Appraising the potential for platooning in the U.S.

  • 13-Jul-2017 08:12 EDT

In March 2017, Volvo Trucks and Partners for Advanced Transportation Technology (PATH) at the University of California, Berkeley completed a successful demonstration of partially automated truck platooning. (image: Volvo Trucks)

Connected and automated vehicles (CAVs) are receiving significant attention as a technology solution to realize safer, more cost-effective and efficient operation of several transportation systems. CAVs can also potentially help curb energy consumption and greenhouse gas (GHG) emissions from the transportation sector. One of the most promising CAV technologies that could experience widespread adoption in the next five to 10 years in the U.S. is platooning for combination trucks.

Platooning is a demonstrated method of groups of vehicles travelling close together actively coordinated in formation at high speed that has the potential to reduce energy consumption resulting from aerodynamic drag. Trucks are ideal applications for platooning because of their technical characteristics and mode of operation (several vehicles driving for long distances along the same route, often concentrated in few corridors).

Combination trucks account for the majority of the energy use in the U.S. freight sector (64.9% of freight, and 4.8% of total U.S. energy use in 2013) and an even larger share of GHG emissions (77.1% of freight, and 7.5% of total U.S. GHG emissions in 2013). Looking at the future, the importance of trucking on the U.S. energy use and GHG emissions is likely to increase, due mainly to three factors:

• Freight transport has been growing more rapidly than passenger transport, and the trend is likely to continue in the future

• A continued increase in the share of trucking in total freight activity

• Transportation, and freight in particular, is more expensive to decarbonize compared to other sectors, and will experience lower energy and GHG emissions reduction in response to economy-wide climate change mitigation measures.

Estimating ‘platoonable’ miles

Several studies have been focusing on assessing the potential savings achievable by platooning operations for a group of two or more trucks, as well as extrapolating these savings on a national scale, based on overall miles traveled by trucks. However, a key element has been neglected in the existing literature: what is the “platoonable” fraction of traveled miles during real-world operations? Namely, in a fleet of trucks, what fraction of miles driven is amenable for platooning operation? Clearly not every mile driven can be driven in a platoon formation, and platooning operations at low speeds do not lead to significant fuel saving.

However, for large trucks operating extensively on highways over long distances, the fraction of platoonable miles at high speed can be significant.

Researchers from the National Renewable Energy Laboratory (NREL) conducted an estimation of the platoonable fraction of miles driven by combination trucks in the United States based on more than 3 million miles of driving data collected across a variety of fleet operators, truck manufacturers, times of operation, and regions. The data considered have been collected directly by NREL and other partners who have contributed data to NREL’s Fleet DNA database using onboard data logging devices or telematics systems.

National impact and future work

In 2014, 169.8 billion miles were driven by combination trucks in the United States, consuming a total of 29.1 billion gallons of fuel and emitting approximately 6.9 billion metric tons of carbon dioxide equivalent. Based on the NREL researchers’ analysis, approximately 65.6% of those miles could potentially be driven in platoon formation. Assuming an energy (and emissions) savings of approximately 6.4% for each team of platooned vehicles (based on efficiency improvements previously published in a platooning benefits study), widespread adoption of platooning operations can potentially reduce trucks’ energy use by approximately 4.2%.

With these bounding assumptions, the widespread adoption of platooning operations for combination trucks in the U.S. could lead to a total savings of 1.5 billion gallons of petroleum-derived fuels (equal to 1.1% of the current U.S. import of oil: 2.7 billion barrels in 2015) and 15.3 million metric tons of CO2 (a 0.22% emissions reduction) per year.

The best combined result for platooning operations, according to the previous study, was at 55 mph (90 km/h) and a 30-ft (9-m) following distance. In future applications, platooning fuel savings can be enhanced by addressing barriers to closer platoon formation—such as reduced engine cooling—and by including more vehicles in each platoon. Additional benefits of truck platooning, such as road capacity optimization and accidents reduction, as well as other truck safety and operational considerations have been well documented.

A split-duty combination truck that runs local pickup and delivery trips during the day and regional line-haul operation at night (representing the majority of the miles driven) is an ideal application for platoon operations. For such targeted applications, which are likely to be early adopters of connected and automated technologies, the fraction for platoonable miles increases to approximately 76.6%. A more comprehensive “Big Data” analysis considering a larger data set that covers multiple years and a wider array of applications is planned to further refine this estimate.

This technical potential study presents an upper bound because in the real world, truck and fleet operators may not be willing to participate to platoon operations under all the conditions considered here (e.g., an operator might not be willing to wait to form a platoon). Therefore, NREL researchers plan to perform an expert elicitation study involving truck owners and fleet operators to assess the overall willingness to participate in platooning and the main barriers for the widespread adoption of this technology.

This article is based on SAE International technical paper 2017-01-0086 by Matteo Muratori, Jacob Holden, Michael Lammert, Adam Duran, Stanley Young, and Jeffrey Gonder of the National Renewable Energy Laboratory. The paper was presented as part of the “Intelligent Transportation Systems” technical session at WCX17 World Congress Experience.

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