overly optimistic in the past.”

A message was left Tuesday seeking comment from Texas-based Tesla.

After the crash in a suburban area about 15 miles (24 kilometers) northeast of Seattle, the driver told a trooper that he was using Tesla's Autopilot system and looked at his cellphone while the Tesla was moving.

“The next thing he knew there was a bang and the vehicle lurched forward as it accelerated and collided with the motorcycle in front of him,” the trooper wrote in a probable-cause document.

The 56-year-old driver was arrested for investigation of vehicular homicide “based on the admitted inattention to driving, while on Autopilot mode, and the distraction of the cell phone while moving forward, putting trust in the machine to drive for him,” the affidavit said.

The motorcyclist, Jeffrey Nissen, 28, of Stanwood, Washington, was under the car and pronounced dead at the scene, authorities reported.

Nissen's death is at least the second in the U.S. involving Tesla's “Full Self-Driving” system. In investigative documents, the U.S. National Highway Traffic Safety Administration said earlier it had found one fatality and 75 crashes while the system was being used. It wasn't clear whether the system was at fault in the fatality.

Tesla has two partially automated driving systems, “Full Self-Driving,” which can take on many driving tasks even on city streets, and Autopilot, which can keep a car in its lane and away from objects in front of it. Sometimes the names are confused by Tesla owners and the public.

Tesla says at present neither system can drive itself and that human drivers must be ready to take control at any time.

“Full Self-Driving” is being tested on public roads by selected Tesla owners. The company recently has been calling it FSD Supervised.

Musk said last week that he did not think approval by government regulators would be a limiting factor in deploying robotaxis. “If you’ve got billions of miles that show that in the future, unsupervised FSD is safer than humans, what regulator could really stand in the way of that?” he asked.

But Phil Koopman, a professor at Carnegie Mellon University who studies autonomous vehicle safety, said he doesn't see Tesla running robotaxis without human drivers on nearly all roads for another decade.

The safety record Musk cites is based on having a human driver supervise the automated system, he said. “Unless you have data showing that the driver never has to supervise the automation, then there's no basis for claiming they're going to be acceptably safe,” he said.

Musk has said Tesla will unveil a dedicated robotaxi vehicle at an event on Oct. 10. The event was delayed from Aug. 8 to make changes in the vehicle that Musk wanted.

Musk has been telling investors that Tesla is less of a car company and more of a robotics and artificial intelligence company. Many investors have put money into the company based on long-term prospects for robotics technology.

Musk has been touting self-driving vehicles as a growth catalyst for Tesla since “Full Self Driving” hardware went on sale late in 2015.

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A View From HETI

Merab Momen, founder of AI CTO Services. Courtesy Photo

Artificial intelligence is now everywhere. It is mentioned in every startup pitch deck, and every corporate roadmap claims to use it. However, many early-stage businesses struggle with the simple question, “What does AI actually mean for my business?”

In a recent podcast episode of EnergyTech Startups, Merab Momen, founder of AI CTO Services and a long time AI practitioner, explains why most founders misunderstand AI, how startups can practically apply it and why Houston is quietly becoming a serious hub for AI-driven innovation.

Filling the AI Leadership Gap

Merab’s career has spanned decades of technology transitions. He worked on neutral networks in the 1990s, constructed computer vision systems long before they were common, and helped install AI solutions inside huge industrial companies. However, he noticed a huge problem when generative AI started to explode into the mainstream-The requirement of a real partner by the founders for AI integration but inability to rely on a full-time CTO and project-based consultants.

“I really needed something which is much more engaging where I can give that partner-level advice to the founders,” he said. By giving firms on-demand access to high-level AI knowledge and expertise, his methodology enables them to analyse tools, steer clear of cost blunders and eventually transition to a permanent technology leader when the time is right.

AI is Older than Most People Think

Despite its recent rise in popularity, AI is nothing new. AI actually began in the 1950s. Merab in his conversation explained how he worked on his first AI project back in the year 1996 that worked perfectly, but the processing power wasn’t just there to make it practical. He continued how he utilized the swarm intelligence models to optimize supply chains, now referred to as MLPOs and data engineering.

From Language Models to Physical World

Much of the public conversation about AI revolves around chatbots and text generation. But Merab sees far greater potential in AI’s interaction with the physical world, especially in industrial settings. He emphasized edge computing and vision language models (VLMs) as significant advances in manufacturing and energy. This physical shift is opening doors for new opportunities for robotics, automated inspections, and industrial safety applications. Merab added that Houston is uniquely positioned for this transition.

Why Houston has an AI Advantage

Silicon Valley may dominate the AI headlines, but Merab believes Houston’s advantage lies beneath the surface. The city doesn’t lag in AI utilization; it just operates in industries where results show differently.

Machine learning isn’t new to Houston’s core industries. Energy companies, manufacturers, logistics providers, and healthcare systems have been using advanced analytics for decades. The difference lies in them innovating in industrial sectors rather than consumer technology.

What’s Next

With the AI CTO Services growing, Merab is working with startups across industries to deploy AI in practical, business-first ways.

He is more interested in assisting founders in finding answers to critical issues than following new trends.

For Houston’s energy and climate tech community, it needs to transform AI enthusiasm into real-world impact.

Listen to the full conversation with Mehrab Momin on the Energy Tech Startups Podcast to learn more.

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Energy Tech Startups Podcast is hosted by Jason Ethier and Nada Ahmed. It delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.


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