driver-scheduling-optimizer

Solid

Automated driver assignment and hours of service compliance skill ensuring regulatory compliance and operational efficiency

AI & Automation 814 stars 53 forks Updated today MIT

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Quality Score: 95/100

Stars 20%
97
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Driver Scheduling Optimizer ## Overview The Driver Scheduling Optimizer automates driver assignment and ensures hours of service (HOS) compliance while maximizing operational efficiency. It matches drivers to loads based on qualifications, availability, and location while preventing regulatory violations and managing fatigue risk. ## Capabilities - **HOS Compliance Monitoring**: Track and enforce hours of service regulations in real-time - **Driver-Load Matching**: Match drivers to loads based on qualifications, location, and availability - **Qualification Verification**: Verify driver certifications, endorsements, and training requirements - **Fatigue Risk Assessment**: Assess driver fatigue risk based on work patterns and rest periods - **Break and Rest Planning**: Plan mandatory breaks and rest periods into driver schedules - **ELD Data Integration**: Integrate with electronic logging devices for accurate time tracking - **Violation Prevention Alerting**: Alert dispatchers and drivers before potential violations occur ## Tools and Libraries - ELD APIs - FMCSA Compliance Databases - Scheduling Optimization Libraries - Driver Management Systems ## Used By Processes - Driver Scheduling and Compliance - Route Optimization - Fleet Performance Analytics ## Usage ```yaml skill: driver-scheduling-optimizer inputs: drivers: - driver_id: "DRV001" name: "John Smith" current_location: "Chicago, IL" endorsements: ["hazmat", "tanker"] hos_status...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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