One engine. Three product surfaces. Zero magic.
FieldSpace is a deterministic evaluative methodology mapped to the behavioral acceptance criteria framework. The same engine produces per-claim safety case evidence, counterfactual incident replay, and actuarial inputs for fleet underwriting.
Pick the wedge that fits your program
Full-stack replacement is not the first phone call. Start with the observer, prove value on your own logs, then expand only where the evidence supports it.
Validation observer
Consumes your fused tracks and ego state, emits hazard objects and a risk cost-map at 20 Hz. Runs in parallel to your planner, with no actuator authority in the default evaluation scope.
- ›Zero retraining. Works with whatever detector/tracker you already ship.
- ›Bit-identical replay of every hazard decision. Same bytes in, same bytes out.
- ›Side-by-side metrics against your stack on your own driving logs.
- ›Fastest path to standards-mapped evidence without touching production code.
Closed-loop evaluation
Route-aware trajectory generation for simulation and controlled benchmark work. Useful for nuPlan-style comparison, safety metric analysis, and failure-case review.
- ›Lane and route context for benchmark trajectory candidates.
- ›Map-aware motion prediction feeds the reactive PDE traffic field at every tick.
- ›Safety-observer outputs remain inspectable beside planner metrics.
- ›Appropriate for simulation, shadow-mode pilots, and bounded research programs.
Standards alignment without claiming premature certification.
The platform is being packaged for scoped third-party gap assessment as an observer, replay system, and possible validation-support tool-use case. Vehicle-level approval remains OEM-owned.
Review security and standards readiness →Supplier safety plan, SEooC assumptions, requirements traceability, verification evidence, and tool-confidence review.
Triggering-condition inventory, ODD assumptions, false-positive / false-negative analysis, and replayable edge cases.
Scenario taxonomy, source dataset, trigger type, ODD tags, review status, and scenario-evaluation structure.
Threat analysis, SBOM, vulnerability process, access controls, and customer-log handling readiness.
The five stages that make it deterministic
Each stage is a pure function with a typed contract. Replay the same inputs on the same binary, get the same outputs, forever.
Perception
YOLOv8n or your tracker. Class + bbox + velocity into the ego frame.
HD Map
Lanelet2 graph localization, route planner, ODD polygon gate.
Prediction
Map-aware constant-velocity + Frenet projection, 1.5 s horizon, confidence half-life.
PDE Field
Traffic density field on a 256×64 grid. Continuity + velocity + potential.
Output
Observer warnings or bounded trajectory candidates, depending on evaluation mode.
A planner-friendly output, not a black box
The validation observer emits a strict schema your existing planner can consume as an extra constraint layer. Every hazard has a TTC, a risk score, a position, and a trigger reason you can trace back to the source pixel or track.
- ›Reference ROS 2, gRPC, or UDP bindings are available for pilot integration review.
- ›Cost-map compatible with occupancy-grid planners out of the box.
- ›Deterministic replay: bring your MCAP, get the same hazards every run.
{
"t_s": 1734567890.251,
"frame_id": 4821,
"hazards": [
{
"id": "h_001",
"source_track": 17,
"kind": "moving_vehicle",
"risk": 0.82,
"ttc_s": 2.3,
"pos_ego_m": [12.5, -3.2],
"vel_ego_m_s": [5.0, 0.5],
"trigger": "predicted_path_intersects_ego"
}
],
"cost_map": {
"nx": 256, "ny": 64,
"dx_m": 0.2, "dy_m": 0.625,
"encoding": "u8_base64"
},
"mrm_phase": "Idle"
}What it needs, what it runs on
No training cluster is required for the observer path. A commodity CPU and scene state are enough to start replaying logs.
- Ego pose (x, y, heading)
- Ego velocity (longitudinal + lateral)
- Fused object tracks or benchmark scene state
- Wall-clock timestamp
- Optional lane / route context for richer closed-loop evaluation
- BenchRaspberry Pi 5
- Devx86 laptop, 4c/8t
- SimulationJetson Orin / i7
- RAM≥ 2 GB
- GPUoptional
- ROS 2 (Humble, Jazzy)
- gRPC with protobuf contracts
- Simulation and replay interfaces by pilot scope
- MCAP + comma openpilot rlog replay
- Argoverse 2 · nuScenes · Waymo · nuPlan adapters
- CARLA 0.9.14 · NHTSA 37 · Euro NCAP batteries
Bring your logs. Get your numbers.
We run the validation observer against agreed logs or benchmark scenes and send back a side-by-side evidence report your technical team can challenge.