Microsimulation Framework to Explore Impact of Truck Platooning on Traffic Operation and Energy Consumption : Development and Case Study

Cooperative adaptive cruise control (CACC) systems have the potential to improve traffic flow and energy consumption efficiency, but these effects are challenging to estimate. This report presents the development of a micro-simulation model to represent these impacts for heavy trucks using CACC when they share a freeway with manually driven passenger cars. The simulation incorporates automated truck following models which have been derived from experimental data recorded on heavy trucks driven under CACC, adaptive cruise control (ACC), and conventional cruise control (CC). The simulation includes other behavioral models for lane changing, lane change cooperation and lane use restrictions for trucks to better capture realworld traffic dynamics. The developed simulation model was used to conduct a case study for a 15-mile urban freeway corridor with heavy truck traffic and significant congestion. Effects of truck CACC on traffic operation and energy consumption were studied. Simulation results show that truck CACC improved traffic operations for trucks in terms of Vehicle Miles Traveled (VMT), average speed and flow rate. In addition, truck CACC did not adversely affect passenger car operations and in some locations it even produced considerable improvements in the general traffic conditions. A procedure was developed based on the Motor Vehicle Emission Simulator (MOVES) to estimate energy savings for in-platoon trucks. MOVES was re-calibrated using experimental data; and the calibrated MOVES was used to estimate energy saving rates for conditions that have not been covered in the experimental data, but that may occur in a simulation. The procedure was integrated with the microsimulation to study the same 15-mile urban freeway corridor. Results showed that energy consumption per VMT decreased for trucks. The energy consumption decrease originates only partially from aerodynamic drag reduction but primarily from congestion reduction due to platooning.

[1]  P. G. Gipps,et al.  A behavioural car-following model for computer simulation , 1981 .

[2]  Hans Fritz,et al.  Fuel Consumption Reduction in a Platoon: Experimental Results with two Electronically Coupled Trucks at Close Spacing , 2000 .

[3]  Gordon F. Newell,et al.  A simplified car-following theory: a lower order model , 2002 .

[4]  Steven E. Shladover,et al.  Effects of Adaptive Cruise Control Systems on Highway Traffic Flow Capacity , 2002 .

[5]  Lily Elefteriadou,et al.  REVIEW OF TRUCK CHARACTERISTICS AS FACTORS IN ROADWAY DESIGN , 2003 .

[6]  Alexander Skabardonis,et al.  Traffic Analysis Toolbox Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software , 2004 .

[7]  M. Barth,et al.  Heavy-Duty Diesel Vehicle Fuel Consumption Modeling Based on Road Load and Power Train Parameters , 2005 .

[8]  Bart van Arem,et al.  The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics , 2006, IEEE Transactions on Intelligent Transportation Systems.

[9]  James L Pline Traffic engineering handbook , 2009 .

[10]  Dirk Helbing,et al.  Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[11]  Stephan Müller The Impact of Electronic Coupled Heavy Trucks on Traffic Flow , 2012 .

[12]  Jean-Paul M. Arnaout,et al.  Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation , 2014 .

[13]  Steven E Shladover,et al.  Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data , 2014 .

[14]  Adam Duran,et al.  Effect of Platooning on Fuel Consumption of Class 8 Vehicles Over a Range of Speeds, Following Distances, and Mass , 2014 .

[15]  Karl H. Johansson,et al.  Heavy-Duty Vehicle Platooning for Sustainable Freight Transportation: A Cooperative Method to Enhance Safety and Efficiency , 2015, IEEE Control Systems.

[16]  Xiao-Yun Lu,et al.  Cooperative Adaptive Cruise Control (CACC) for Truck Platooning: Operational Concept Alternatives , 2015 .

[17]  Eric Chan,et al.  SARTRE Automated Platooning Vehicles , 2016 .

[18]  Sabina Jeschke,et al.  A Review of Truck Platooning Projects for Energy Savings , 2016, IEEE Transactions on Intelligent Vehicles.

[19]  Qichen Deng A General Simulation Framework for Modeling and Analysis of Heavy-Duty Vehicle Platooning , 2016, IEEE Transactions on Intelligent Transportation Systems.

[20]  Brian R. McAuliffe,et al.  Fuel-economy testing of a three-vehicle truck platooning system , 2017 .

[21]  Xiao-Yun Lu,et al.  Integrated ACC and CACC development for Heavy-Duty Truck partial automation , 2017, 2017 American Control Conference (ACC).

[22]  Dali Wei,et al.  An Enhanced Microscopic Traffic Simulation Model for Application to Connected Automated Vehicles , 2017 .

[23]  Hao Liu,et al.  Impact of cooperative adaptive cruise control on multilane freeway merge capacity , 2018, J. Intell. Transp. Syst..