Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle

Mashadi, Behrooz; Majidi, Majid

doi:10.1590/s1679-78252014001400002

Cited by 24 publications

(8 citation statements)

References 19 publications

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“…Kang et al proposed a novel mixed motion planning and tracking control framework for AVs based on model predictive control (MPC), which was made up of an MPC-based longitudinal motion planning module, feedforward longitudinal motion tracking module, and MPCbased integrated lateral motion planning and tracking module [17]. Mashadia and Majidib proposed a global optimal path planning method for an AV overtaking a moving obstacle by performing a double lane-change maneuver after detecting the obstacle at a proper distance ahead [18]. Jie et al described motion and boundary constraints with a mathematical model proposed to solve the optimal control problem of path planning for unmanned ground systems, where the time-energy performance indicators were described by the Bolza cost function [19].…”

Section: Introductionmentioning

confidence: 99%

Optimum Path Tracking Control for the Inverse Problem of Vehicle Handling Dynamics Based on the hp-Adaptive Gaussian Pseudospectral Method

Liu

Sun

Cui

2021

Mathematical Problems in Engineering

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We propose a vehicle path-tracking method based on the hp-adaptive Gaussian pseudospectral method (GPM), which tackles the problem of the slow convergence speed of the optimal control of vehicle path tracking. First, we establish a kinematic vehicle model by considering the path constraints and boundary constraints during the process of tracking the described path of a vehicle. Subsequently, finding the minimum error of the lateral distance between the prescribed path and the expected trajectory is set as the performance objective function. Finally, the vehicle path tracking problem is transformed into an optimal control problem. The optimization algorithm is combined with the sequential quadratic programming algorithm to optimize problems related to the control and state variables and the boundary and path constraints. The simulated results show that the hp-adaptive GPM can improve the convergence rate of the optimal control problem for vehicle path tracking. The proposed hp-adaptive pseudospectral method has a higher solving efficiency compared with traditional approaches for the vehicle path-tracking problem. Concurrently, the verification results of a real vehicle test indicate the feasibility of the proposed algorithm for solving the vehicle path tracking problem. This research provides valuable insight into the design work of lane changes and is an important step towards the design of feedback control laws for path tracking.

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Section: Introductionmentioning

confidence: 99%

Optimum Path Tracking Control for the Inverse Problem of Vehicle Handling Dynamics Based on the hp-Adaptive Gaussian Pseudospectral Method

Liu

Sun

Cui

2021

Mathematical Problems in Engineering

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“…[1][2][3] Autonomous ground vehicles (AGVs) hold the capacity of geometrical understanding of the environment in order to navigate at a prescribed path without any driver intervention. 4 Safety and traffic flow are among the most notable expectations from AGVs besides the efficiency in parking spaces, energy security, driving comfort, and the reduced transportation costs. 5 For example, AGVs can substantially decrease the death occurred at crashes due to human driver errors considering that human driver error accounts for above 75% of death casualties at traffic accidents.…”

Section: Introductionmentioning

confidence: 99%

A novel adaptive control approach for path tracking control of autonomous vehicles subject to uncertain dynamics

Mohammadzadeh

Taghavifar

2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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Autonomous ground vehicles are constantly exposed to matched/mismatched uncertainties and disturbances and different operating conditions. Consequently, robustness to resist the undesirable effect of changes in the nominal parameters of the vehicle is a significant provision for satisfactory path-tracking control of these vehicles. The accomplishment of lateral path-tracking control is an essential task expectable from autonomous ground vehicles, particularly during critical maneuvers, abrupt cornering, and lane changes at high speeds. This paper presents a new control approach based on immersion and invariance control theorem. The asymptotic stability of the proposed method is ensured and the adaptation laws for the parameters are derived based on the I&I stability theorem. The effectiveness of the proposed control method is confirmed for autonomous ground vehicles systems while making a double-lane-change at various forward speeds. The robustness of the proposed control method is evaluated under parametric uncertainties related to the autonomous ground vehicle and different road conditions. The obtained results suggest that the proposed control method holds the capacity to be applied effectively to the path-tracking task of autonomous ground vehicles under a broad range of operating conditions, parametric uncertainness, and external disturbances.

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“…It provides a new idea for the development and application of vehicle handling dynamics. Mashadi and Majidi 13 used variational method and Pontryagin’s minimum principle to study the obstacle avoidance path planning problem, and CarSim software was used to track the planned path. The simulation results indicate that the path obtained by this method satisfies all vehicle dynamics constraints.…”

Section: Introductionmentioning

confidence: 99%

Study on the optimal lane changing steering input under different road adhesion coefficients

Zhang

Zhao

Zhang

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part I:

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To study the influence of road adhesion coefficient on lane changing steering input, vehicle handling inverse dynamics based on hp-adaptive Radau pseudospectral method is proposed in this article. First, a steering inverse dynamics model is established and then the inverse dynamics problem is converted into an optimal control problem. Second, by applying the hp-adaptive Radau pseudospectral method, the optimal control problem is converted into a nonlinear programming problem, which is then solved through sequential quadratic programming. Besides, two contrast verifications are carried out to validate the correctness and advantages of the proposed method. The simulation results show that the obtained control input satisfies the vehicle dynamic constraints. And comparing with Gauss Pseudospectral Method (GPM), hp-adaptive Radau pseudospectral method has higher computational accuracy and computational efficiency when solving non-smooth problem. The study of optimal steering input can provide guidance for driver’s lane changing behavior, so that the accident rate caused by human factors can be decreased. The proposed method can provide a reference value into the active safety of manned and unmanned vehicles.

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Global optimal path planning of an autonomous vehicle for overtaking a moving obstacle

Cited by 24 publications

References 19 publications

Optimum Path Tracking Control for the Inverse Problem of Vehicle Handling Dynamics Based on the hp-Adaptive Gaussian Pseudospectral Method

Optimum Path Tracking Control for the Inverse Problem of Vehicle Handling Dynamics Based on the hp-Adaptive Gaussian Pseudospectral Method

A novel adaptive control approach for path tracking control of autonomous vehicles subject to uncertain dynamics

Study on the optimal lane changing steering input under different road adhesion coefficients

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