IdeaWell

Project ideas from Hacker News discussions.

A Tesla ran a stop sign and killed a man, Full Self-Driving/Autopilot was on

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

Three prevalent themes in the discussion

1. Lack of transparency / Tesla’s ability to redact safety data

Many commenters criticize Tesla (and automakers in general) for being allowed to withhold details such as software version or whether FSD vs. Autopilot was active, citing “confidential business information” as a loophole.

  • “The redactions have the note: ‘[REDACTED, MAY CONTAIN CONFIDENTIAL BUSINESS INFORMATION]’ … Tesla has chosen to provide as little information as possible, claiming business secrecy, and no one can compel them otherwise.” – jerlam
  • “I would like to know why Tesla (or any automaker) is allowed to redact this information.” – lotsofpulp
  • “Most US regulatory agencies give businesses broad latitude to self‑redact their trade secrets in public filings, because otherwise they would have to take time away from their regulatory mission …” – SpicyLemonZest

2. Safety comparison – autonomous vs. human drivers (statistics, whataboutism, risk trade‑offs)

A large share of the debate centers on whether self‑driving systems are “safer on average” and how that should weigh against occasional fatal crashes, with arguments about what constitutes a fair comparison.

  • “Self driving is safer than human driving, why should we apply urgent attention to AI driver safety. Human drivers are killing hundreds of people daily.” – Footnote7341
  • “American drivers kill ~100 people every day … If autonomy were 50% safer … it would save 25 lives every day. It would also kill 25 people every day.” – marcusverus
  • “It’s not whataboutism when you’re comparing the exact same actions …” – wat10000 (countering the what‑about‑ism charge)
  • “Personally I think that fully autonomous vehicles need to be at minimum 100x safer than humans in order to maintain a social license to operate.” – simondotau

3. Accountability, liability, and justice – who is responsible when a crash occurs?

Commenters repeatedly point out that human drivers can be prosecuted, jailed, or lose their licenses, whereas autonomous systems lack clear legal liability or punishment mechanisms, raising concerns about justice and enforcement.

  • “In California the charge can be anything from vehicular manslaughter to second degree murder … In comparison self‑driving systems do not have any punishment mechanism in the penal code. There is not even a well‑established liability standard …” – manquer
  • “No, because you can punish bad drivers, remove them from the driving pool, put them in jail … There is no way for FSD to have any accountability, and so no justice can be served.” – saulpw
  • “‘Who to blame’ turns out to be one of the most important facets of humanity, and it turns out we structure our entire society around it: assigning liability and pursuing justice.” – datsci_est_2015
  • “If you want to use supervised FSD, that’s fine, but every collision gets automatically uploaded to a repository that is searchable by law enforcement and insurance companies.” – simondotau (suggesting a technical remedy)

🚀 Project Ideas

[Aftermarket Autonomous Vehicle Event Data Recorder]

Summary

  • An aftermarket hardware logger that plugs into a vehicle’s CAN/OBD-II interface to capture timestamped sensor data, software version, and autopilot/FSD state for later analysis.
  • Core value proposition: Provides owners, researchers, and regulators with tamper‑resistant telemetry to verify what the car was actually doing during an incident, addressing the current lack of transparent software‑version reporting.

Details

Key Value
Target Audience Tesla/other AV owners, safety researchers, insurance companies, regulatory agencies
Core Feature Real‑time logging of CAN bus messages, GPS, vehicle speed, steering, brake, and software version (via OBD‑II or manufacturer API) with encrypted local storage and optional secure upload
Tech Stack ESP32 or Raspberry Pi Pico W (C/Rust), CAN transceiver, microSD card, TLS‑enabled MQTT/HTTPS to cloud, optional IPFS pinning
Difficulty High
Monetization Revenue-ready: hardware sales ($149) + optional $9/mo cloud storage & analytics subscription

Notes

  • HN commenters repeatedly asked “Why doesn’t Tesla report the version and whether it was FSD or Autopilot?” and lamented redacted reports; a verifiable logger would give the data they want.
  • Could become a reference tool for NHTSA investigations and for independent safety studies, sparking discussion on data transparency in autonomous driving.

[Autonomous Incident Transparency Portal]

Summary

  • A web platform that aggregates NHTSA crash reports, FOIA requests, and crowdsourced submissions to create a searchable, version‑aware database of AV incidents, highlighting missing or redacted fields.
  • Core value proposition: Gives journalists, regulators, and the public a clear view of which software versions are implicated in crashes, countering the current opacity and enabling data‑driven advocacy.

Details

Key Value
Target Audience Journalists, safety advocates, regulators, researchers
Core Feature Searchable interface with filters for date, location, software version (FSD/Autopilot/None), injury severity; visualizations of trends; ability to submit FOIA requests and upload redacted documents for community redaction‑removal efforts
Tech Stack Python/Django backend, PostgreSQL + Elasticsearch for search, React/TypeScript frontend, AWS S3 for document storage, optional GPT‑assisted entity extraction
Difficulty Medium
Monetization Revenue-ready: premium API access for enterprises ($199/mo) + grant funding for public‑good tier

Notes

  • Commenters highlighted Tesla’s redactions (“[REDACTED, MAY CONTAIN CONFIDENTIAL BUSINESS INFORMATION]”) and asked why companies can withhold version info; this portal would surface those gaps and apply community pressure for disclosure.
  • Enables fact‑checking of claims like “FSD is already massively safer than human drivers” by providing actual incident counts per version.

[Verifiable AV Log Service for Legal & Insurance Use]

Summary

  • A service that pulls a vehicle’s operational logs (via official APIs where available) or from a user‑installed logger, cryptographically signs the data, and stores a tamper‑proof proof on a blockchain or IPFS, producing a certificate that can be presented in court or to insurers.
  • Core value proposition: Provides objective, verifiable evidence of what software version and driver‑assist state were active at the time of an incident, addressing the accountability gap noted in the discussion.

Details

Key Value
Target Audience Tesla owners, insurance adjusters, lawyers, fleet operators
Core Feature One‑click retrieval of logs (software version, autopilot engagement, speed, braking), generation of a signed JSON‑Web‑Token + hash stored on IPFS/Filecoin, downloadable PDF certificate with verification URL
Tech Stack Node.js/TypeScript, Tesla Owner API (or generic OBD‑II logger SDK), Ethereum L2 or Filecoin for storage, QR‑code verification UI
Difficulty Medium
Monetization Revenue-ready: $19 per verification report; subscription fleet plan $149/mo for unlimited reports

Notes

  • Several users complained that “there is no way for FSD to have any accountability” and that “we can’t punish bad drivers” but autonomous systems lack liability mechanisms; this service creates a credible evidence trail.
  • Would be welcomed by commenters seeking a “Flight Data Recorder”‑style solution for self‑driving cars, giving them a practical tool to close the accountability loop.

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