What problem does it solve?
Building RoadRunner driving scenarios by hand through the GUI is slow and error-prone, and programmatic authoring with roadrunnerAPI involves many subtle rules around actor placement, anchoring, routes, and phase logic that are easy to get wrong.
Core Features & Use Cases
- Actor and Route Authoring: Add vehicles, pedestrians, and props, anchor them to lanes via HD Map queries or autoAnchor, and build routes with waypoints and curve configuration.
- Phase Logic Construction: Create sequential and parallel phases with actions (ChangeSpeedAction, ChangeLaneAction, gap-keeping) and trigger conditions (distance, time, speed, collision).
- Physics-First Design and Validation: Derive speeds, gaps, and trigger timing kinematically before coding, then validate the scenario structure with validate(rrs).
- Use Case: Create a cut-in scenario where a target vehicle merges in front of a faster ego vehicle, with a distance-based trigger and verified lane-change safety margins, all generated from MATLAB code.
Quick Start
Ask your AI agent to create a RoadRunner cut-in scenario with an ego vehicle and a target vehicle on adjacent lanes using the roadrunner-scenario-authoring skill.