Introduction
FRED Engineering has been conducting iRAP assessments across Europe, Sub-Saharan Africa, and India for years, navigating everything from short rural corridors to complex urban networks. Like many firms in the road safety field, they’ve wrestled with a familiar challenge: manual iRAP coding is time-consuming, resource-intensive, and prone to interpretation inconsistencies, especially in mixed traffic environments (heterogeneous road environments).
Recently, they piloted AssetMAPPER Roads, an AiRAP accredited inspection system by Transoft Solutions, on the SS87 “Sannitica” project in Southern Italy.
Today, we caught up with Antonino Tripodi, Technical Director at FRED Engineering, to learn about the bottlenecks they were facing, what drew them to AI-powered automation, and how the pilot is changing the way they approach iRAP workflows.
The Interview
Can you tell us about the work FRED Engineering does. What kinds of projects do you typically handle?
Antonino Tripodi: Our mission is to help authorities, institutions and companies to reduce traffic fatalities and injuries on roads and urban areas through sustainable and innovative road safety solutions. We conduct iRAP assessments across a wide range of road environments, from short corridor studies to extensive network evaluations. Scope of our projects span baseline assessments, investment scenario development, and countermeasure planning, both low-cost and high-cost interventions.
Over the years, we’ve completed assessments in several European countries, including Italy, Spain, Albania and India, as well as in various Sub-Saharan African states, including Tchad, Burkina Faso, Tanzania, Mozambique. The road networks we assessed vary greatly in both type and length, ranging from short corridors of just a few dozen kilometres to extensive networks covering both rural and urban environments.
What were the main challenges you were facing with manual iRAP coding before trying AssetMAPPER Roads?
Antonino Tripodi: One of the main challenges concerned with the interpretation of the guidelines provided in the iRAP coding manual, particularly for staff who are new to the process.
In highly mixed traffic environments (heterogeneous road environments), for instance, in regions like the Sub-Saharan Africa where rural villages, open countryside, and urban areas alternate within short distances, attributes such as land use and roadside (and among many others) can change rapidly along the same corridor. This frequent variability considerably increases the margin for error, which in turn affects the quality and time taken in subsequent validation phase.
After the manual coding phase, we generate a CSV file and upload it into ViDA, the platform used to calculate Star Ratings. It cross-checks the coded data against a predefined compatibility matrix to identify potential inconsistencies between attribute groups. The higher the variability and subjectivity in attribute interpretation, the more likely these mismatches become. As a result, the coding often needs to be reviewed and corrected multiple times—an iterative and resource-intensive process, especially for long corridors or network-wide assessments.
Can you give us a sense of the resources typically required for a project?
Antonino Tripodi: For a project of similar scale and complexity to the SS87 project, which is about 60 kilometres, it would typically require a team of three to four road coders working over a two-month period to complete the assessment.
But here’s what’s frustrating: most of that time isn’t spent on analysis or developing safety recommendations. It’s spent on coding and recoding data, then validating and revalidating it.
What made you decide to explore AssetMAPPER Roads?
Antonino Tripodi: We were motivated by the potential to enhance efficiency in iRAP assessments through AI-based automation. AssetMAPPER Roads caught our attention because it could help us simplify the end-to-end coding process while maintaining strict alignment with iRAP standards.
Several factors drove our decision to test this tool. First, we wanted to diversify our assessment toolkit and explore how AI-based technologies could optimize our time and resource allocation. Second, our experience with the demo provided by the Transoft team showed that AssetMAPPER Roads has an intuitive interface that should be easy for our team to learn and use.
Ultimately, we saw an opportunity to modernize our approach without compromising the quality standards that iRAP assessments demand.
Figure 1. Road Coding Features as demonstrated in AssetMAPPER Roads (sample image for illustrative purposes)
The SS87 “Sannitica” Pilot Project
You piloted AssetMAPPER Roads on the SS87 “Sannitica” project in Southern Italy. Can you tell us about that project?
Antonino Tripodi: The project concerned the iRAP Star Rating assessment and the development of investment plans for the SS87 “Sannitica,” a national road located in Southern Italy. The project involved the evaluation of approximately 60 kilometres of road.
