Research on Trajectory Planning and Tracking Strategy of Lane-changing and Overtaking based on PI-MPC Dual Controllers

Abstract Automatic lane change is a necessary part for autonomous driving. This paper proposes an integrated strategy for automatic lane-changing decision and trajectory planning in dynamic scenario. The Back Propagation Neural Network (BPNN) is used in decision-making layer, whose prediction accuracy of the discretionary lane-changing is 94.22%. The planning layer determines the adjustable range of the average vehicle speed based on the size of the “lane-changing demand”, which is obtained based on the data of hidden layer in neural network, and then dynamically optimizes the lane-changing curve according to the vehicle speed and the current scenario. In order to verify the rationality of the proposed lane-changing architecture, simulation experiments based on a driving simulator is performed. The experiments show that the vehicle’s maximum lateral acceleration under the proposed lane-changing trajectory at a speed of 70km/h is about 0.1g, which means the vehicle has better comfort during lane-changing. At the same time, the proposed lane-changing trajectory is more in line with the human driver’s lane-changing trajectory compared with that of other planning strategy. Meanwhile, the planning strategy can also support the lane-changing trajectory planning on a curved road.

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Trajectory planning and optimisation method for intelligent vehicle lane changing emergently

IET Intelligent Transport Systems ◽

10.1049/iet-its.2018.5224 ◽

2018 ◽

Vol 12 (10) ◽

pp. 1336-1344 ◽

Cited By ~ 5

Author(s):

Haobin Jiang ◽

Kaijin Shi ◽

Junyu Cai ◽

Long Chen

Keyword(s):

Trajectory Planning ◽

Intelligent Vehicle ◽

Lane Changing

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A Lane-Changing Trajectory Planning and Assistant Decision-Making Method for Autonomous Vehicle

CICTP 2018 ◽

10.1061/9780784481523.009 ◽

2018 ◽

Author(s):

Zheyu Cui ◽

Jianming Hu ◽

Hongfei Guan

Keyword(s):

Decision Making ◽

Trajectory Planning ◽

Autonomous Vehicle ◽

Lane Changing

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A Universal Trajectory Planning Method for Automated Lane-Changing and Overtaking Maneuvers

Mathematical Problems in Engineering ◽

10.1155/2020/1023975 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13 ◽

Cited By ~ 1

Author(s):

Ying Wang ◽

Chong Wei

Keyword(s):

Trajectory Planning ◽

Mathematical Optimization ◽

Initial Position ◽

Planning Method ◽

Reference Trajectory ◽

Time Intervals ◽

Simulation Experiments ◽

Lane Changing ◽

Traffic State ◽

Mathematical Optimization Model

Lane-changing and overtaking are conventional maneuvers on roads, and the reference trajectory is one of the prerequisites to execute these maneuvers. This study proposes a universal trajectory planning method for automated lane-changing and overtaking maneuvers, in which the trajectory is regarded as the combination of a path and its traffic state profiles. The two-dimensional path is represented by a suitable curve to connect the initial position with final position of the ego vehicle. Based on the planned path, its traffic state profiles are generated by solving a nonlinear mathematical optimization model. Moreover, the study discretizes the time horizon into several time intervals and determines the parameters to obtain the continuous and smooth profiles, which guarantees the safety and comfort of the ego vehicle. Finally, a series of simulation experiments are performed in the MATLAB platform and the results show the feasibility and effectiveness of the proposed universal trajectory planning method.

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Accelerated Lane-Changing Trajectory Planning of Automated Vehicles with Vehicle-to-Vehicle Collaboration

Journal of Advanced Transportation ◽

10.1155/2017/8132769 ◽

2017 ◽

Vol 2017 ◽

pp. 1-11 ◽

Cited By ~ 13

Author(s):

Haijian Bai ◽

Jianfeng Shen ◽

Liyang Wei ◽

Zhongxiang Feng

Keyword(s):

Boundary Conditions ◽

Simulation Model ◽

Trajectory Planning ◽

Polynomial Method ◽

Vehicle Model ◽

Automated Vehicles ◽

Lane Changing ◽

Cooperative Strategies ◽

Vehicle To Vehicle ◽

Changing Process

Considering the complexity of lane changing using automated vehicles and the frequency of turning lanes in city settings, this paper aims to generate an accelerated lane-changing trajectory using vehicle-to-vehicle collaboration (V2VC). Based on the characteristics of accelerated lane changing, we used a polynomial method and cooperative strategies for trajectory planning to establish a lane-changing model under different degrees of collaboration with the following vehicle in the target lane by considering vehicle kinematics and comfort requirements. Furthermore, considering the shortcomings of the traditional elliptical vehicle and round vehicle models, we established a rectangular vehicle model with collision boundary conditions by analysing the relationships between the possible collision points and the outline of the vehicle. Then, we established a simulation model for the accelerated lane-changing process in different environments under different degrees of collaboration. The results show that, by using V2VC, we can achieve safe accelerated lane-changing trajectories and simultaneously satisfy the requirements of vehicle kinematics and comfort control.

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