Next Generation Road Asset Management
Smart Strategies for Resilient and High-Performing Road Networks
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Course code : AM-F2
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Delivery: Online/Live
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Language: English
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Starting Date:
13 October 2026 -
Registration Deadline:
1 October 2026 -
Total Duration:
12 Hours (4x3 classes) -
Price :IRF Members : 850 CHF
Others : 1100 CHF
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Learning Outcomes
By the end of the course, participants will be able to :
Define levels of service and performance objectives for different classes of road networks
Use performance indicators and multi-criteria approaches to support investment decisions
Apply core road asset management principles to support long-term network performance
Explain how predictive analysis and data-driven tools are changing asset management practice
Understand how condition assessment, risk and lifecycle analysis inform maintenance priorities
Identify where digital twins, monitoring systems and emerging technologies can add operational value
Target Audience
Course Structure
Class 1 : Foundations of Modern Road Asset Management :
Tuesday 13 October 2026, 14:00-17:15 CET
Understand how modern asset management frameworks support safer, more reliable and resilient road networks.
Key topics:
- Why Asset Management is evolving
- International frameworks & maturity models
- Defining service levels for different classes of roads
- Linking asset performance to user expectations and network function
- Lifecycle thinking and whole-life cost considerations
- Introduction to RAMS principles in road infrastructure
- Asset governance and institutional responsibilities
- Why safety, resilience and operational performance increasingly influence asset management decisions
- Common implementation challenges in low-capacity environments
Class 2 : Condition Assessment, Risk and Performance Monitoring :
Thursday, 10 September 2026, 14:00-17:15 CET
How agencies assess infrastructure condition, identify critical risks, and prioritise interventions.
Key topics:
- Condition assessment fundamentals for road infrastructure assets
- Asset inventories, inspections and monitoring approaches
- Understanding deterioration mechanisms and failure risks
- Selecting meaningful performance indicators
- Integrating safety and climate vulnerability into asset assessments
- Risk-based approaches to maintenance prioritisation
- Multi-criteria analysis for competing investment needs
- Service Level Agreements (SLAs) and performance-based maintenance approaches
- Using operational and condition data to support better decisions
- Managing uncertainty and incomplete data
Class 3 : Predictive and Data-Driven Asset Management :
Tuesday 15 October 2026, 14:00-17:15 CET
From Reactive Maintenance to Smarter Intervention Strategies
Key topics:
- Transitioning from reactive to predictive asset management
- Forecasting deterioration and intervention timing
- Data-driven maintenance planning and optimisation
- Decision-support tools and asset management systems
- Risk-based intervention strategies and scenario planning
- Introduction to digital twins and infrastructure modelling concepts
- Integrating monitoring technologies, sensors and operational data
- Using predictive analysis to support resilience and lifecycle planning
- Understanding where digitalisation creates operational value
Class 4 : From Pilot to Network Impact : Scaling and Proving ITS Value
Thursday, 17 September 2026
Delivering Governance, Funding and Long-Term Infrastructure Stewardship
Key topics:
- Embedding asset management into organisational culture and governance
- Aligning technical priorities with funding realities
- Procurement and delivery models supporting long-term performance
- Integrating maintenance, safety and resilience programmes
- Performance-Based Contracts (PBCs) and outcome-oriented maintenance delivery
- Building investment cases for maintenance and rehabilitation
- Communicating infrastructure risks and funding needs to decision-makers
- Scaling modern asset management approaches in LMICs
- Common implementation pitfalls and institutional barriers
- Future trends in infrastructure stewardship and intelligent asset management
Course Instructor