Figure 2. Star rating assessment results from the SS87 project.
Results and Impact
How has AssetMAPPER Roads addressed the challenges you described earlier?
Antonino Tripodi: AssetMAPPER Roads outputted the automated extraction and classification of several iRAP attributes which provided a reduction in the time required for coding. This allows automatic coding of 20 road attributes, and the tool also helps standardize attribute interpretation across different sections of the network, contributing to a more consistent and efficient workflow.
The use of AssetMAPPER Roads has allowed us to reduce the amount of time, effort, and personnel required for iRAP coding activities. This has enabled us to focus more on interpreting and analysing the results rather than spending most of our resources on the coding process itself.
What specific features or functionality have been most valuable for your work?
Antonino Tripodi: The most immediate benefit is the automated coding of several attribute groups, which simplifies the overall process.
Another particularly valuable feature is the ability to visualize the Star Rating for different road user categories: vehicles, motorcyclists, cyclists, and pedestrians directly along the assessed corridor.
In the traditional workflow, this step is only possible after uploading the CSV file into ViDA, at the final stage of an iterative process. Having this functionality integrated earlier within AssetMAPPER provides immediate visual feedback on safety performance, helping to better interpret the results and verify the consistency of the coded data.
Figure 3. Star Rating Visualization by road user category in AssetMAPPER (sample image for illustrative purposes)
Quality and Industry Adoption
One common concern about AI tools is whether they compromise quality. How did AssetMAPPER Roads perform in terms of data quality and alignment with iRAP standards?
Antonino Tripodi: This is critical for us. AssetMAPPER Roads is a dynamic and intelligent tool that helps reduce time and resource requirements while delivering reliable results in terms of data quality.
The automated approach didn’t introduce new errors. If anything, it reduced human error while maintaining compliance with established iRAP protocols. It can represent valuable support for professionals involved in iRAP assessments who aim to optimize their workflow without compromising methodological integrity.
You mentioned earlier your interest in AI-based automation. What’s the general sentiment around AI in the road safety consulting industry, particularly in Europe?
Antonino Tripodi: There is a clear and growing interest in the use of AI-based solutions. This openness largely stems from the increasing need to automate and streamline workflows, particularly in activities that are repetitive and time-consuming, such as data coding and validation. AI tools are therefore seen as valuable instruments to enhance efficiency and consistency, while maintaining compliance with established methodologies like iRAP.
Although most software solutions that incorporate AI are still in the experimental or pilot phase, there is a clear willingness among road safety consulting firms to adopt and make use of them. The industry recognizes the potential of AI to improve efficiency, data consistency, and overall project quality, and this is driving a growing openness towards integrating such technologies into standard workflows.
Would you recommend AssetMAPPER Roads to other road safety professionals conducting iRAP assessments?
Antonino Tripodi: Yes, absolutely. AssetMAPPER Roads is a dynamic and intelligent tool that supports a reduction in time and resource requirements while delivering reliable results in terms of data quality. It can represent a valuable tool for professionals involved in iRAP assessments who aim to optimize their workflow without compromising methodological integrity.
About FRED Engineering
FRED Engineering is an international consulting firm that specializes in engineering services concerning the safety of transport infrastructures, their resilience against climate change, their improved accessibility for all. Established in 2017, FRED Engineering has worked in over 70 countries, providing innovative transport infrastructure solutions that prioritise both people and the environment, allowing everyone access to transport solutions while providing mobility safely and sustainably.
About AssetMAPPER Roads
AssetMAPPER Roads is an AiRAP-accredited inspection system that helps accelerate iRAP Star Rating assessments through both automated road coding with advanced computer vision technology and manual road coding with easy-to-use dropdown menus. This web-based application leverages open-source data and 360° video footage to streamline the road coding and data preparation processes. With AssetMAPPER Roads, transportation agencies can conduct network-wide safety assessments more efficiently and cost-effectively, enabling faster identification of high-risk roads and data-driven prioritisation of infrastructure improvements aligned with global road safety standards.
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