Abstract
Tractor-trailer vehicles, which are composed of a car-like tractor towing a passive trailer, have been widely deployed in the transportation industry, and trajectory planning is a critical step in enabling such a system to drive autonomously. Owing to the properties of being highly nonlinear and nonholonomic with complex dynamics, the tractor-trailer system poses great challenges to the development of motion-planning algorithms. In this study, an indirect trajectory planning framework for a tractor-trailer vehicle under on-road driving is presented to deal with the problem that the traditional planning framework cannot consider the feasibility and quality simultaneously in real-time trajectory generation of the tractor-trailer vehicle. The indirect planning framework can easily handle complicated tractor-trailer dynamics and generate high-quality, obstacle-free trajectory using quintic polynomial spline, speed profile optimization, forward simulation, and properly designed cost functions. Simulations under different driving scenarios and trajectories with different driving requirements are conducted to validate the performance of the proposed framework.
Similar content being viewed by others
References
GONZÁLEZ-CANTOS A, OLLERO A. Backing-up maneuvers of autonomous tractor-trailer vehicles using the qualitative theory of nonlinear dynamical systems [J]. The International Journal of Robotics Research, 2009, 28(1): 49–65.
WANG Y J, CARTMELL M P. Trajectory generation for a four wheel steering tractor-trailer system: A two-step method [J]. Robotica, 1998, 16(4): 381–386.
SHAREEF Z, TRÄCHTLER A. Simultaneous path planning and trajectory optimization for robotic manipulators using discrete mechanics and optimal control [J]. Robotica, 2016, 34(6): 1322–1334.
ZHAO H C, CHEN W, ZHOU S B, et al. Online trajectory planning for an industrial tractor towing multiple full trailers [C]//2020 IEEE International Conference on Robotics and Automation (ICRA). Paris: IEEE, 2020: 6089–6095.
LI B, ACARMAN T, ZHANG Y M, et al. Tractor-trailer vehicle trajectory planning in narrow environments with a progressively constrained optimal control approach [J]. IEEE Transactions on Intelligent Vehicles, 2020, 5(3): 414–425.
OLIVEIRA R, LJUNGQVIST O, LIMA P F, et al. A geometric approach to on-road motion planning for long and multi-body heavy-duty vehicles [C]//2020 IEEE Intelligent Vehicles Symposium (IV). [s.l.]: IEEE, 2020: 999–1006.
BOLZERN P, DESANTIS R M, LOCATELLI A, et al. Path-tracking for articulated vehicles with off-axle hitching [J]. IEEE Transactions on Control Systems Technology, 1998, 6(4): 515–523.
BUSHNELL L, MIRTICH B, SAHAI A, et al. Off-tracking bounds for a car pulling trailers with kingpin hitching [C]//Proceedings of 1994 33rd IEEE Conference on Decision and Control. Lake Buena Vista, FL: IEEE, 1994: 2944–2949.
LAMIRAUX F, BONNAFOUS D, VAN GEEM C. Path optimization for nonholonomic systems: Application to reactive obstacle avoidance and path planning [M]//Control problems in robotics. Heidelberg: Springer, 2003: 1–18.
EVESTEDT N, LJUNGQVIST O, AXEHILL D. Motion planning for a reversing general 2-trailer configuration using Closed-Loop RRT [C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Daejeon: IEEE, 2016: 3690–3697.
LIMA P F. Optimization-based motion planning and model predictive control for autonomous driving: With experimental evaluation on a heavy-duty construction truck [D]. Stockholm: KTH Royal Institute of Technology, 2018.
ALTAFINI C. Some properties of the general n-trailer [J]. International Journal of Control, 2001, 74(4): 409–424.
ALTAFINI C. Following a path of varying curvature as an output regulation problem [J]. IEEE Transactions on Automatic Control, 2002, 47(9): 1551–1556.
FAN H Y, ZHU F, LIU C C, et al. Baidu Apollo EM motion planner [EB/OL]. [2020-12-20]. https://arxiv.org/pdf/1807.08048.pdf.
TAKAHASHI A, HONGO T, NINOMIYA Y, et al. Local path planning and motion control for AGV in positioning [C]//IEEE/RSJ International Workshop on Intelligent Robots and Systems. Tsukuba: IEEE, 1989: 392–397.
WERLING M, ZIEGLER J, KAMMEL S, et al. Optimal trajectory generation for dynamic street scenarios in a Frenét Frame [C]//2010 IEEE International Conference on Robotics and Automation. Anchorage, AK: IEEE, 2010: 987–993.
STELLATO B, BANJAC G, GOULART P, et al. OSQP: An operator splitting solver for quadratic programs [C]//2018 UKACC 12th International Conference on Control (CONTROL). Sheffield: IEEE, 2018: 339.
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation item
the National Natural Science Foundation of China (No. 61873165/U1764264), and the Shanghai Automotive Industry Science and Technology Development Foundation (No. 1807)
Rights and permissions
About this article
Cite this article
Shen, Q., Wang, B. & Wang, C. Real-Time Trajectory Planning for On-road Autonomous Tractor-Trailer Vehicles. J. Shanghai Jiaotong Univ. (Sci.) 26, 722–730 (2021). https://doi.org/10.1007/s12204-021-2362-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12204-021-2362-9