| MODEL PREDICTIVE TRAJECTORY OPTIMIZATION AND TRACKING IN HIGHLY CONSTRAINED ENVIRONMENTS
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| Zhiqiang Fu 1,2, Lu Xiong 1,2, Zixuan Qian 1,2, Bo Leng 1,2, Dequan Zeng 1,2, Yanjun Huang 1,2 |
1School of Automotive Studies, Vehicle Engineering, Tongji University
2Clean Energy Automotive Engineering Center, Tongji University |
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| ABSTRACT |
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This paper presents a model predictive trajectory optimization and tracking framework to avoid collisions for
autonomous vehicles in highly constrained environments. Firstly, a vehicle model is established in road coordinate system to
describe the relationship between the vehicle and the reference road. Secondly, a numerical optimization method is applied to
smoothen the reference path generated by waypoints. Then, a multilayer searched method is used to establish a safe driving
corridor in highly constrained environments. In addition, an optimal path optimization and tracking framework based on
model predictive control is formulated to improve the driving safety and comfort. The proposed framework considers the
constraints of path boundaries and vehicle dynamics to provide the optimal control command. Furthermore, the speed profile
is optimized based on the longitudinal motion model in space domain to ensure the constraints of speed limits and vehicle
acceleration. Finally, the proposed algorithms are evaluated through experiments in various scenarios to demonstrate the
effectiveness. |
| Key Words:
Trajectory optimization, Path tracking, Model predictive control, Obstacle avoidance
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Corresponding Author.
Lu Xiong , Email. 
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