Ecological Cooperative Look-Ahead Control for Automated Vehicles Travelling on Freeways With Varying Slopes

Higher fuel economy standards and more stringent limitations on greenhouse gas emissions for ground vehicles have been made due to public concerns about energy crisis and environmental issues. By organizing a group of automated vehicles into a platoon at a short intervehicular distance, the overall fuel consumption and greenhouse gas emissions of vehicle platoon can be decreased due to reduced aerodynamic drag, which is called the platooning technology. In addition, the eco-driving technology can help further increase the fuel efficiency of vehicle platoon by optimizing speed trajectories of vehicles. However, little research has been done into the combination of the eco-driving and platooning technologies. Based on distributed model predictive control (DMPC), this paper proposes an ecological cooperative look-ahead control strategy for a platoon of automated vehicles travelling on a freeway with varying slopes, where both the eco-driving and platooning technologies are used. To maximize the fuel efficiency of vehicle platoon, an ecological cooperative look-ahead control problem (Eco-CLC) is first formulated based on DMPC, where rotational inertia coefficient related to reduction ratio of gear box, aerodynamic drag related to spacing and model constraints are considered. Since the Eco-CLC problem is a nonconvex and nonlinear optimization problem with hard state constraints, it is very difficult to quickly obtain its optimal solution. To enhance real-time control performance, after the hard state constraints of the Eco-CLC problem are transformed into parts of the multi-objective function using the band-stop function, the improved ecological cooperative look-ahead control (iEco-CLC) based on DMPC is given. A particle swarm optimization algorithm with multiple dynamic populations is further presented to quickly solve the iEco-CLC problem online. Simulation results demonstrate, compared with benchmarks, the proposed strategy can save more than 21% of fuel for vehicle platoon.

[1]  Bing Liu,et al.  V2X-Based Decentralized Cooperative Adaptive Cruise Control in the Vicinity of Intersections , 2016, IEEE Transactions on Intelligent Transportation Systems.

[2]  Zeyu Chen,et al.  Particle swarm optimization-based optimal power management of plug-in hybrid electric vehicles considering uncertain driving conditions , 2016 .

[3]  Peter H. Bauer,et al.  Adaptive Multiresolution Energy Consumption Prediction for Electric Vehicles , 2017, IEEE Transactions on Vehicular Technology.

[4]  Fei Luo,et al.  A Switched Control Strategy of Heterogeneous Vehicle Platoon for Multiple Objectives With State Constraints , 2019, IEEE Transactions on Intelligent Transportation Systems.

[5]  Hai Le Vu,et al.  Characterising Green Light Optimal Speed Advisory trajectories for platoon-based optimisation , 2017 .

[6]  Hannes Hartenstein,et al.  VANET: Vehicular Applications and Inter-Networking Technologies , 2010, VANET.

[7]  David M. Bevly,et al.  An Evaluation of the Fuel Economy Benefits of a Driver Assistive Truck Platooning Prototype Using Simulation , 2016 .

[8]  Bo Cheng,et al.  Instantaneous Feedback Control for a Fuel-Prioritized Vehicle Cruising System on Highways With a Varying Slope , 2017, IEEE Transactions on Intelligent Transportation Systems.

[9]  Richard H. Middleton,et al.  Leader tracking in homogeneous vehicle platoons with broadcast delays , 2014, Autom..

[10]  Wencong Su,et al.  Distance-Based Ecological Driving Scheme Using a Two-Stage Hierarchy for Long-Term Optimization and Short-Term Adaptation , 2017, IEEE Transactions on Vehicular Technology.

[11]  Hui Cheng,et al.  Autonomous coordinated control of a platoon of vehicles with multiple disturbances , 2014 .

[12]  Alden H. Wright,et al.  Genetic Algorithms for Real Parameter Optimization , 1990, FOGA.

[13]  Shang-Jeng Tsai,et al.  Efficient Population Utilization Strategy for Particle Swarm Optimizer , 2009, IEEE Trans. Syst. Man Cybern. Part B.

[14]  Xun Gong,et al.  Fast Nonlinear Model Predictive Control on FPGA Using Particle Swarm Optimization , 2016, IEEE Transactions on Industrial Electronics.

[15]  Jianqiang Wang,et al.  Stabilizing Periodic Control of Automated Vehicle Platoon With Minimized Fuel Consumption , 2017, IEEE Transactions on Transportation Electrification.

[16]  Yang Zheng,et al.  Distributed Model Predictive Control for Heterogeneous Vehicle Platoons Under Unidirectional Topologies , 2016, IEEE Transactions on Control Systems Technology.

[17]  Elliot W. Martin,et al.  Greenhouse Gas Emission Impacts of Carsharing in North America , 2011, IEEE Transactions on Intelligent Transportation Systems.

[18]  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.

[19]  Jianqiang Wang,et al.  Minimum Fuel Control Strategy in Automated Car-Following Scenarios , 2012, IEEE Transactions on Vehicular Technology.

