scholarly journals Vehicle trajectory optimization based on limiting average algorithm

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Xingdong Wang ◽  
Shuo Liu
Keyword(s):  
Trajectory Optimization ◽  
Vehicle Trajectory

High-Speed Reentry Vehicle Trajectory Optimization and Guidance with Lateral Maneuver

2021 ◽  
pp. 4151-4166
Author(s):  
Xiangyang Hui ◽  
Fenghua Chi ◽  
Zheng Qi ◽  
Meng Wu ◽  
Fei Li
Keyword(s):  
Trajectory Optimization ◽  
High Speed ◽  
Reentry Vehicle ◽  
Vehicle Trajectory

The Applications of Improved Genetic Algorithm on Hypersonic Vehicle Trajectory Optimization

2012 ◽  
Vol 466-467 ◽  
pp. 1095-1099
Author(s):  
Liu Xu ◽  
Wei Min Li ◽  
Lin Zhang ◽  
An Tang Zhang
Keyword(s):  
Genetic Algorithm ◽  
Trajectory Optimization ◽  
Optimal Trajectory ◽  
Optimal Solution ◽  
High Sensitivity ◽  
Initial Guess ◽  
Cruise Missile ◽  
Trajectory Design ◽  
Improved Genetic Algorithm ◽  
Vehicle Trajectory

The Optimal trajectory design for hypersonic cruise missile is an optimal control problem with strict terminal constraints and variable final time. The classical algorithms always encounter the problems of high sensitivity to initial guess and local convergence in solving this problem. Aiming at these problems, genetic algorithm (GA) which is of good global convergence is applied to designing the optimal trajectory for hypersonic cruise missile. In order to improve the convergence rate of GA and overcome its premature problems, this text introduces a predatory search (PS) strategy to speed the convergence of genetic algorithms, robust and closer to the optimal solution. This text compares the original genetic algorithm (GA) and improved genetic algorithm by the emulate experiments, and the results show that the PSGA is a more effective method to design the Optimal trajectory for hypersonic cruise missile than the original genetic algorithm.

scholarly journals UB-LSTM: A Trajectory Prediction Method Combined with Vehicle Behavior Recognition

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Haipeng Xiao ◽  
Chaoqun Wang ◽  
Zhixiong Li ◽  
Rendong Wang ◽  
Cao Bo ◽  
...  
Keyword(s):  
Prediction Model ◽  
Trajectory Optimization ◽  
Dynamic Environment ◽  
Prediction Method ◽  
Trajectory Prediction ◽  
Behavior Recognition ◽  
Recognition Model ◽  
Bidirectional Lstm ◽  
Vehicle Trajectory ◽  
Actual Trajectory

In order to make an accurate prediction of vehicle trajectory in a dynamic environment, a Unidirectional and Bidirectional LSTM (UB-LSTM) vehicle trajectory prediction model combined with behavior recognition is proposed, and then an acceleration trajectory optimization algorithm is proposed. Firstly, the interactive information with the surrounding vehicles is obtained by calculation, then the vehicle behavior recognition model is established by using LSTM, and the vehicle information is input into the behavior recognition model to identify vehicle behavior. Then, the trajectory prediction model is established based on Unidirectional and Bidirectional LSTM, and the identified vehicle behavior and the input information of the behavior recognition model are input into the trajectory prediction model to predict the horizontal and vertical speed and coordinates of the vehicle in the next 3 seconds. Experiments are carried out with NGSIM data sets, and the experimental results show that the mean square error (MSE) between the predicted trajectory and the actual trajectory obtained by this method is 0.124, which is 97.2% lower than that of the method that does not consider vehicle behavior and directly predicts the trajectory. The test loss is 0.000497, which is 95.68% lower than that without considering vehicle behavior. The predicted trajectory is obviously optimized, closer to the actual trajectory, and the performance is more stable.

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