TR-T0155 PTV Visum - Synthetic Matrix Estimation (ODME) in PTV Visum (US)

In this course, we will cover the application of synthetic matrix estimation (ODME) procedures in PTV-Visum. ODME methods are used to adjust demand matrices, so that network assignment results match observed count data more closely.

Matrix estimation can be useful in the following situations:

• Using current year counts to update trip tables from travel demand models for a traffic study that occurs in a different year than the   calibrated base model.
• A matrix generated from sample data is to be improved using count data. For example: big data from mobile devices.
• Adjusting seed or existing trip tables to match surveyed trip length distribution.

The course will cover both entropy-based (TFlowFuzzy) and least squares matrix estimation methods implemented in Visum. Application of the dynamic variant of the least squares method will also be covered. While matrix estimation methods are applicable to both PrT (auto) and PuT (transit) modes, this course will cover the PrT (auto) side application.

Intermediate

Traffic engineers and travel demand modelers working on corridor and impact studies with short to mid-term horizons.

Knowledge of traffic assignments in general and ideally some application experience in PTV-Visum.

4 hours

Due to organizational and local conditions, the duration of the course may vary. Please note the details of your chosen course date before booking.

• Data preparation for matrix estimation
• Application of matrix estimation methods in PTV-Visum (TFLowFuzzy, Least Squares, Dynamic Least Squares)
• Analysis of results 

The courses below are the next scheduled course dates. Check our training calendar to see all available dates or contact us if you do not find a suitable date.