This document discusses approaches to matrix adjustments in transport modeling and provides an update on the Transport Modellers Network (TMN). It describes common methods for deriving base year demand matrices using traffic count data, including matrix estimation and manual adjustment. It outlines common mistakes when using these methods and recommendations for mitigating errors, such as checking for illogical routes, reviewing distribution changes, and ensuring network and count data quality. The second section provides an update on the recent TMN national meeting and discusses expanding the local TMN branch reach, setting objectives, serving members, discussing hot topics, and other issues.

1. Insert Heading
Matrix Adjustments – How to build
better matrices.
Plus a National Update on the TMN
11 November 2015

2. Topics
• Matrix Adjustments / Matrix Estimation
– approaches available to create matrices (base and forecast year)
– common mistakes
– mitigating these mistakes
– reporting
• Transport Modellers Network
– an update on the TMN following the recent national meeting;
– an interactive session on the direction of local TMN branch:
o broadening the reach of TMN
o objectives for TMN locally / nationally
o how best the TMN can service the local members
o hot topics that should be discussed
o other issues/ideas

3. Matrix Adjustments / Matrix Estimation
• Derivation of demand matrices that can be used in Transport Models
– Utilise traffic count data to adjust matrices
– Used to derive base year demand i.e. require existing count information
• Reasons for use
– Most often: lack of data
– Fast efficient process
– Refining existing matrices to improve accuracy
– Requires little data

4. Approaches
• Preferred approach –
– Trip Generation to derive origins/destinations
– Trip Distribution to generate OD demand
– Mode Choice/Time Period Splicing to derive demand to be assigned
• In the absence of information, or where not suitable to apply, three main
approaches to deriving matrices
– Matrix Estimation/Adjustment <-Base Year
– Furnessing/Fratar <-Base Year/Forecast Year
– Manual Adjustment <-Base Year/Forecast Year

5. Approaches
• Base Year Inputs –
– Preferably a prior matrix
– At a min should have origin and destination totals
– No input should be treated very carefully
– Bluetooth data?
– Traffic Count data
• Approach should be assessed based on information available, data quality
and timelines of project

6. Common Mistakes
• Matrix Estimation is a mathematical process
– It does not think
– It does not question outputs
– It attempts to produce the best statistical fit
– It is only good as the inputs provided
• So what does that mean?
– A good r-squared is not necessarily a good indication of a fit-for-purpose matrix
– Don’t trust the results on face value
– But a good fit may indeed be a good result

7. Common Mistakes
• Common Mistakes made include
– Not checking that demand has been assigned to illogical OD routes
– Checking that the key movements still contain the majority of the demand
– Confirming that the matrix has not been altered significantly
– Assuming that a good r-squared confirms that the demand is suitable
– Assuming that errors in the fit are attributed to the demand
– Software

8. Mitigating Mistakes
• Illogical OD Routes
– Banned Turn
– Demand assigned to OD Pair 1->2
– Resultant trip
1
2
6 5
3
4
1
2
6 5
3
4

9. Mitigating Mistakes
• Illogical OD Routes
– Trip recorded against multiple counts
– For simple networks
• Check prior matrix for OD pairs that are not sensible to be included
• Ensure no large allocation applied before or after estimation
– For complex/large networks
• Note possible OD pairs that would ideally use turn
• Check quantum
• Review path data i.e. select-link
1
2
6 5
3
4

10. Mitigating Mistakes
• Fixing Demand
– The performance of the matrix may vary by location
– Certain cells or row/column totals may be known
– Good Matrix Estimation Tools will allow you to fix cell values, rows / column totals
– Provides flexibility and helps remove potential distortion / compensating errors
– Allows for new land developments not to distort process
Matrix 1 2 3 4 5 6
1
2
3
4
5
6

11. Mitigating Mistakes
• Reviewing Distribution
– Important to understand changes to matrix
– Need to understand if large/small multipliers have been used
– Large/small adjustments imply poor fit of prior matrix
– Need to understand if adjustments valid or masking an underlying issue
– What is impact of changes

12. Mitigating Mistakes
• Reviewing Distribution
– Calculate factors applied on OD level
– Adjustment Factor = Estimated Matrix / Prior Matrix
– Plot as a distribution
– Should follow normal distribution
if good fit of prior
– Quick and easy check
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
18.0%
20.0%
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
2.4
ProportionofODCells
ME Adjustment Factors

13. Mitigating Mistakes
• Reviewing Distribution
– Important to review prior and post estimation matrix statistics
• Total Demand
• Vehicle Kilometres Travelled
• Vehicle Hours Travelled
• Trip Ends Profile / Trip Distribution profile
– Large changes indicate change in travel patterns and a need to investigate further

14. Mitigating Mistakes
• Network, Counts and Assignment
– Don’t just review the demand matrices
– Is network correctly coded?
• Capacities of links?
• Junction layouts?
• Phasing?
• Turn bans?
– How reliable is the count information supplied?
• Is it current year?
• What type of count?
• Do counts provide screenline to assess demand?
1
2
6
5
3
4

15. Mitigating Mistakes
• Network, Counts and Assignment
– What do the travel paths look like?
• Select link
• Key corridors
• Bandwidth plots
– Count performance by location?
• Systematic/geographical bias/issues?
– Centroid loadings
• Suitable location
• Representative of network access/egress

16. Reporting
• TELL A STORY!
– If the changes or the results seem counter-intuitive are they correct?
– Report on the process adopted
• Document assumptions – where professional judgement applies
• Refer to guidelines for validation/confirmation of suitable process adopted
• No of iterations, constraints, checks, source of prior (inc development)
– Report on the level of performance and provide key reporting statistics
• Change in network stats
• Distribution of factors
• Modelled vs observed (scatter plot)
• Screenline demands (bar charts)

17. TMN National Meeting
• AITPM TMN Vision:
– Better connecting people and organisations within the discipline and “outside”
the discipline
– Manage modelling stream of National Conference and Forum annually (as a focus)
in partnership with the State Committee
– Hosting State based events
– Enabling national and international links
– Doing all this within the umbrella of AITPM

18. TMN In South Australia
• How do we broaden the reach of TMN?
• What should be the objectives for TMN locally / nationally?
• How best can the TMN can service the local members?
• What are the hot topics that should be discussed?
• Any other issues or ideas?