Using Low-Cost Radar Sensors and Action Cameras to Measure Inter-Vehicle Distances in Real-World Truck Platooning  
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1 Department of Civil and Environmental Engineering, Norwegian University of Science and Technology (NTNU), NO-7491 Trondheim, Norway 1  
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2 Research Division Strategic Analyses and Joint Systems, Norwegian Defence Research Establishment (FFI), NO-2027 Keller, Norway 2  
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1 Department of Civil and Environmental Engineering, Norwegian University of Science and Technology (NTNU), NO-7491 Trondheim, Norway 13 Department of Humans and Automation, Institute for Energy Technology (IFE), NO-1751 Hilden, Norway 3  
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4 Norwegian Public Roads Administration (NPRA), NO-7031 Trondheim, Norway 4  
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1 Department of Civil and Environmental Engineering, Norwegian University of Science and Technology (NTNU), NO-7491 Trondheim, Norway 1  
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on which more research is needed to establish the feasibility of truck platooning. Public roads authorities govern the design and operations of the road network and may thus be important facilitators of truck platooning. As Norway is a small automotive market with conditions for automated vehicles, the Norwegian Public Roads Administration (NPRA) have taken a proactive role in trialing advanced transportation technologies, exemplified by the Borealis testbed [6] and the ongoing MODI project [7], which aims to demonstrate automated trucking between the Netherlands and Norway within 2026. In general, the shorter inter-vehicle distances are between platooning trucks, the greater are the resulting benefits in terms of fuel savings and potential road capacity improvements. Thus, the greater the stability of inter-vehicle distances over time, the more beneficial platooning will be [8]. However, during real-world driving, combinations of external traffic, road alignment and truck weight differences will influence the inter-vehicle distances, and thus also the extent of benefits unlocked [9; 10]. Moreover, the extent to which truck platoons impact surrounding traffic depends partly on their total length, which is influenced by inter-vehicle distances. By implication, inter-vehicle distance data will be important for public roads authorities when regulating truck platooning, such as when deciding on which road sections platoons should be allowed, and the maximum number of trucks which can platoon together. However, such data may not be easily accessible, and even if they were, it is unclear how they should be contextualized and analyzed. In the field studies organized through the large, aforementioned platooning projects, truck manufacturers and transport companies have typically facilitated and allowed for the collection of inter-vehicle distance measurements using integrated vehicle sensors. While integrated distance sensors could also be cameras and lidars [11], radar sensors are most often used, as they are affordable, computationally simple and robust under adverse light and weather conditions [11; 12; 13; 14; 15]. This is despite issues with clutter [16] and ghosting [17], referring to unwanted signals that distort and interfere with the desired detection, and the detection of non-existent targets which are difficult to distinguish from real ones. If allowed, using data from integrated vehicle sensors is very convenient, as they are already collected as real-time inputs to platooning control systems, removing the need for using aftermarket distance sensors. However, manufacturers often use proprietary algorithms for data processing, defining message codes [18] to encrypt collected data. This makes external individuals unable to access them, unless authorized to do so. Smaller truck platooning field studies may not have the benefit of truck manufacturers participating as partners.