Monitoring the weight of heavy traffic, such as trucks, using highways – and particularly bridges – is gaining more traction worldwide as infrastructure ages and its structural health presents pressing difficulties.
“Road operators are facing increasing challenges related to the ageing of the infrastructure, especially when looking into bridge infrastructure,” says David Cornu, head of business unit traffic solutions at Kistler.
It is a problem tailor-made for Weigh in Motion (WiM) companies. “More and more bridges are showing increased structural deficiencies and approaching in a fast pace their end of service life,” Cornu adds. “WiM has proved to be a strong means to identify overloaded vehicles. For the upcoming years we expect a further push into the deployment of automatic WiM enforcement sites, where trucks are automatically fined in case of overloading. This will enable efficient protection of the bridge infrastructure and at the same time an increase in traffic safety. In combination with our bridge structural health monitoring systems, the health and strength of a bridge structure can be fully assessed and monitored over time, to ensure a safe operation 24/7 and to allow a safe extension of its service life.”
“Customers are recognising that there are problems on bridges caused by overloaded vehicles” Florian Weiss, Traffic Data Systems
Direct enforcement is one area of WiM that could provide impetus for companies in the sector – but some are still waiting for its promise to be realised. “I had high hopes that direct enforcement would move WiM forward,” admits Florian Weiss, CEO and owner of WiM specialist Traffic Data Systems. “We haven’t seen that yet.”
But Weiss has certainly seen the importance of WiM rise in terms of bridge maintenance. “Authorities are realising that infrastructure is important: in particular customers are recognising that there are problems on bridges caused by overloaded vehicles,” Weiss continues. “WiM is a way of monitoring real weights on bridges. I see a shift in 2024 from statistics - the simple vehicle-counting approach - to actual monitoring.”
The extra data this gives you is vital, he says: “In order to find a solution, you need to know how a bridge is really used. In many countries they have a sufficient amount of traffic counters – but is a tractor with a trailer empty? Half-loaded? Overloaded? This is the information you can only get from WiM, not a traffic counter.”
In much the same way, authorities are realising that the costs of not doing anything are out of proportion with the alternative, he says. “If you take the cost of replacing, say, 300m of a six-lane motorway with the cost of implementing a WiM system – it’s nothing!”
Leonardo Guerson, WiM product manager and application engineer at Intercomp, is seeing high quality WiM data increasingly used for traffic input in road asset management, particularly in pavement design and maintenance. “This development is propelled by the availability of cost-effective, high-accuracy WiM sensors in the market, allowing for the establishment of an adequate number of WiM sites to collect representative data,” Guerson explains. “Access to precise traffic load data reduces the need for estimations, significantly enhancing the accuracy of infrastructure designs and maintenance actions aligned with infrastructure demands. By utilising high-accuracy data collection sensors, end users not only enhance the reliability of their datasets but also reduce ownership costs, thanks to less frequent recalibrations and sensor replacements.”
“Precise traffic load data reduces the need for estimations, significantly enhancing the accuracy of infrastructure designs and maintenance” Leonardo Guerson, Intercomp
Václav Blahník, product manager of WiM at Cross Zlín, points to what the company sees as a “probably very turbulent” year ahead. Perhaps this turbulence will open the door for WiM companies which are happy to embrace complication on behalf of their customers.
“For this reason, we will get more complex implementations, including additional technologies like laser scanning, profiling, RFID vehicle detection etc,“ Blahník says. “Due to this, we expect also further requirements to integrate WiM systems into superior ITS systems.“
International Road Dynamics, meanwhile, sees a growing need to enhance road safety by identifying tyre types and tyre anomalies. “We believe that, in 2024, the requirements for tyre anomaly detection will continue to grow and play a pivotal role in the industry,” insists CEO Rish Malhotra.
IRD’s Tire Anomaly and Classification System measures tyre width and detects problems, as well as classifying vehicles based on their tyre properties. “From a law enforcement perspective, this well-adopted technology provides significant advantages, enabling authorities to identify and manage safety risks more effectively, thereby predicting and preventing road accidents,” Malhotra says. “Given the growing demand from commercial vehicle enforcement agencies, this outlook, when coupled with the power of AI will deliver innovative solutions to improve truck safety. These will continue to align with IRD’s mission to champion safer and more efficient roadways worldwide. The combination of machine learning, deep neural networks and computer vision provides opportunities to address in new ways an increasing range of functions that are a part of commercial vehicle operations.”
“We expect a further push into the deployment of automatic WiM enforcement sites, where trucks are automatically fined in case of overloading” David Cornu, Kistler
The International Society for Weigh in Motion (ISWiM) represents researchers, vendors and end-users of WiM technology, both infrastructure- and vehicle-based. In November it held a conference in Brisbane, Australia, with the International Forum for Heavy Vehicle Transport & Technology (HVTT Forum), which promotes and supports the development of road freight transport technology, safety and policy and to facilitate information exchange between researchers, policy makers, regulators, road agencies and the transport industry.
Andy Lees, Q-Free independent consultant on WiM and information officer for ISWiM, was at the event and points to another trend which is opening up. “The improvement in vehicle classification for WiM has long been a goal and the recent introduction of loop profiling is starting to make inroads into this issue,” he says. “In fact, a paper was presented at the recent Technology Convergence conference in Brisbane on this very topic.”
But it is the newest of technologies which will really start to make this sing. “The application of AI is now enhancing this process by using neural networks to help improve the complex algorithms used to determine vehicle types,” Lees says. “The advantages of adopting machine learning techniques for this process are numerous and varied. The end user is provided with enhanced identification and categorisation methods which would otherwise be unobtainable, such as electric vehicle identification, vehicles with raised axles, low platform versus box trailers versus tanker trailers to name but a few.”
