Problem Solved: Computer Vision is Generating Data for Road Pavement Management

Road Pavement Repair
Markus Melander
Head of Business Development, Computer Vision Solutions
Feb 12th 2019
Road Weather
Artificial Intelligence (AI)

All around the globe, roads rank among the most important assets for nations, facilitating economies and allowing governments to manage internal logistics. Neglecting road maintenance has far-reaching detrimental effects in areas as diverse as agriculture, education, and rural development, as detailed by the EU parliament's report: EU Road Surfaces: Economic and Safety Impact of the Lack of Regular Road Maintenance.

Climate change has a direct impact on these vital pieces of infrastructure by creating icing and melting cycles that nibble away at asphalt, much in the same way that rust corrodes iron. In warmer climates, sun does equally destructive damage, where ultra-violet rays weaken the chemical bonds which give asphalt its strength. With climate change posing a growing, open-ended problem, and maintenance budgets being constantly challenged, the question becomes: in order to protect our precious transportation network, how can we do more with less money? 

Typical pavement management budgets range from roughly €4,000 - €5,000 per kilometer. Finland, for example, has a re-surfacing budget of €270 M for around 51,000 km of paved state roads. The European road maintenance economy, meanwhile, is valued at about €21 B. With this amount of annual spending, the opportunity certainly exists to keep roads in better shape. In order to maximize the value of each euro spent, governments must identify the areas of investment with the highest overall impact and carefully allocate budgets accordingly. (Cost estimates from International Road Federation, IRF and Finnish Transport Infrastructure Agency, FTIA)

Vaisala's computer vision powered data collection platform, RoadAI, is designed with this task in mind. RoadAI leverages wireless connectivity and cloud technology to make safe, continuous data generation possible for entire road teams or fleet of vehicles through the upload of real-time visual information. The system provides automated, computer vision based condition analysis. Easy data collection and superior data quality is providing better capabilities to manage pavement rehabilitation processes in all the organization’s levels. Whether in field operations or funding allocation, RoadAI empowers everyone from highway engineers to policy-makers to make more informed decisions by bringing objective situational awareness into planning processes. The problem of road maintenance -- and with it, the bigger picture of managing infrastructure, public transportation, and more -- is a massive task facing governments worldwide. With RoadAI, there's interesting tool that can help with important work fixing road defects based on quality data.

If this post inspires you, contact us and we tell you how technology can support you or your organization in the field and in the office. Please take also look to the following video to learn how the RoadAI system works.

Markus Melander, Head of Business Development, CV Solutions

Markus Melander

Head of Business Development, Computer Vision R&D

Markus is responsible for commercialization of Vaisala´s computer vision based services for roads and rails. Markus holds a Masters degree in technological entrepreneurship from Lappeenranta University of Technology. He is a former officer of Finnish Defence Forces and has been the head for Digitalization Program and multiple ICT projects in the Finnish Transportation Agency (FTA). Markus was also a co-founder and CEO of Vionice (acquired by Vaisala in 2017).

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