Appendix 3 – Predictive Analysis Results

This section covers the analysis of Brimbank’s road performance from 2001 to 2008. Brimbank has collected two sets of reliable and repeatable condition data based on an industry accepted method (RTA, NSW URCOND 90 Methodology and guidelines provided in NAASRA and Austroads Manual) in this time period.

9.3.2 What condition characteristics do we measure our roads

Brimbank measures road condition based on the following criteria. Refer to Figure A.1.1 below.

• Cracking: Related to pavement and surface fatigue

• Rutting: Related to loss of pavement structure in wheel paths

• Roughness: Related to loss of integrity of longitudinal profile and ride quality • Pavement defects: Related to pavement deformities in localised areas

• Texture: Related to loss of surface integrity due to bitumen oxidisation, stone loss or bleeding.

• Local defects: Related to minor surface deformities

Typical Road Condition criteria in Brimbank City Council

9.3.3 What do we use this condition data for

Brimbank uses condition information for:

Typical surface deformation Typical local defects Typical local defects

• Monitoring overall road network performance over time

• Planning by developing predictive models that can forecast future funding needs • Prioritising capital works program for following years

• Compliance by producing valuations and annual depreciation figures for AAS116 requirements.

9.3.4 Why do we monitor road network performance

Monitoring overall ‘road network performance’ over time is a recognised means of strategic management based on the International Infrastructure Management Manual as well as the more recent NAMS (National Asset Management Steering Group) guidelines. Brimbank’s Road Asset Management Plan also states that ‘road network performance’ will be used as a strategic performance indicator for reviewing road management practices, funding

allocations and compliance with the MAV’s STEP Program. Performance monitoring over different periods in time provides Brimbank with a strategic perspective on the following aspects:

• Has our road network improved, deteriorated or stayed the same over the last few years.

• Are we spending enough and in the right spots?

• Which parts of the network show higher rates of deterioration and what are we doing about it?

• Do we need to improve the methods and techniques of measuring asset condition?

9.3.5 How do we assess road asset performance

Future Performance

Future performance is forecast using prediction models. Brimbank’s road prediction models provide the first-cut simulated performance profile, i.e. the models predict what condition the roads will be in 3, 5, 10 and 20 years time. These profiles are called ‘predictive profiles’.

Historical Performance

Historical road asset performance is based on network comparison of various sets of road condition data. It is assessed by comparing time based profiles of condition. Brimbank has 2 sets of reliable data between 2001 and 2008. The comparison is based on the proportion of the network in each condition state, i.e. good, moderate or poor condition in accordance with the Road Asset Management Plan.

Each round of data collection covered 100% of Brimbank’s network to provide a consistent snap-shot in time.

The predicted profiles will be regularly compared against historical profiles (reality checks) over time to improve the ability of the performance models to select the most needy streets and roads for a treatment and to enhance our confidence in rational decision making with regard to future funding and allocation.

Page -63- scenarios and make rational trade-off decisions about the following in accordance with our Road Asset Management plan.

1. How much should we spend each year on routine maintenance, reseals and rehabilitations to preserve our road asset network in its present condition over 3, 5, 10 and 20 years?

2. What will happen to our road asset condition over 3, 5, 10 and 20 years if we spent more or spent less than we currently spend or if we use a different mix of spending patterns, i.e. distribution between reseals, patching and rehabilitations?

3. Based on our current adopted level of funding, which road sections we will program for resurfacing and rehabilitation in the next 2 financial years.

9.3.7 How reliable is our predictive models

Model Reliability

Brimbank’s condition measurement method and prediction models have been in use since late 2000. These prediction profiles, treatment decision models, life cycle paths etc, were all developed through a series of rigorous on-site consultations and workshops with key operational staff that had knowledge of how these assets performed. Initial outputs have been checked each year for reliability and consistency. As new capital treatments have surfaced in the industry from time to time, our models have incorporated these in the prediction methodology. We have trialled all options of reseals, asphalt, mill and re-sheet etc to ensure that models are representative of real-time needs and performance. The costs applied in the model are obtained from actual historical costs to ensure that the forward predictions are realistic. The prediction model has been the basis upon which Brimbank allocates its annual capital funding to various road projects across the municipality. When this project level program is developed by the system, Council officers verify the validity of the output on site to ensure that the model is realistic.

The 2001 data was used as part of this analysis to predict the 2008 condition based on actual funding in each year from 2001 to 2008. The results match very closely with the actual condition assessment in 2008, demonstrating that the models are robust and have a high level of integrity. See Figures A.1.2, A.1.3, A.1.4 and A.1.5.

Road Cracking, 2001 versus 2008 Comparison

Page -65-

Road Roughness, 2001 versus 2008 Comparison

Local Defects, 2001 versus 2008 Comparison

Condition Reliability

Condition data capture has always been undertaken by Brimbank with a strong focus on quality assurance. QA outcomes and desired levels of tolerance are written into the contract specifications. The data collection contractor performs to this specification and Council officers also undertake regular desktop and on-site audits to ensure data integrity.

It must be noted that road data I typically collected by local governments using a

combination of visual and automated methods. Both methods have their advantages and disadvantages. Whilst the industry is attempting to make automated methods highly reliable, the evidence to date still suggests that there is a long way to go before this is actually

achievable. Based on experiences in the industry, Brimbank has used an appropriate combination of visual and automated method for its surveys.

It must also be noted that the accuracy of the road data isn’t at a micro-accuracy level, and overall rating is estimated based on the quantity of defects within a road segment.

9.3.8 What information do the above profiles provide from an Asset Management perspective

The overall network condition has deteriorated between 2001 and 2008. However, the level of impact in most condition criteria has been moderate. It is interesting to note that only roughness/ride has marginally improved. This is in line with Brimbank’s models, to consistently apply major treatments like rehabilitations and reconstructions to particularly address roughness.

It is therefore obvious that the allocated funding over the last 8 years has not been sufficient to preserve the condition of the network. See Figure below:

Actual funding profile, 2001 to 2008.

(Includes pavement reconstructions, rehabilitations, resurfacing, kerb & channel. Excludes drainage, footpath, vehicle crossings, etc)

9.3.9 Managing future needs and sustainability

Page -67- optimised its expenditure, by spending its capital budget in the most cost effective fashion. Cost effectiveness in this sense of life cycle sustainability means the following:

• The prediction models are based on long term impacts of short term decisions • Lowest life cycle cost over 10 years is the adopted strategy