Add comprehensive Korean code review guide for transport modelers

[Copilot]

Overview

This PR adds a comprehensive Korean-language code review and learning guide for transportation modelers working with the TM2PY (Travel Model 2 Python Package) framework. The guide addresses the need for educational documentation that helps transport planners and modelers understand, learn, and effectively apply TM2PY for highway and transit demand forecasting.

What's Added

New Documentation: docs/code_review_for_transport_modelers_kr.md

A 683-line comprehensive guide in Korean (한국어) covering:

Main Applications

• Highway (road) demand forecasting and traffic assignment
• Transit (public transportation) demand forecasting
• Network analysis and accessibility studies

Architecture and Components

• Detailed explanation of RunController and component-based design
• How components interact and execute in sequence
• Configuration system using TOML files

Highway Demand Forecasting Workflow

• Network preparation with VDF, tolls, and link attributes
• Demand loading from OMX matrix files
• SOLA equilibrium traffic assignment algorithm
• Skim matrix generation (time, distance, toll, generalized cost)
• MAZ-level micro-analysis using shortest path algorithms

Transit Demand Forecasting Workflow

• Transit network structure (modes, vehicles, routes)
• Optimal strategy-based assignment
• Transfer modeling and penalties
• Fare system integration
• Access/egress connector times

Learning Roadmap
Organized by skill level with specific learning objectives:

• Beginner: Installation, basic execution, configuration files
• Intermediate: Network data structures, demand matrices, assignment algorithms
• Advanced: Component development, Emme API integration, performance optimization

Practical Applications

• Scenario analysis for new infrastructure
• Toll policy impact assessment
• MAZ-level accessibility analysis
• Transit service improvement studies
• Multi-period time-of-day analysis

Additional Content

• Data input/output specifications
• Best practices for project organization
• Troubleshooting common issues
• Links to additional resources

Documentation Configuration Updates

mkdocs.yml Changes

1. Added navigation entry for the new Korean guide to make it easily discoverable
2. Removed incompatible extensions:
   • fontawesome_markdown: Not compatible with current markdown version and unused in docs
   • custom_templates: Referenced non-existent templates directory

These changes ensure the documentation builds successfully while maintaining all functionality.

Verification

• ✅ Documentation builds successfully with mkdocs build
• ✅ Korean text properly encoded (UTF-8)
• ✅ All markdown syntax validated
• ✅ Navigation structure correctly updated
• ✅ No breaking changes to existing documentation

Target Audience

This guide is specifically designed for:

• Korean-speaking transportation planners and engineers
• Traffic modelers learning activity-based modeling
• Researchers studying urban transportation systems
• Government agency staff working on regional travel demand models

Why This Matters

Transportation modeling is a specialized field that requires understanding both transportation planning concepts and technical implementation. This guide bridges that gap by:

• Explaining complex algorithms in accessible Korean language
• Providing practical examples from real-world applications
• Offering a structured learning path from beginner to advanced
• Connecting theoretical concepts to actual code implementation

The addition of Korean-language documentation makes TM2PY more accessible to the global transportation modeling community, particularly in regions where Korean is the primary language.

Original prompt

transport modeler 가 학습할 수 있도록 코드 리뷰를 해줘.

주요 활용방안이 뭔지, 어떤 점을 중점적으로 공부하면 되는지.

대중교통, 도로 수요예 활용할 수 있는 방안이 뭔지 등.

---

✨ Let Copilot coding agent set things up for you — coding agent works faster and does higher quality work when set up for your repo.