A Primitive Comparison for Traffic-Free Path Planning

Motion planning in on-road urban driving is usually stated as an optimization problem in a multi-dimensional space that presents a high complexity in obtaining a global optimal solution. In that sense, a great amount of different approaches to solve this problem coexist in the literature. However, to the best of our knowledge, there is no prior work studying how to choose the best strategy in this multi-dimensional space. This paper presents an in-depth analysis of interpolation curve planners based on continuous curvature Bézier compositions. To that end, a comparison framework to benchmark different path-planning primitives for on-road urban driving is proposed, and the evaluation of different primitive configurations and optimization techniques for path-planning is carried out. In addition, the results are openly published together with its consequent analysis, based on a set of key performance indicators related to the aforementioned main features.

[1]  Marco Pavone,et al.  Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions , 2013, ISRR.

[2]  Anthony J. Barbera,et al.  Trajectory Generation for an On-Road Autonomous Vehicle , 2006 .

[3]  Christos Dimitrakakis,et al.  Online statistical estimation for vehicle control , 2006 .

[4]  Vicente Milanés Montero,et al.  Smooth path and speed planning for an automated public transport vehicle , 2012, Robotics Auton. Syst..

[5]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[6]  John F. Canny,et al.  New lower bound techniques for robot motion planning problems , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[7]  Thierry Fraichard,et al.  Safe motion planning in dynamic environments , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Gabriel Hugh Elkaim,et al.  Manipulating B-Spline Based Paths for Obstacle Avoidance in Autonomous Ground Vehicles , 2007 .

[9]  Osamu Takahashi,et al.  Motion planning in a plane using generalized Voronoi diagrams , 1989, IEEE Trans. Robotics Autom..

[10]  S. LaValle Rapidly-exploring random trees : a new tool for path planning , 1998 .

[11]  Julius Ziegler,et al.  Making Bertha Drive—An Autonomous Journey on a Historic Route , 2014, IEEE Intelligent Transportation Systems Magazine.

[12]  Hongyan Wang,et al.  The complexity of the two dimensional curvature-constrained shortest-path problem , 1998 .

[13]  Wolfram Burgard,et al.  Kinodynamic motion planning for mobile robots using splines , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  John M. Dolan,et al.  Focused Trajectory Planning for autonomous on-road driving , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[15]  Anthony J. Barbera,et al.  Trajectory generation for an on-road autonomous vehicle , 2006, SPIE Defense + Commercial Sensing.

[16]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[17]  Jorge Nocedal,et al.  A trust region method based on interior point techniques for nonlinear programming , 2000, Math. Program..

[18]  B. Faverjon,et al.  Probabilistic Roadmaps for Path Planning in High-Dimensional Con(cid:12)guration Spaces , 1996 .

[19]  L. Shepp,et al.  OPTIMAL PATHS FOR A CAR THAT GOES BOTH FORWARDS AND BACKWARDS , 1990 .

[20]  Carlo H. Séquin,et al.  Interpolating Splines: Which is the fairest of them all? , 2009 .

[21]  Jean-Paul Laumond,et al.  Primitives for smoothing mobile robot trajectories , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[22]  Xiaohui Li,et al.  Real-Time Trajectory Planning for Autonomous Urban Driving: Framework, Algorithms, and Verifications , 2016, IEEE/ASME Transactions on Mechatronics.

[23]  Emilio Frazzoli,et al.  A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles , 2016, IEEE Transactions on Intelligent Vehicles.

[24]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[25]  Jacky Baltes,et al.  A benchmark suite for mobile robots , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[26]  Thomas K. Peucker,et al.  2. Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature , 2011 .

[27]  Jorge Godoy,et al.  Smooth path planning for urban autonomous driving using OpenStreetMaps , 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).

[28]  J. Betts Survey of Numerical Methods for Trajectory Optimization , 1998 .

[29]  Andreas Geiger,et al.  Vision meets robotics: The KITTI dataset , 2013, Int. J. Robotics Res..

[30]  Salah Sukkarieh,et al.  An Analytical Continuous-Curvature Path-Smoothing Algorithm , 2010, IEEE Transactions on Robotics.

[31]  J. Villagra,et al.  OBSTACLE-AVOIDING PATH PLANNING FOR HIGH VELOCITY WHEELED MOBILE ROBOTS , 2005 .

[32]  John M. Dolan,et al.  A behavioral planning framework for autonomous driving , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[33]  Matthias Althoff,et al.  CommonRoad: Composable benchmarks for motion planning on roads , 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).

[34]  Gerardo Beruvides,et al.  A Simple Multi-Objective Optimization Based on the Cross-Entropy Method , 2017, IEEE Access.

[35]  Aurelio Piazzi,et al.  ${ \mmb{\eta } }^{3}$-Splines for the Smooth Path Generation of Wheeled Mobile Robots , 2007, IEEE Transactions on Robotics.

[36]  Harald Opheim Smoothing a Digitized Curve by Data Reduction Methods , 1981, Eurographics.

[37]  J. J. Moré,et al.  Levenberg--Marquardt algorithm: implementation and theory , 1977 .

[38]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[39]  W. Hager,et al.  An hp‐adaptive pseudospectral method for solving optimal control problems , 2011 .

[40]  Christos Katrakazas,et al.  Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions , 2015 .

[41]  Dinh Quoc Tran,et al.  An application of sequential convex programming to time optimal trajectory planning for a car motion , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

[42]  Emilio Frazzoli,et al.  Optimal kinodynamic motion planning using incremental sampling-based methods , 2010, 49th IEEE Conference on Decision and Control (CDC).

[43]  Julius Ziegler,et al.  Trajectory planning for Bertha — A local, continuous method , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[44]  R. Curry,et al.  Path Planning Based on Bézier Curve for Autonomous Ground Vehicles , 2008, Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008.

[45]  Jin-Woo Lee,et al.  On-Road Trajectory Planning for General Autonomous Driving with Enhanced Tunability , 2014, IAS.

[46]  Jing-Sin Liu,et al.  Practical and flexible path planning for car-like mobile robot using maximal-curvature cubic spiral , 2005, Robotics Auton. Syst..