This comprehensive Emme modeling course equips you with the skills to build, analyze, and visualize transportation models. Starting from foundational concepts, you’ll progress to advanced techniques, including transit and freight modeling. Through hands-on exercises and real-world project work, you’ll gain practical experience in applying Emme to solve transportation challenges. The course also emphasizes best practices, model calibration, and scenario analysis, ensuring you’re prepared for the complexities of transportation planning. Additionally, it covers Python scripting for automation and addresses the importance of mental well-being in this demanding field. Whether you’re a beginner or an experienced modeler, this course will enhance your proficiency in Emme and empower you to make informed transportation decisions.
Key concepts covered include:
- Week 1: Fundamentals & Emme Basics
- Transportation modeling concepts, data, and the 4-step process
- Introduction to Emme: interface, tools, network building
- Data management, matrices, and the Modeler
- Scenario management and expressions
- Week 2: Emme Modeling Techniques & Analysis
- Comparing scenarios, worksheets, and visualization
- Zone systems and matrix operations
- Data exchange and volume delay functions
- Assignment methods and calibration
- Results analysis and visualization
- Week 3: Advanced Emme & Applications
- Advanced analysis techniques (path analysis, desire lines)
- Transit modeling and best practices
- Python scripting and automation
- KEE model development and calibration
- Scenario analysis and future year forecasting
- Week 4: Project Work & Future Directions
- Model checks and transit/freight modeling
- Case studies and real-world project application
- Further learning resources and mental well-being
- Additional course recommendations