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Dynamic Trajectory Planning for Automated Lane Changing Using the Quintic Polynomial Curve
- Source :
- Journal of Advanced Transportation. September 15, 2023, Vol. 2023
- Publication Year :
- 2023
-
Abstract
- As one of the key algorithms in supporting AV (autonomous vehicle) to complete the LC (lane changing) maneuver, the LTP (LC trajectory planning) algorithm generates safe and efficient LC trajectory for the AV. This paper proposes a novel dynamic LTP algorithm based on the quintic polynomial curve. This algorithm is capable of adjusting LC trajectory according to the state changes of the surrounding driving environment. The formulation of our proposed algorithm mainly consists the underlying form of trajectory equation, the optimization objective function, the corresponding constrains, and the SQP (sequential quadratic programming) algorithm. For each planning step, the time-based quintic polynomial function is introduced to model the trajectory equation. The problem of solving the parameters of the corresponding equation is then transformed into an optimization problem, which takes driver's safety, comfort, and efficiency into account. After that, the SQP algorithm is employed to solve this optimization problem. Finally, both numerical simulation and field-data validation are used to verify the effectiveness of our proposed algorithm. We anticipate that the research could provide certain valuable insights for developing more reliable LC algorithms for AVs.<br />Author(s): Yang Li [1]; Linbo Li (corresponding author) [1]; Daiheng Ni [2] 1. Introduction Numerous research studies indicate that the advent of AVs (autonomous vehicles) could significantly enhance traffic safety, [...]
- Subjects :
- Algorithm
Numerical analysis
Driverless cars
Algorithms
Simulation methods
Subjects
Details
- Language :
- English
- ISSN :
- 01976729
- Volume :
- 2023
- Database :
- Gale General OneFile
- Journal :
- Journal of Advanced Transportation
- Publication Type :
- Academic Journal
- Accession number :
- edsgcl.766447128
- Full Text :
- https://doi.org/10.1155/2023/6926304