Autonomous Wary Collision Avoidance

被引:10
作者
Fors, Victor [1 ]
Olofsson, Bjorn [1 ,2 ]
Nielsen, Lars [1 ]
机构
[1] Linkoping Univ, Dept Elect Engn, Div Vehicular Syst, SE-58183 Linkoping, Sweden
[2] Lund Univ, Dept Automat Control, SE-22100 Lund, Sweden
来源
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES | 2021年 / 6卷 / 02期
关键词
Friction; Acceleration; Collision avoidance; Numerical models; Computational modeling; Tires; Intelligent vehicles; Autonomous vehicles; control design; obstacle avoidance; optimal control; vehicle dynamics; vehicle safety;
D O I
10.1109/TIV.2020.3029853
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Handling of critical situations is an important part in the architecture of an autonomous vehicle. A controller for autonomous collision avoidance is developed based on a wary strategy that assumes the least tire-road friction for which the maneuver is still feasible. Should the friction be greater, the controller makes use of this, and performs better. The controller uses an acceleration-vector reference obtained from optimal control of a friction-limited particle, whose applicability is verified by using numerical optimization on a full vehicle model. By employing an analytical tire model of the tire-road friction limit, to determine slip references for steering, and body-slip control, the result is a controller where the computation of its output is explicit, and independent of the actual tire-road friction. When evaluated in real-time on a high-fidelity simulation model, the developed controller performs close to that achieved by offline numerical optimization.
引用
收藏
页码:353 / 365
页数:13
相关论文
共 37 条
[1]   Modeling and optimization with Optimica and JModelica.org-Languages and tools for solving large-scale dynamic optimization problems [J].
Akesson, J. ;
Arzen, K-E. ;
Gafvert, M. ;
Bergdahl, T. ;
Tummescheit, H. .
COMPUTERS & CHEMICAL ENGINEERING, 2010, 34 (11) :1737-1749
[2]   CasADi: a software framework for nonlinear optimization and optimal control [J].
Andersson, Joel A. E. ;
Gillis, Joris ;
Horn, Greg ;
Rawlings, James B. ;
Diehl, Moritz .
MATHEMATICAL PROGRAMMING COMPUTATION, 2019, 11 (01) :1-36
[3]   Optimal motion control for collision avoidance at Left Turn Across Path/Opposite Direction intersection scenarios using electric propulsion [J].
Arikere, Adithya ;
Yang, Derong ;
Klomp, Matthijs .
VEHICLE SYSTEM DYNAMICS, 2019, 57 (05) :637-664
[4]  
Bakker E, 1987, 870421 SAE
[5]   Trajectory tracking for autonomous vehicles on varying road surfaces by friction-adaptive nonlinear model predictive control [J].
Berntorp, K. ;
Quirynen, R. ;
Uno, T. ;
Di Cairano, S. .
VEHICLE SYSTEM DYNAMICS, 2020, 58 (05) :705-725
[6]   Models and methodology for optimal trajectory generation in safety-critical road-vehicle manoeuvres [J].
Berntorp, Karl ;
Olofsson, Bjorn ;
Lundahl, Kristoffer ;
Nielsen, Lars .
VEHICLE SYSTEM DYNAMICS, 2014, 52 (10) :1304-1332
[7]   Advances in simultaneous strategies for dynamic process optimization [J].
Biegler, LT ;
Cervantes, AM ;
Wächter, A .
CHEMICAL ENGINEERING SCIENCE, 2002, 57 (04) :575-593
[8]   Coordinating Tire Forces to Avoid Obstacles Using Nonlinear Model Predictive Control [J].
Brown, Matthew ;
Gerdes, J. Christian .
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2020, 5 (01) :21-31
[9]   Closed-loop controller for post-impact vehicle dynamics using individual wheel braking and front axle steering [J].
Yang, Derong ;
Jacobson, Bengt ;
Jonasson, Mats ;
Gordon, Tim J. .
International Journal of Vehicle Autonomous Systems, 2014, 12 (02) :158-179
[10]   Optimal lane change motion of intelligent vehicles based on extended adaptive pseudo-spectral method under uncertain vehicle mass [J].
Fang Zeping ;
Duan Jianmin .
ADVANCES IN MECHANICAL ENGINEERING, 2017, 9 (07)