RIMS Forum 22 March 2012 by Matthew Rodwell Hastings District Council

1. RIMS Best Practice:
Traffic Count Estimation
2012 Road Asset & Information
Management Forum

2. Acknowledgements
Ministry of Transport MWH New Zealand
Stuart Badger Fergus Tate

3. Traffic Count Estimation:
research result is a proposed traffic
monitoring framework that significantly
improves the overall accuracy and
efficiency (and therefore value for
money) of typical traffic data collection
regimes

4. Proposed Traffic Monitoring Framework
• creation of a traffic link model
• core annual monitoring sample
• rotational sample (80/20)
• Linking estimates

5. Contents
• Why is it important
• RIMS Objective
• Background
• Sampling Framework
• Improving Traffic Estimates
• Other Considerations

6. Why is it Important?
•AADT shows network traffic levels
•Basis for local & national traffic monitoring
•Reasons for RCAs to have accurate estimates
1. Better Decision Making
2. Used in LoS & Benchmarking
3. Funding Decisions

7. Uses of Traffic Count Data
Long term Network Renewal Customer Service Operational
planning & Development
Network traffic Project planning Responding to TM requirements
levels enquiries
TSA & Predictive Pavement & Development Regulatory
modelling capacity design control & planning requirements
Safety studies & Loading for bridge Network
crash analysis design monitoring
Traffic modelling Project economics MIS
& simulation (BCR)
LOS & Policy HCV management
Development

8. RIMS Objective
1. RIMS intention: an applied guide
2. Improve traffic counting outcomes and
value for money
3. Presentation will cover some of the
technical research details & elements of
the applied guide

9. Background
Ministry of Transport Research: “Updating National
Traffic Data: Stage 1 and 2 Final Report” (Hyder
Consulting and MWH New Zealand Limited, 2005)
Prompted due to realisation that data held across
RCAs was very unreliable

10. Network % with Counts < 5yrs old
50%
40% Data Confidence
30%
20%
10%
0%
0% 25% 50% 75% 100%
% of RCAs

12. Research Goals
1. Improving the efficiency of traffic counting
programmes
• Increasing the coverage
• Improve relevancy of data collected
2. Improving Traffic Estimates
• Improving the estimates on uncounted road sections
• Improving the updating of estimates
3. Facilitate RCA implementation

13. Latest Work
1. Pilot the proposed framework in three RCAs:
• Upper Hutt [urban], Southland [rural] & Hastings [mixed]
2. Nation-wide survey of traffic monitoring practices
in RCAs.

14. Approach
• creating a traffic link network from the spatially
referenced RAMM database
• fitting the proposed stratified sampling method to
this network

15. Traffic Link Network / Model
1. Create Spatial Network
2. Aggregate sections that carry the same traffic
3. Relate sections subject to the same growth
effects (parent/child)
• Maximises network coverage
• Optimises size of sampling framework

16. Node 2006
Node 2000 Node 2001 Node 2003 Node 2004 Node 2005 Node 2007
RAMM Cway id: 1949 RAMM Cway id: 1951 RAMM Cway_id: 1953
RAMM Cway id: 1950 RAMM Cway_id: 1952
Legend:
RAMM C_way section node point

17. T.Link_id: 949 T.Link_id: 1950 T.Link id: 1951
Node 2006
Node 2000 Node 2001 Node 2003 Node 2004 Node 2005 Node 2007
RAMM Cway id: 1949 RAMM Cway id: 1951 RAMM Cway_id: 1953
RAMM Cway id: 1950 RAMM Cway_id: 1952
Legend:
Node point derived from Spatial model
RAMM C_way section node point
Combined spatial and RAMM C_way section node
point

18. Size of Traffic Link Model
20%
40%
60%
80%
0%
100%
RCA

19. Sampling Framework
Two distinct needs for traffic count data.
• monitoring of travel activity, at a local, regional, or national level
• determining traffic volumes and travel on individual roads
1. core sample - for monitoring travel activity
2. rotational sample - to cover the road network.

20. Core Sample
National Traffic Database Project - Dr M K Mara
developed a sampling framework to estimate the
total vehicle travel within an RCA, to a given level of
precision.

21. ADT B5 B4 B3 B2 B1
20,000
15,000
10,000
5,000
0
0% 40% 60% 80% 90% 100%
Proportion of Links

22. Core Sample Size Requirements
Hastings District Council
Nominal
Precision
+/-10% +/-5%
<40% 2 7
AADT Quantile
40-60% 3 8
60-80% 8 31
80-90% 6 23
90-100% 27 107
Total 46 175

23. Rotational Sample
• The aim of the rotational sample is to ensure that
over time traffic data is collected on, or is applicable
to, as much of the network as possible.
• Focuses on capturing majority of network VKT

24. Rotational Sample Coverage
Proportion of Total Vehicle Kilometres of Travel
RCA Contained in the Model
25% Model 50% Model
Hastings District Council 87% 97%
Upper Hutt City Council 86% 97%
Southland District Council 84% 95%

25. Sample Size vs. Network Coverage

26. Sample Size vs. Network Coverage

27. Pilot Area Results
Counting approximately 17% of the traffic links p.a.
would:
1. satisfy the core sampling requirements
2. Cover 80% of the total vkt (two year rotational cycle),
3. provide sufficient additional capacity to retain the
investment in the historic monitoring programme

28. Traffic Estimates
• Sections of road are linked
• Approximate relationships (e.g. growth trends) can
be assumed
• Linking sections can improve confidence on
unmonitored sections

29. Traffic Estimates
Z
0.2Z
0.65Z A 0.95Z B Z
Y=0.45Z
Y C 0.5Y
0.5Y

30. Other Considerations
1. Data use / type of data you want
2. HCV Traffic
3. Growth Node
4. Seasonality
5. Traffic modelling

31. Traffic
Modelling
Capture movement
patterns
• Cordons
• Screen-lines

32. Summary
• Traffic count data is important
• Monitoring framework improves the overall accuracy and
efficiency
• 3 Key foundations to strategy:
• creation of a traffic link model
• core annual monitoring sample of between 3% and 7% links
• 2 year rotational sample (top 20% of VKT links)
• Other considerations to make
• HCVs
• Seasonality
• Network Change
• Cordons & screen-lines

33. Process Review
1 2 3 4
8 7 6 5
9 10 11

34. Spatialise
RAMM Data 2 3 4
8 7 6 5
9 10 11

35. Update ADT
1 estimates to 3 4
same base
8 7 6 5
9 10 11

36. Homogenise
network to
1 2 form traffic 4
links
8 7 6 5
9 10 11

37. Relate Links
(e.g. by ADT
1 2 3 % or Growth
etc.)
8 7 6 5
9 10 11

38. 1 2 3 4
Stratify
8 7 6 Network
9 10 11

39. 1 2 3 4
Select
random
8 7 sample for 5
CORE SITES
9 10 11

40. 1 2 3 4
Select 20%
with highest
8 VKT for 6 5
ROTATIONAL
SITES
9 10 11

41. 1 2 3 4
Substitute
sites:
Core sample 7 6 5
Historic sites
Other goals
9 10 11

42. 1 2 3 4
8 7 6 5
Set
Frequency
for Counts
10 11

43. 1 2 3 4
8 7 6 5
Produce
9 Programme 11

44. 1 2 3 4
8 7 6 5
Aim to count
15-20% of
9 10 your links
annually

45. Questions?
More Information?
www.rims.org.nz
Matthew Rodwell
matthewr@hdc.govt.nz