Emme 4.5 introduces new modelling, productivity and platform features including the new Emme Agent population synthesizer, Python 3 support, streamlined data exchange with Dynameq DTA and other enhancements. Please consult the Release Notes included in the software for a comprehensive list.
Users with software maintenance may log in and download Emme 4.5 from their INRO account here.
The new Emme Agent population synthesizer can be used to produce a list of synthetic households and persons from a partial sample in a manner which best matches demographic controls.
A synthetic population is critical to the accuracy of simulation outcomes, and may be used as the first step in an agent-based travel model or as an advanced method to prepare demographics for aggregate models or survey expansion. Features include a flexible zone hierarchy with simultaneous controls for more representative populations and capability to reflect structural changes between original samples and forecasting scenarios. The population synthesizer is available in the new Emme Agent window and API.
Emme Agent introduces a new demographic scenario which organizes zone systems (e.g. MAZ, TAZ, District, Region), samples (e.g. surveys) and synthesized populations, each reflecting distinct socioeconomic and land-use conditions. Emme Agent also adds a new datastore and a familiar expression engine and calculator for convenient data analysis and preparation. Synthetic population results may be used with any disaggregate travel model or TAZ-level results may be easily saved into matrices for use in zonal aggregate travel models.
The new Emme Agent API allows scripting of Agent data and procedures, especially useful for automating repetitive data tasks. When used from Emme Notebook, changes are reactive in the Agent UI for live feedback.
The new Population Synthesis Scene provides choropleth and dot density maps for mapping synthesizer controls and population results on any zone system.
All Emme Python libraries, APIs and toolboxes as well as the Modeller application framework and Emme Notebook are updated to Python 3. Users can now deploy Python 3 libraries with Emme and use Emme libraries with Python 3.
Sending large Emme networks to Dynameq now runs up to 10 times faster and supports variable transit line headway by time period.
Please refer to the software Release Notes for details on these and other enhancements. And let us know with feedback on the INRO Community Forum.