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Tesla Model S on Autopilot crashes into stalled van on highway
A Tesla Model S crashes into the back of a stalled vehicle on a highway. Who is responsible, Autopilot, TACC, or the driver? Ultimately, we know the answer but not everyone wants to admit it.
A Tesla Model S on Autopilot crashed into the back of a stalled van in the high speed lane of a highway this week. The owner Chris Thomann who caught the accident through his dash cam believes it shows the Traffic Aware Cruise Control/Autopilot feature of his car malfunctioned. According to the description on Thomann’s YouTube video, he claims Autopilot and TACC have worked flawlessly many times before, but this time “The forward collision warning turned on way too late, it was set to normal warning distance”.
Updated: The original YouTube video has been marked as private so we added this animated gif via CNET showing the events of what happened.
There have been several instances lately in which Tesla drivers claim their cars malfunctioned, leading to collisions. Is there something wrong with these systems that people should be aware of?
The answer appears to be “No.” On Reddit, Tesla owner Ricodic took the time to post this language from page 69 of the Model S owner’s manual:
Warning: Traffic-Aware Cruise Control can not detect all objects and may not brake/decelerate for stationary vehicles, especially in situations when you are driving over 50 mph (80 km/h) and a vehicle you are following moves out of your driving path and a stationary vehicle or object, bicycle, or pedestrian is in front of you instead. Always pay attention to the road ahead and stay prepared to take immediate corrective action. Depending on Traffic-Aware Cruise Control to avoid a collision can result in serious injury or death. In addition, Traffic-Aware Cruise Control may react to vehicles or objects that either do not exist or are not in the lane of travel, causing Model S to slow down unnecessarily or inappropriately.
The problem is not with the software, it is with human drivers. It’s not that we don’t trust the technology; it’s that we trust it too much. We assume it means we can read the paper on the way to work or fall asleep at the wheel. We get lulled into a sense of false security by how well Autopilot and TACC work most of the time. The failure is in the human brain, which needs a moment or two to recognize that an emergency is in the making and that it is time to re-assert control over the vehicle.
Tesla owner Jarrod Overson spoke about this candidly in a post on Medium after his car suffered a collision in April. “Once I recognized the car was stopped in front of me, I explicitly remember panicking with the following thoughts going through my head: “Does my car see this? Is it going to do anything? NO. NO IT ISN’T. EMERGENCY.” In retrospect, the actions I needed to take were obvious . I should have regained control immediately. That half of a second or more probably would have made a lot of difference. The problem is that my brain wasn’t primed to have that conversation with itself. Now it is.”
Overson knew some would take him to task for his error in judgment. “I’m not looking forward to the comments calling me stupid for not doing this automatically, but I felt like it’s an important topic to be open about. I’d wager we all had a time in our lives where we didn’t know the extent of some technology, trusted it too far, and had to recalibrate after we understood the limits. Now we might just have to be a little bit luckier to get to that recalibration stage.”
It’s what autonomous driving experts refer to as “the handoff,” that brief period of time between when everything is going along serenely and when it is not. It’s when the computer suddenly finds itself in one of what Elon Musk calls a “corner case.” Those are instances that requires human input. Often, drivers have less than a second to react.
As good as Autopilot is — and it is getting better all the time — Tesla drivers still must be aware that the company and the software expect them to step in when necessary. Many put too much faith in the technology and are willing to abdicate ultimate responsibility for the operation of the car to machines.
The glowing praises we often hear from Elon make it easy to do. Perhaps Musk and Tesla could back their statements about the wonders they have created down a notch. Not everyone reads every page of the owner’s manual and even fewer commit everything found in the instructions to memory.
Elon Musk
The Boring Company just doubled its tunneling power in Nashville
The Boring Company’s Prufrock MB2 is commissioned and ready to mine beneath Nashville’s streets.
The Boring Company’s second tunnel boring machine, Prufrock MB2, is officially ready to dig in Nashville. The company confirmed the news on X, posting: “Prufrock-MB2 is ready to mine in Nashville! MB2 commissioning is complete, including the brief 11 rpm rotation shown here. Will MB2 catch up to MB1, who had quite the head start? And Prufrock-MB3 ships in August!”
MB2 arrives with meaningful improvements over its predecessor. Lessons learned from the launch and operation of MB1 have already been applied to MB2 to improve efficiency and prepare the machine for launch.
Traditional tunnel boring machines operate in a stop-and-go cycle, digging roughly five feet, halt, erect precast concrete segments to line the tunnel wall, then resume. That repeated interruption is one of the main reasons conventional tunneling is slow and expensive. Prufrock is designed to install the tunnel liner simultaneously with mining, eliminating the need to stop every five feet. The machine also skips the need for excavated launch pits. Prufrock arrives on a truck, tilts down, and launches into the ground within 24 hours. And when the tunnel is complete, it emerges from the ground and drives to its next launch site on a trailer, eliminating the need for expensive cranes or pit excavation. The machine is also fully electric and runs with zero people in the tunnel during normal operations, controlled remotely from a surface operations center.
Prufrock-MB2 is ready to mine in Nashville! MB2 commissioning is complete, including the brief 11 rpm rotation shown here.
Will MB2 catch up to MB1, who had quite the head start?
And Prufrock-MB3 ships in August! pic.twitter.com/TTrMql2aRg
— The Boring Company (@boringcompany) June 17, 2026
It won’t be long before we hear of another major update on The Boring Company’s Music City Loop project – a planned underground transit network beneath Nashville that would move passengers in electric vehicles through a series of tunnels at highway speeds, and bypassing surface traffic entirely. Nashville was selected in part because of its strong rock conditions that suits the Prufrock machines well, and relatively less regulatory hurdles.
Progress has been steady on multiple fronts. All 37 permits and approvals required ahead of tunneling have been obtained, out of 45 total. Key wins include a fully executed TDOT tunnel permit authorizing 25 miles of tunnel, unanimous airport authority approval for a Nashville International Airport station, and the city’s first residential station agreement serving downtown tower residents.
With MB1 already tunneling, MB2 now commissioned, and MB3 shipping in August, Nashville is becoming something of a live proving ground for scaled tunnel boring. The broader ambition is not limited to one city. The Boring Company’s stated goal is to make underground transportation a practical alternative to surface roads across major metro areas. Nashville is one of many cities, including a successful Las Vegas tunnel system, where that idea is being put to the test at real speed.
Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.
The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.
Tesla is sending out this email to New Jersey Tesla owners, warning them that NJ could block autonomous vehicles, and to take action.
“Proposed legislation moving through Trenton right now would impose restrictions so severe that true driverless deployment would remain illegal.… pic.twitter.com/2bmY646AUL
— Sawyer Merritt (@SawyerMerritt) June 16, 2026
According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.
Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.
The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.
In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.
Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.
In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.
Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.
Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.
This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.
As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.
Turn-by-turn navigation is not new technology.
For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.
Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.
Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.
Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.
But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.
This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.
More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.
It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?
Multiple Data Sources
First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.
Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.
Persistent Learning
FSD seems to struggle with persistent learning from driver interventions.
Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.
This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.
I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.
The next thing I’ve noticed, and this might be controversial, is that Nav has gotten even worse.
I think that might actually be a good thing; Tesla seems to be adjusting it. They just need to adjust it the opposite way.
The car is taking extremely strange routes to very… https://t.co/UHg3tVfNA2
— TESLARATI (@Teslarati) June 16, 2026
Reasoning, Scaling, and Intuition
Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.
Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.
Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.
Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.
Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.
The Boring Company just doubled its tunneling power in Nashville
Tesla urges New Jersey owners to oppose new bill that could block Robotaxi
