Connected and Automated Trucks
NREL's connected and automated vehicle (CAV) research for trucks focuses on data collection, modeling and simulation, and analysis of fuel-saving solutions such as truck platooning and eco-routing.

Truck Technology Development and Evaluations
NREL researchers pair advanced modeling and simulation capabilities with real-world commercial vehicle operating data from NREL's FleetDNA data warehouse to evaluate a wide range of advanced truck technologies.
In addition to modeling and simulation, our researchers identify representative public road sections for fleet performance evaluation. This allows us to conduct comprehensive, well-documented on-road truck evaluation campaigns subject to real-world conditions.
Fuel-Efficient Routing
NREL researchers investigate the potential to maximize energy savings by identifying the most fuel-efficient routes for vehicle travel. We develop models to assess how CAVs can achieve maximum mobility with minimum energy consumption, and emulate real-world traffic dynamics using microsimulations to evaluate the energy impacts of CAVs.
These analyses help fleet owners, operators, and managers identify operational shifts that further leverage the energy efficiencies represented by CAV technologies.
Truck Platooning
Vehicle automation is a promising fuel-saving strategy, and truck platooning has emerged as a likely contender to reduce harmful emissions from the heavy-duty vehicle sector. Platooning, or electronically linking trucks into groups, allows multiple vehicles to accelerate or brake simultaneously and reduces aerodynamic drag to create significant energy and fuel savings.
Large-scale temporal and geospatial analysis performed by NREL has indicated that 63% of the total miles driven by Class 8 trucks in the United States occur at speeds amenable to platooning.
NREL conducts a variety of studies to assess the fuel-saving potential of vehicle platooning.
Fuel-Saving Assessments
In collaboration with industry partners, NREL conducts extensive track and on-road evaluation campaigns to assess the fuel-saving potential of two- and three-truck platoons.
Using computer vision, we can identify and analyze the fuel-use impacts of speed variations, road curvature, other vehicles cutting in and out of the platoon, the use of mismatched vehicles (i.e., trucks with standard and aerodynamic trailers in the same platoon), and the presence of passenger vehicles traveling in front of platoons.
Our rigorous analysis can pinpoint fuel savings for both lead and trailing trucks. These reductions in fuel use and improvements to energy efficiency can prove attractive for long-haul fleet managers interested in reducing fleet costs.
Other analyses include:
- Speed, Following Distance, and Mass Impacts: Researchers pinpoint optimal conditions—including varying steady-state speeds, following distances, ambient temperatures, and gross vehicle weights—that improve vehicle fuel economy for truck platoons.
- Lateral Alignment Impacts: Researchers evaluate the impacts of vehicle alignment in truck platoons and determine optimal vehicle spacing for increased energy savings.
- Mixed Traffic Impacts: Researchers investigate the energy-saving impact of multiple-passenger-vehicle patterns ahead of and adjacent to the platoon, cut-in and cut-out maneuvers by other vehicles, transient traffic, and the use of mismatched platooned vehicles.
- Thermal Impacts: Researchers explore the tradeoffs between various airflow strategies for engine cooling and the aerodynamic-enabled fuel savings of platooning.
Deployment Potential Analyses
Researchers at NREL analyze real-world data sourced from Fleet DNA and independent truck platooning projects to assess the potential for commercially available heavy-duty trucks to operate in platoons.
Future Research
Using wind tunnel evaluations, computational fluid dynamics simulations, and analysis of independent truck platooning efforts, NREL researchers have identified areas in need of additional research:
- Close formation and longer-distance effects
- Aerodynamic packages optimized for platooning
- Measurement of platoon system performance in various traffic conditions
- Impact of vehicle lateral offsets
- Characterization of the national potential for platooning based on fleet operational characteristics.
Data and Tools
The following NREL data and tools support CAV research and analysis:
FleetREDI: Fleet Research, Energy Data, and Insights
Fleet DNA: Commercial Fleet Vehicle Operating Data
FASTSim: Future Automotive Systems Technology Simulator
HIVE: Highly Integrated Vehicle Ecosystem Simulation Framework
RouteE: Route Energy Prediction Model
Publications
Analysis of the Unsteady Wakes of Heavy Trucks in Platoon Formation and Their Potential Influence on Energy Savings, SAE International Technical Paper (2021)
Decision Tree Regression To Identify Representative Road Sections for Evaluating Performance of Connected and Automated Class 8 Tractors, SAE International Technical Paper (2021)
Co-Optimization of Vehicles and Routes (CoVaR), PACCAR Technical Center Presentation (2021)
Advancing Platooning With ADAS Control Integration and Assessment Test Results, SAE World Congress (2021)
Impact of Lateral Alignment on the Energy Savings of a Truck Platoon, SAE World Congress (2020)
Impact of Mixed Traffic on the Energy Savings of a Truck Platoon, SAE World Congress (2020)
Impact to Cooling Airflow from Truck Platooning, SAE World Congress (2020)
Exploring Telematics Big Data for Truck Platooning Opportunities, SAE World Congress (2020)
Influences on Energy Savings of Heavy Trucks Using Cooperative Adaptive Cruise Control, SAE World Congress (2020)
Contact
To learn more about our connected and automated vehicle research or explore partnership opportunities, please reach out.
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