Fuel-Efficient Driving Strategies for Heavy-Duty Vehicles: A Platooning Approach Based on Speed Profile Optimization

A method for reducing the fuel consumption of a platoon of heavy-duty vehicles (HDVs) is described and evaluated in simulations for homogeneous and heterogeneous platoons. The method, which is based on speed profile optimization and is referred to as P-SPO, was applied to a set of road profiles of 10 km length, resulting in fuel reduction of 15.8% for a homogeneous platoon and between 16.8% and 17.4% for heterogeneous platoons of different mass configurations, relative to the combination of standard cruise control (for the lead vehicle) and adaptive cruise control (for the follower vehicle). In a direct comparison with MPC-based approaches, it was found that P-SPO outperforms the fuel savings of such methods by around 3 percentage points for the entire platoon, in similar settings. In P-SPO, unlike most common platooning approaches, each vehicle within the platoon receives its own optimized speed profile, thus eliminating the intervehicle distance control problem. Moreover, the P-SPO approach requires only a simple vehicle controller, rather than the two-layer control architecture used in MPC-based approaches.

[1]  Erik Hellström,et al.  A Real-Time Fuel-Optimal Cruise Controller for Heavy Trucks using Road Topography Information , 2006 .

[2]  Roberto Horowitz,et al.  Safe Platooning in Automated Highway Systems Part I: Safety Regions Design , 1999 .

[3]  Wolf-Heinrich Hucho,et al.  Aerodynamics of Road Vehicles: From Fluid Mechanics to Vehicle Engineering , 2013 .

[4]  Xiaoliang Ma,et al.  Fast Algorithm for Planning Optimal Platoon Speeds on Highway , 2014 .

[5]  Ioannis Kanellakopoulos,et al.  Variable time headway for string stability of automated heavy-duty vehicles , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[6]  Ioannis Kanellakopoulos,et al.  Nonlinear spacing policies for automated heavy-duty vehicles , 1998 .

[7]  Rajesh Rajamani,et al.  On spacing policies for highway vehicle automation , 2003, IEEE Trans. Intell. Transp. Syst..

[8]  J.K. Hedrick,et al.  Longitudinal Vehicle Controller Design for IVHS Systems , 1991, 1991 American Control Conference.

[9]  Mattias Wahde,et al.  Fuel consumption optimization of heavy-duty vehicles using genetic algorithms , 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).

[10]  Roberto Horowitz,et al.  Safe Platooning in Automated Highway Systems , 1997 .

[11]  Sina Torabi,et al.  Fuel-Efficient Truck Platooning using Speed Profile Optimization , 2017 .

[12]  Pravin Varaiya,et al.  Automated Highway System Experiments in the Path Program , 1993, J. Intell. Transp. Syst..

[13]  Karl Henrik Johansson,et al.  Control of platoons of heavy-duty vehicles using a delay-based spacing policy , 2015 .

[14]  Karl Henrik Johansson,et al.  Cooperative Look-Ahead Control for Fuel-Efficient and Safe Heavy-Duty Vehicle Platooning , 2015, IEEE Transactions on Control Systems Technology.

[15]  Karl Henrik Johansson,et al.  An experimental study on the fuel reduction potential of heavy duty vehicle platooning , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[16]  Luca Caltagirone,et al.  Truck Platooning Based on Lead Vehicle Speed Profile Optimization and Artificial Physics , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[17]  Bo Egardt,et al.  Cooperative energy management of automated vehicles , 2016 .

[18]  Assad Alam,et al.  Fuel-Efficient Heavy-Duty Vehicle Platooning , 2014 .

[19]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[20]  H. Fritz,et al.  Longitudinal and lateral control of heavy duty trucks for automated vehicle following in mixed traffic: experimental results from the CHAUFFEUR project , 1999, Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328).

[21]  Michael Henzler,et al.  Optimal parameter selection of a Model Predictive Control algorithm for energy efficient driving of heavy duty vehicles , 2015, 2015 IEEE Intelligent Vehicles Symposium (IV).

[22]  Karl Henrik Johansson,et al.  Look-ahead cruise control for heavy duty vehicle platooning , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[23]  Erik Hellström,et al.  Look-ahead Control for Heavy Trucks to minimize Trip Time and Fuel Consumption , 2007 .

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