Agent Skillsbenchflow-ai/skillsbench › vehicle-dynamics

vehicle-dynamics

GitHub

用于车辆运动仿真,涵盖基础运动学更新、安全跟车距离计算、碰撞时间(TTC)估算及加速度物理约束。支持基于状态的巡航控制模式逻辑实现。

tasks/adaptive-cruise-control/environment/skills/vehicle-dynamics/SKILL.md benchflow-ai/skillsbench

Trigger Scenarios

模拟车辆运动轨迹 计算安全跟车距离 评估碰撞风险(TTC) 实现巡航控制状态机

Install

npx skills add benchflow-ai/skillsbench --skill vehicle-dynamics -g -y
More Options

Non-standard path

npx skills add https://github.com/benchflow-ai/skillsbench/tree/main/tasks/adaptive-cruise-control/environment/skills/vehicle-dynamics -g -y

Use without installing

npx skills use benchflow-ai/skillsbench@vehicle-dynamics

指定 Agent (Claude Code)

npx skills add benchflow-ai/skillsbench --skill vehicle-dynamics -a claude-code -g -y

安装 repo 全部 skill

npx skills add benchflow-ai/skillsbench --all -g -y

预览 repo 内 skill

npx skills add benchflow-ai/skillsbench --list

SKILL.md

Frontmatter
{
    "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'

Version History

  • 9a1f4dd Current 2026-07-24 16:38

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