AgentSkillsCN

Calculate Fleet Efficiency

计算车队运营效率

SKILL.md

Skill: Calculate Fleet Efficiency

Domain

transportation

Description

Calculates fleet operational efficiency metrics including utilization, fuel economy, and maintenance optimization for fleet management decisions.

Tags

fleet, transportation, logistics, efficiency, fuel, maintenance

Use Cases

  • •Fleet utilization analysis
  • •Fuel efficiency optimization
  • •Maintenance scheduling
  • •Route efficiency assessment

Proprietary Business Rules

Rule 1: Utilization Calculation

Asset utilization measurement against capacity.

Rule 2: Fuel Economy Analysis

MPG analysis and fuel cost optimization.

Rule 3: Maintenance Interval Optimization

Predictive maintenance scheduling based on usage.

Rule 4: Driver Performance Scoring

Driver efficiency and safety metrics.

Input Parameters

  • •fleet_id (string): Fleet identifier
  • •vehicle_data (list): Vehicle details and specs
  • •trip_history (list): Recent trip records
  • •fuel_records (list): Fuel consumption data
  • •maintenance_logs (list): Maintenance history
  • •driver_metrics (dict): Driver performance data

Output

  • •fleet_efficiency_score (float): Overall efficiency rating
  • •utilization_metrics (dict): Utilization analysis
  • •fuel_analysis (dict): Fuel efficiency findings
  • •maintenance_forecast (list): Upcoming maintenance needs
  • •optimization_recommendations (list): Efficiency improvements

Implementation

The calculation logic is implemented in fleet_calculator.py and references data from CSV files:

  • •utilization.csv - Reference data
  • •fuel.csv - Reference data
  • •maintenance_intervals.csv - Reference data
  • •driver_benchmarks.csv - Reference data
  • •score_weights.csv - Reference data
  • •cost_factors.csv - Reference data
  • •compliance.csv - Reference data
  • •parameters.csv - Reference data.

Usage Example

python
from fleet_calculator import calculate_fleet_efficiency

result = calculate_fleet_efficiency(
    fleet_id="FLT-001",
    vehicle_data=[{"id": "VH-001", "type": "semi", "capacity_tons": 20}],
    trip_history=[{"vehicle_id": "VH-001", "miles": 500, "load_pct": 0.85}],
    fuel_records=[{"vehicle_id": "VH-001", "gallons": 80, "miles": 500}],
    maintenance_logs=[{"vehicle_id": "VH-001", "type": "oil_change", "odometer": 45000}],
    driver_metrics={"avg_speed": 58, "idle_time_pct": 0.12}
)

print(f"Fleet Efficiency Score: {result['fleet_efficiency_score']}")

Test Execution

python
from fleet_calculator import calculate_fleet_efficiency

result = calculate_fleet_efficiency(
    fleet_id=input_data.get('fleet_id'),
    vehicle_data=input_data.get('vehicle_data', []),
    trip_history=input_data.get('trip_history', []),
    fuel_records=input_data.get('fuel_records', []),
    maintenance_logs=input_data.get('maintenance_logs', []),
    driver_metrics=input_data.get('driver_metrics', {})
)