It’s the most promising concept for making freight transport faster, more productive, safer and greener: truck platooning. This is a technology in which trucks drive in a platoon (convoy) just short distances apart. In order to gain the greatest benefit from this technology, however, the trucks must be able to locate each other on the road. In the Truck Platoon Matching project, TNO is collaborating with various partners to develop a solution that makes this possible.
Truck platooning is an up-and-coming technology. This approach can enable trucks to save time and improve fuel efficiency with ten percent. Thanks to a Wi-Fi link between the trucks they can brake and accelerate at the same time, thus preventing jerky changes in speed and the tailbacks that arise from this. What’s more, the motorway will probably become safer for all road users. It’s expected that this technology will appear on the market around 2020. In order to gain the maximum benefits from the technology at this time, trucks equipped in this manner will need to be able to locate each other. In addition they need to know whether travelling the road together is actually worthwhile: if a partner has to head off in a different direction at the first exit, then there is little point in forming a platoon.
The heaviest load at the front
“The Truck Platoon Matching project is all about bringing the right trucks together,” explains project leader Robbert Janssen of TNO. “The trucks all have to be going in the same direction, of course, but the loads have to be known as well. That’s because it’s best to have the truck with the heaviest load travelling at the front. The engine powers and the braking capacity levels have to be roughly similar as well, because the trucks must be able to brake and accelerate at more or less the same speed.” If all these factors match up, then the current locations and travelling speeds of the trucks must also permit them to form a platoon. Waiting for a long time or making large detours will negate the advantages of driving together. In short, Truck Platoon Matching requires the availability of lots of real time data as well as complex calculation methods for processing this data.
“The business case isn’t based only on the fuel saving for the transport companies, but also on greater safety, less traffic congestion, reduced emissions and a better traffic flow”
Two matching methods
The project, which started a year ago, involves two matching methods. The first method finds matches before the journey starts, on the basis of existing plannings. “There are various locations in the Netherlands where many trucks start their journey,” says Theodoor Torn of Ortec, the software optimization company that is developing this method. “These include container terminals, auction houses and large distribution centres. Using the data from the transport companies you can calculate what the benefits will be if several trucks set off from one of these points at the same time.” The second method, on-the-fly matching, has been developed by TNO and enables matches to be found during the journey. If a truck is already halfway along its route and it turns out there is another truck with roughly the same destination in the vicinity, then the system links them up. Ultimately the aim is to combine both methods in a single cloud solution.
Collaboration the key to success
The project is bringing promising results. Although the matching methods have so far only been tested with simulation models, there are good grounds for developing them further into a workable prototype. According to Bob Dodemont, the programme manager at the Port of Rotterdam Authority, the key to success is that so many representatives from the sector are collaborating in this project. “It’s not a purely scientific exercise. Our clients are clearly involved in the research and have been able to input their know-how, wishes and requirements. You can really see how this innovation serves a range of interests. It’s a good fit for SmartPort, the partnership institute that aims to make Rotterdam the smartest and best port in the world.”
Feedback based on practical experience
Some freight companies provided the data from their on-board units. In view of the relatively closed nature of the sector this is quite notable, but Kees Overbeek of container transport firm Overbeek was full of enthusiasm right from the start. “This can save plenty of costs in the future. We provided important feedback based on practical experience. To give one example, we pointed out that it’s not efficient to stand motionless for a long time in order to enable a match. You save fuel, that’s true, but the driver time constitutes half of the costs.”
“We want to expand the algorithm to include the drivers’ rest times”
Expanding the algorithm
The follow-up project is already underway. New insights gained during the first project are now being integrated in an initial prototype of the tool that will take things a step closer to the market. “We want to expand the algorithm to include the drivers’ rest times, for instance,” says Janssen. “There’s not much point in platooning if the driver has to take a break after a quarter of an hour. On the other hand, the break can be used to wait for a platoon partner.”
Major collective benefit
Besides TNO, nine other parties took part in the first project: De Jong-Grauss Transport, De Rijke Trucking, Erasmus University Rotterdam, Port of Rotterdam Authority, Ortec, Overbeek Int. Transport, SmartPort Rotterdam, Transport en Logistiek Nederland and VDS Logistics. In the second phase of the project these are being joined by Simacan, Route42, Calendar42 and Innovatiecentrale. According to Torn, the popularity of the project illustrates that ever more parties are grasping its significance. “It’s important that logistics grow increasingly smart so that we can use our resources more efficiently. The business case isn’t based only on the fuel saving for the transport companies, but also on greater safety, less traffic congestion, reduced emissions and a better traffic flow. So there’s a major collective benefit.”
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