vehicle-dynamics

Calculate vehicle dynamics and safety metrics for autonomous driving simulations.

4|Updated Feb 22, 2026
One-click install
npx skills add https://github.com/GeneralReasoning/env-skillsbench --skill vehicle-dynamics
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vehicle-dynamics
Source: https://github.com/GeneralReasoning/env-skillsbench/tree/main/adaptive-cruise-control/environment/skills/vehicle-dynamics
Command: npx skills add https://github.com/GeneralReasoning/env-skillsbench --skill vehicle-dynamics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps simulate vehicle motion, compute safe following distances, time-to-collision, and speed/position updates, and implement vehicle state machines for cruise control modes.

Core Features & Use Cases

  • Discrete-time kinematic updates for speed and position
  • Safe following distance and TTC calculations
  • Vehicle state machine with cruise control modes (cruise, follow, emergency) and practical scenarios

Quick Start

Set up a 2-second simulation with ego at 25 m/s following a lead at 22 m/s and observe speed, position, and TTC over time.

Frequently Asked Questions about vehicle-dynamics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I simulate cruise control vehicle dynamics for autonomous driving?

You can simulate cruise control vehicle dynamics by applying discrete-time kinematic updates to calculate speed and position, using a state machine to switch between cruise, follow, and emergency driving modes.

How do I calculate time-to-collision and safe following distance in a vehicle simulation?

Calculate time-to-collision and safe following distance by tracking the relative speed and position gap between an ego vehicle and a lead vehicle during discrete-time kinematic updates in the simulation.

How does a vehicle state machine switch between cruise, follow, and emergency modes?

A vehicle state machine switches between cruise, follow, and emergency modes by evaluating real-time kinematic data, applying acceleration clamping, and updating state transitions based on distance and time-to-collision thresholds.

Can I use this simulation for car-following and lane-keeping tasks in controlled environments?

Yes, you can use this simulation for car-following and lane-keeping tasks in controlled environments by modeling discrete-time kinematic motion and applying safety metrics like distance and time-to-collision calculations.

What is the best way to implement acceleration clamping in a kinematic vehicle simulation?

The best way to implement acceleration clamping in a kinematic vehicle simulation is to apply physical limits during discrete-time speed updates, ensuring the ego vehicle transitions safely between cruise, follow, and emergency states.