iROADS™ is our world-leading digital asset management software. iROADS is specifically designed for progressive highway authorities and other organisations responsible for managing roads and highways. iROADS offers a range of features that help highway authorities manage their road network more efficiently and sustainably. Our pavement specialists continuously listen to our customers to improve iROADS™ to ensure it is fit for purpose for the future.
In our latest product update, TRL Software’s Lead Business Analyst Shibin Bhaskaran discusses our approach to Asset Investment Planning (AIP) and Whole Life Cost Analysis. He further discusses why generic AIP tools may miss the point for mature highway operators.
For assets with a long lifecycle – such as pavement assets which may last several decades – decisions about how to maintain and operate the asset need to take into account this long-term view. If investing more in the next maintenance cycle can significantly reduce the operational life of an asset, this may be a worthwhile investment. And of course, the life of the asset is not the only factor to consider: maintaining a pavement has effects on safety, traffic delays, embodied carbon, and so on – these should all be considered in a holistic cost-benefit analysis. We call this type of analysis, which quantifies costs and benefits over a long period, and allows us to balance multiple factors over both short- and long-term a Whole Life Cost (WLC) analysis.
Objectives of life cycle planning through Whole Life Cost Analysis:
- Determine the level and details of pavement investments required to achieve desired performance and choose an appropriate maintenance strategy.
- Predict future performance of road infrastructure assets including specific pavement defects that can be expected.
- Minimize costs over the pavement life cycle while maintaining the required performance.
- Based on the budget and funding available, determine the detailed pavement performance that can be achieved.
Business Components & Tools
Asset Investment Planning Capabilities in iROADSTM
Future evolution of our Asset Investment Planning module
- Volume and variety of data
To run a WLC analysis for even a single scheme requires a huge amount of different types of data: the basic layout and dimensions of the pavement, condition data, construction data, traffic data, overlay and depth restriction data and more. Additionally, running a long-term analysis – say, for 60 years – means that the amount of data which needs to be generated, processed, stored, and tracked only increases. Generic AIP tools which are not pavement specific is unable to understand the impact and relationship between different data elements. Hence the results may not be fit for purpose or realistic.
To handle this enormous volume of data in IROADS, we decided to use high-speed cloud storage instead of on-premises or regular cloud data storage. This enables us to scale up for high performance computing and machine learning workloads. Secondly, sophisticated caching strategies are also implemented to retrieve the required data from the huge pool of data in a much quicker and efficient way.
- Data Evolution and its impact on results
Different pavement schemes can use same or different sets of configurations to perform the whole life costing analysis. In such cases, the probability of data getting modified increases because there can be multiple privileged users managing the complex configurations. To avoid such impacts of change in the configuration data on the existing schemes (that are being analysed or has already been analysed) we are storing the snapshot of the relevant configuration data tied to a particular pavement scheme. With snapshotting capabilities, users can analyze different scenarios including historical and real pavement data linked to pavement schemes. This level of analysis maybe missing in generic AIP tools.
- Specific configurations required for pavement analysis and how this was managed
WLC pavement analysis can be highly complex, and as such requires significant configuration and cost details to provide meaningful results. As an example – in some cases more than 10,000 costs need to be configured to accurately calculate works costs over 60 years. This can seem daunting, however we specifically designed features and workflows to make this as efficient and easy as possible for users. For one thing, the vast majority of configuration only needs to be done infrequently (most likely: yearly) by expert users – regular users therefore never have to worry about this. iROADS provides tools to make configuration as painless as possible – for example, the inbuilt, interactive, interface allows large data tables to be managed easily.
- Understanding of pavement data and real-life pavement processes are required for accuracy of results
The results of WLC analyses are used to support business-critical decisions, often involving significant sums of public money, about how to manage infrastructure assets all over the world. As such, the accuracy of the outputs is critical, and a basic expectation for customers.
We have efficient pavement algorithms, developed, and tested through years of research, in place to perform these critical and complex calculations. We also have intermediate gateways at every major step of the analysis process that enables us to provide options and views to end users. These gateways provide opportunities for the users to assess the calculations and measure the accuracy at any stage of the process, including end results. Pavement schemes can also be prioritized based on comparison of their cost analysis.
- Complexity in modelling the future
A central principle in WLC analysis is to model future effects based on current data and sound pavement forecasting models. For example: as traffic on a road increases, so does the rate of deterioration of that road’s condition, thereby leading to an earlier need for maintenance – all of this (and more) needs to be modelled by projecting current data. Additionally, the effects of any maintenance ‘triggered’ during the analysis period needs to be accounted for.
iROADS provides platform for privileged users to configure different profiles for deteriorating the road’s condition. Users can either use flat percentage and value to deteriorate the condition every year or use iROADS charts and dashboards to visualise the deterioration profile curves for projecting the condition of the road for future years. In near future, we also have plans to use AI/ML technology to model the future effects of the maintenance on the road condition.
The WLC analysis with the AIP module is a tool to help find the optimal maintenance plan. What optimal means should be based on the goals of the organization. In the simplest sense, it is a pure cost-benefit optimization – “what approach gets us the most bang for our buck?”. Even this simplest use case requires pavement calculations and data processing which is far too complex to for generic AIP solutions. Nearly always, there are additional factors to consider, such as: the available short-term maintenance budget, or performance targets and KPIs which must be hit. Finding an optimal solution in such a complex context specific to pavements is no easy task.
- Support Sustainability Goals
Sustainability in road asset management can be promoted by reducing the amount of carbon used in road construction, maintenance and operations on the one hand, and by minimizing the harmful emissions from traffic – which can be affected by road congestion due to roadworks, and even the pavement condition – on the other hand. These should factor into a fully holistic cost-benefit analysis, via a cost being applied to embodied and emitted carbon resulting directly from road construction or maintenance.