[20]  Bo Cheng,et al.  Fuel-Optimal Cruising Strategy for Road Vehicles With Step-Gear Mechanical Transmission , 2015, IEEE Transactions on Intelligent Transportation Systems.

[21]  Huiping Li,et al.  Distributed receding horizon control of constrained nonlinear vehicle formations with guaranteed γ-gain stability , 2016, Autom..

[22]  Nick Stabile,et al.  The Aerodynamic Performance of Platoons: Final Report , 1995 .

[23]  Fei Luo,et al.  Cooperative Look-Ahead Control of Vehicle Platoon for Maximizing Fuel Efficiency Under System Constraints , 2018, IEEE Access.

[24]  Minggao Ouyang,et al.  Dieseline fueled flexible fuel compression ignition engine control based on in-cylinder pressure sensor , 2015 .

[25]  Francesco Borrelli,et al.  Control of Connected and Automated Vehicles: State of the Art and Future Challenges , 2018, Annu. Rev. Control..

[26]  William B. Dunbar,et al.  Distributed Receding Horizon Control of Vehicle Platoons: Stability and String Stability , 2012, IEEE Transactions on Automatic Control.

[27]  Nathan van de Wouw,et al.  Cooperative Adaptive Cruise Control: Network-Aware Analysis of String Stability , 2014, IEEE Transactions on Intelligent Transportation Systems.

[28]  Bo Cheng,et al.  Fuel-Saving Servo-Loop Control for an Adaptive Cruise Control System of Road Vehicles With Step-Gear Transmission , 2017, IEEE Transactions on Vehicular Technology.

[29]  Kaijiang Yu,et al.  Model Predictive Control for Hybrid Electric Vehicle Platooning Using Slope Information , 2016, IEEE Transactions on Intelligent Transportation Systems.

[30]  Junmin Wang,et al.  Integrated Power Management and Aftertreatment System Control for Hybrid Electric Vehicles With Road Grade Preview , 2017, IEEE Transactions on Vehicular Technology.

[31]  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.

[32]  Roger Westerholm,et al.  Emissions of particulate associated oxygenated and native polycyclic aromatic hydrocarbons from vehicles powered by ethanol/gasoline fuel blends , 2018 .

[33]  Yonggui Liu,et al.  Cooperative look-ahead control of vehicle platoon travelling on a road with varying slopes , 2019 .

[34]  Karl Henrik Johansson,et al.  Cyber-Physical Control of Road Freight Transport , 2016, Proc. IEEE.

[35]  S. Fabri,et al.  Particle Swarm Optimization for Nonlinear Model Predictive Control , 2011 .

[36]  Guoyuan Wu,et al.  Power-Based Optimal Longitudinal Control for a Connected Eco-Driving System , 2016, IEEE Transactions on Intelligent Transportation Systems.

[37]  J. Barkenbus Eco-driving: An overlooked climate change initiative , 2010 .

[38]  Ge Guo,et al.  Cooperative Spacing Control for Interconnected Vehicle Systems With Input Delays , 2017, IEEE Transactions on Vehicular Technology.

[39]  Narayan C. Kar,et al.  Rule-Based Control Strategy With Novel Parameters Optimization Using NSGA-II for Power-Split PHEV Operation Cost Minimization , 2014, IEEE Transactions on Vehicular Technology.

[40]  Bo Cheng,et al.  Fuel-Saving Cruising Strategies for Parallel HEVs , 2016, IEEE Transactions on Vehicular Technology.

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

[42]  Saad Mekhilef,et al.  A review on global fuel economy standards, labels and technologies in the transportation sector , 2011 .

[43]  Pierluigi Pisu,et al.  Fast Model Predictive Control-Based Fuel Efficient Control Strategy for a Group of Connected Vehicles in Urban Road Conditions , 2017, IEEE Transactions on Control Systems Technology.

[44]  Mingfa Yao,et al.  Effects of port injection of hydrous ethanol on combustion and emission characteristics in dual-fuel reactivity controlled compression ignition (RCCI) mode , 2018 .

[45]  Bugong Xu,et al.  Convergence Analysis of Cooperative Braking Control for Interconnected Vehicle Systems , 2017, IEEE Transactions on Intelligent Transportation Systems.

[46]  Peng Liu,et al.  Distributed Model Predictive Control for Cooperative and Flexible Vehicle Platooning , 2019, IEEE Transactions on Control Systems Technology.

[47]  George Kosmadakis,et al.  Methane/hydrogen fueling a spark-ignition engine for studying NO, CO and HC emissions with a research CFD code , 2016 .

[48]  Nasser L. Azad,et al.  A Distributed Reference Governor Approach to Ecological Cooperative Adaptive Cruise Control , 2018, IEEE Transactions on Intelligent Transportation Systems.

[49]  Leandro dos Santos Coelho,et al.  Comparison between two FPGA implementations of the Particle Swarm Optimization algorithm for high-performance embedded applications , 2010, 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA).

[50]  Datong Qin,et al.  Efficiency Study of a Dual-Motor Coupling EV Powertrain , 2015, IEEE Transactions on Vehicular Technology.