This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Hierarchical Framework for Adaptive Cruise Control with Model Predictive Control Method
Technical Paper
2017-01-1963
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
Adaptive cruise control (ACC), as one of the advanced driver assistance systems (ADAS), has become increasingly popular in improving both driving safety and comfort. Since the objectives of ACC can be multi-dimensional, and often conflict with each other, it is a challenging task in its control design. The research presented in this paper takes ACC control design as a constrained optimization problem with multiple objectives. A hierarchical framework for ACC control is introduced, aimed to achieve optimal performance on driving safety and comfort, speed and/or distance tracking, and fuel economy whenever possible. Under the hierarchical framework, the operational mode is determined in the upper layer, in which a model predictive control (MPC) based spacing controller is employed to deal with the multiple control objectives. On the other hand, the lower layer is for actuator control, such as braking and driving control for vehicle longitudinal dynamics. Actuator delay, combined with vehicle longitudinal dynamics, is converted into a delay-free system by augmenting the system dimension. Then a quadratic cost function is developed to obtain an ideal control output by solving an optimal control problem. Driving safety is guaranteed by constraining the inter-vehicle distance within a safe range. Other objectives are considered by their corresponding performance indexes. The low-level controller serves as the actuator control unit, which controls the powertrain and braking systems to ensure desired acceleration be tracked based on the inverse longitudinal dynamics model. Finally, the proposed ACC is simulated and evaluated under PanoSim®, a virtual experimental environment for development, testing and verification of ADAS and intelligent driving in general. Simulation results have demonstrated satisfactory performance with the proposed ACC system.
Authors
Topic
Citation
Jiang, Y., Deng, W., He, R., Yang, S. et al., "Hierarchical Framework for Adaptive Cruise Control with Model Predictive Control Method," SAE Technical Paper 2017-01-1963, 2017, https://doi.org/10.4271/2017-01-1963.Also In
References
- Fancher P , Bareket Z Evaluating headway control using range versus range-rate relationships[J] Vehicle System Dynamics 1994 23 1 575 596
- Ioannou P , Xu Z THROTTLE AND BRAKE CONTROL SYSTEMS FOR AUTOMATIC VEHICLE FOLLOWING∗ [J] Journal of Intelligent Transportation Systems 1994 1 4 345 377
- Yi K , Hong J , Kwon Y D A vehicle control algorithm for stop-and-go cruise control[J] Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 2001 215 10 1099 1115
- Shakouri P , Ordys A , Askari M R Adaptive cruise control with stop&go function using the state-dependent nonlinear model predictive control approach[J] ISA transactions 2012 51 5 622 631
- Marzbanrad J , Tahbaz-zadeh Moghaddam I Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade[J] Vehicle System Dynamics 2016 54 9 1291 1316
- Kim , H. , and Yi , K. Design of a Model Reference Cruise Control Algorithm SAE Int. J. Passeng. Cars - Electron. Electr. Syst. 5 2 440 449 2012 10.4271/2012-01-0492
- Lattemann , F. , Neiss , K. , Terwen , S. , and Connolly , T. The Predictive Cruise Control - A System to Reduce Fuel Consumption of Heavy Duty Trucks SAE Technical Paper 2004-01-2616 2004 10.4271/2004-01-2616
- Luo L , Liu H , Li P et al. Model predictive control for adaptive cruise control with multi-objectives: comfort, fuel-economy, safety and car-following[J] Journal of Zhejiang University-Science A 2010 11 3 191 201
- Li S , Li K , Rajamani R et al. Model predictive multi-objective vehicular adaptive cruise control[J] IEEE Transactions on Control Systems Technology 2011 19 3 556 566
- Luo Y , Chen T , Zhang S et al. Intelligent hybrid electric vehicle ACC with coordinated control of tracking ability, fuel economy, and ride comfort[J] IEEE Transactions on Intelligent Transportation Systems 2015 16 4 2303 2308
- Li L , Wang X , Song J Fuel consumption optimization for smart hybrid electric vehicle during a car-following process[J] Mechanical Systems and Signal Processing 2017 87 17 29