Safety Overview

SidewalkPilot moves a physical RC-scale vehicle. Its current safeguards reduce specific risks during supervised tests; they do not constitute certification or a complete functional-safety system.

Implemented Layers

  1. Operator control: while the Xbox controller is connected and the Raspberry Pi 5 loop is responsive, steering, gas, or brake input cancels autonomy. The Share button requests an orderly shutdown. The operator also needs an independent way to cut power.
  2. LiDAR longitudinal intervention: when AEB is enabled and fresh center- corridor returns are available, the policy can cap forward throttle and request a hard brake at 1.05 m. LiDAR never commands steering.
  3. Inference freshness: unavailable or stale model results cause the autonomous path to request a hard stop. The current neural path assigns confidence 1.0 to accepted fresh results, so the confidence field is not a calibrated detector for wrong scenes.
  4. Operating procedure: tests require line-of-sight supervision, bounded routes, dry conditions, and no autonomous public-road operation. The declared MAX_AUTONOMOUS_SPEED_MPH is not wired into a measured-speed governor and must not be described as an enforced cap.

Known Gaps

  • Stale or empty LiDAR data removes obstacle intervention rather than forcing a stop.
  • Software override depends on a connected controller and responsive process.
  • Configured LiDAR thresholds do not prove physical stopping distance.
  • No arbitrary-pedestrian, all-weather, or unattended-operation claim is made.
  • Quantitative false-trigger, disconnect, stopping-distance, and override-latency records still need controlled physical tests.

Evidence Standard

Code and unit tests establish the configured arbitration logic. Physical claims require a preserved setup, payload, speed, route, logs, video, and pass/fail record. The July 13 model comparison selected v3.4 in the cases presented, but it was not a safety certification or complete route benchmark.