Dynamic Urban Scenarios
Interactive Hazard Placer
🚧 Add Cone
🚶 Add Pedestrian
🚚 Add Truck
Click buttons above or click directly on track to drop live hazards into vehicle's trajectory.
Environmental Conditions
Telemetry Benchmark
Wayve Completion
TRUE
HD-Map Completion
FALSE
Avg Compute Latency
18 ms
HD-Map Interventions
2
Why Wayve's Approach Differs: Hand-coded robotics require pre-mapped HD geometries and rigid rule trees, causing failures on unmapped roadworks or unexpected hazards. Wayve's End-to-End (E2E) vision model learns end-to-end driving policies directly from camera data and foundation AI models, enabling immediate generalization to zero-shot scenarios.