Optimization-based Path Planning for an Autonomous Vehicle in a Racing Track

被引：0
作者：
Bonab, Saeed Amirfarhangi [1 ]
Emadi, Ali [2 ]
机构：
[1] McMaster Univ, Dept Mech Engn, Hamilton, ON, Canada
[2] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON, Canada
来源：
45TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2019) | 2019年
关键词：
Autonomous driving; motion planning; optimal control; optimization; path planning; receding horizon;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Path planning is discussed in this article for an autonomous vehicle given a route to follow. Route data is considered to be available for a distance ahead of the vehicle in a receding horizon manner. Linear approximation of the nonlinear equations for a vehicle following a path is obtained. Based on these equations, the optimization problem is formed in a convex optimization format and solved to find the optimal path. Optimality is a trade-off between comfort and travel time. Results are provided for some cases considering that the vehicle is traveling in the Suzuka circuit and the observable horizon ahead of the vehicle is a part of this track. Results are discussed for a few trade-off values and analyzed from the practical point of view, which shows that the method is capable of producing an optimal path to follow in an insignificant amount of time. Finally, an alternative approach for improving model accuracy is proposed and discussed. Finally, it has been concluded that the proposed method has a significant potential for motion planning/controlling applications for an autonomous vehicle using model predictive control.
引用
收藏
页码：3823 / 3828
页数：6
相关论文
共 27 条
[1]  
Bast H, 2016, LECT NOTES COMPUT SC, V9220, P19, DOI 10.1007/978-3-319-49487-6_2
[2]   Real-time Approximation of Clothoids With Bounded Error for Path Planning Applications [J].
Brezak, Misel ;
Petrovic, Ivan .
IEEE TRANSACTIONS ON ROBOTICS, 2014, 30 (02) :507-515
[3]   Autonomous driving in urban environments: approaches, lessons and challenges [J].
Campbell, Mark ;
Egerstedt, Magnus ;
How, Jonathan P. ;
Murray, Richard M. .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2010, 368 (1928) :4649-4672
[4]   Sampling-Based Robot Motion Planning: A Review [J].
Elbanhawi, Mohamed ;
Simic, Milan .
IEEE ACCESS, 2014, 2 :56-77
[5]   Maneuver-Based Trajectory Planning for Highly Autonomous Vehicles on Real Road With Traffic and Driver Interaction [J].
Glaser, Sebastien ;
Vanholme, Benoit ;
Mammar, Said ;
Gruyer, Dominique ;
Nouveliere, Lydie .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2010, 11 (03) :589-606
[6]   A Review of Motion Planning Techniques for Automated Vehicles [J].
Gonzalez, David ;
Perez, Joshue ;
Milanes, Vicente ;
Nashashibi, Fawzi .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 17 (04) :1135-1145
[7]  
Grant M., 2014, Cvx: Matlab software for disciplined convex programming
[8]   Graph implementations for nonsmooth convex programs [J].
Grant, Michael C. ;
Boyd, Stephen P. .
Lecture Notes in Control and Information Sciences, 2008, 371 :95-110
[9]  
Gurobi Optimization LLC., 2021, Gurobi Optimizer Reference Manual
[10]   Bezier curve based path planning for autonomous vehicle in urban environment [J].
Han, Long ;
Yashiro, Hironari ;
Nejad, Hossein Tehrani Nik ;
Quoc Huy Do ;
Mita, Seiichi .
2010 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2010, :1036-1042
123