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vehicle-dynamics

Use this skill when simulating vehicle motion, calculating safe following distances, time-to-collision, speed/position updates, or implementing vehicle state machines for cruise control modes.

Install / Use

npx skills add benchflow-ai/skillsbench --skill vehicle-dynamics

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

81/100

Supported Platforms

Universal

Our assessment of vehicle-dynamics

vehicle-dynamics scores 81/100 on our quality scale, 3097th of 4,653 Development & Engineering skills we index.

Its SKILL.md is 2.2 KB long, split into 7 sections with 7 code examples: moderately detailed.

With 1,813 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
20/30
Structure
18/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so vehicle-dynamics is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

vehicle-dynamics compared with similar skills

All 4 of these similar skills score higher than vehicle-dynamics; compare them before choosing.

SkillScoreStarsUpdatedFormat
vehicle-dynamics (this skill)by benchflow-ai811.8k2mo agoSKILL.md
Agent-Reachby Panniantong10087.6k16d agoCLAUDE.md
headroomby headroomlabs-ai10074.3ktodayCLAUDE.md
ai-job-searchby MadsLorentzen10044.7ktodayCLAUDE.md
claude-howtoby luongnv8910041.7k2d agoCLAUDE.md

Frequently asked questions

How do I install vehicle-dynamics?
Run npx skills add benchflow-ai/skillsbench --skill vehicle-dynamics. The install tabs above show the steps for each supported agent.
Which AI agents does vehicle-dynamics work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is vehicle-dynamics safe to use?
It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is vehicle-dynamics still maintained?
The repository was last updated about 2 months ago, so vehicle-dynamics is actively maintained.

name: vehicle-dynamics description: Use this skill when simulating vehicle motion, calculating safe following distances, time-to-collision, speed/position updates, or implementing vehicle state machines for cruise control modes.

Vehicle Dynamics Simulation

Basic Kinematic Model

For vehicle simulations, use discrete-time kinematic equations.

Speed Update:

new_speed = current_speed + acceleration * dt
new_speed = max(0, new_speed)  # Speed cannot be negative

Position Update:

new_position = current_position + speed * dt

Distance Between Vehicles:

# When following another vehicle
relative_speed = ego_speed - lead_speed
new_distance = current_distance - relative_speed * dt

Safe Following Distance

The time headway model calculates safe following distance:

def safe_following_distance(speed, time_headway, min_distance):
    """
    Calculate safe distance based on current speed.

    Args:
        speed: Current vehicle speed (m/s)
        time_headway: Time gap to maintain (seconds)
        min_distance: Minimum distance at standstill (meters)
    """
    return speed * time_headway + min_distance

Time-to-Collision (TTC)

TTC estimates time until collision at current velocities:

def time_to_collision(distance, ego_speed, lead_speed):
    """
    Calculate time to collision.

    Returns None if not approaching (ego slower than lead).
    """
    relative_speed = ego_speed - lead_speed

    if relative_speed <= 0:
        return None  # Not approaching

    return distance / relative_speed

Acceleration Limits

Real vehicles have physical constraints:

def clamp_acceleration(accel, max_accel, max_decel):
    """Constrain acceleration to physical limits."""
    return max(max_decel, min(accel, max_accel))

State Machine Pattern

Vehicle control often uses mode-based logic:

def determine_mode(lead_present, ttc, ttc_threshold):
    """
    Determine operating mode based on conditions.

    Returns one of: 'cruise', 'follow', 'emergency'
    """
    if not lead_present:
        return 'cruise'

    if ttc is not None and ttc < ttc_threshold:
        return 'emergency'

    return 'follow'

Related Skills

View on GitHub
GitHub Stars1.8k
CategoryDevelopment
Updated2mo ago
Forks368

Languages

PDDL

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions