November 2020
tl;dr: Google/Waymo's early efforts on traffic light mapping and detection.
The state of TFL can ONLY be perceived visually.
Maps are important. Using a prior map (that includes stop signs, speed limits, lanes), a vehicle can largely simplify its onbaord perception requirements to the estimating its position wrt the map (localization) and dealing with dynamic obstacles.
Using a map, both FP and FN are fail-safe. For FN, map indicates there should be a traffic light, and the car should take conservative actions (braking and alerting the driver). For FP (from brake taillight), the car should be braking anyway.
- Position estimation
- at least two labels in diff images are needed, and the position estimation will be more accurate if more labels are available.
- Assuming TFLs are about 0.3 m in diameter.
- TFL Semantics
- drivers need to know which lights are relevant to their current lane and to their desired trajectory through the intersections. This can be represented as an association between a TFL and the different allowed routes through an intersection.
- Some heuristics are used to label then manually verified.
- Traffic light control:
- in the path, no red/yellow lights and at least one green, then the car is allowed to proceed. Default color to yellow.
- There are almost always multiple semantically identical TFL in an intersection, it is only necessary for the system to see one of these lights to determine the TFL state.
- TFL Mapping has camera exposure set to a constant value. The image looks dark even during the day.
- For classification, insist on no FP green lights.
- Questions and notes on how to improve/revise the current work