Tracking and Safety Control for Car-Trailer System with Optimization
- 10.2991/assehr.k.220504.041How to use a DOI?
- Dynamic function; Energy function; Optimization; Genetic algorithm; Sequential quadratic programming method
This Study aims to develop an automatic car-trailer system tracking and safety control model and optimize every parameter related to improve traffic safety. The authors proposed a car-trailer system tracking and safe control model. Kinetics, dynamics, and simulation code are established for both tractor and trailer. Moreover, a safety control is introduced to avoid any obstacle in the path. Furthermore, by using ISIGHT, algorithms (Genetic Algorithms and Successive quadratic programming (SQP)) are used to optimize parameters used in the car-trailer system. Thus, shortest traveling time and smallest risk of rolling-over for trailer are ensured. The numerical deduction for kinetic, dynamics, safety control are successfully established. MATLAB simulations are programmed correctly to imitate the moving path of both tractor and trailer. Optimization are finished smoothly with clear result. Originality/value: this is a simulation of tractor-trailer model and accomplishment of its safe-driving and path-optimizing features. there are two main contributions: the first is the simulation of tractor-trailer model and the accomplishment of its tracking and collision avoidance functions; the second is investigating trajectory with the shortest time traveled through optimization. this paper provides a reference to develop self-driving car-trailer with optimized attributes and path choosing.
- © 2022 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license.
Cite this article
TY - CONF AU - Boshen Yang AU - Tianyi Zhang PY - 2022 DA - 2022/06/01 TI - Tracking and Safety Control for Car-Trailer System with Optimization BT - Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022) PB - Atlantis Press SP - 223 EP - 228 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.220504.041 DO - 10.2991/assehr.k.220504.041 ID - Yang2022 ER -