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Journal ArticleDOI

Path tracking control for inverse problem of vehicle handling dynamics

30 Sep 2017-Journal of Vibroengineering (JVE International Ltd.)-Vol. 19, Iss: 6, pp 4591-4608
TL;DR: In this paper, a path tracking controller based on active disturbance rejection control (ADRC) theory is presented to solve path tracking problem in inverse vehicle handling dynamics, which can help drivers easily identify safe lane-keeping trajectories and area.
Abstract: A path tracking controller based on active disturbance rejection control(ADRC) theory is presented in this paper to solve path tracking problem in inverse vehicle handling dynamics. The basic idea behind the work is to design an active disturbance rejection controller according to yaw rate and lateral displacement during a vehicle travels along a prescribed path to generate an expected trajectory which guarantees minimum clearance to the prescribed path. Aiming at this purpose, using preview follower theory, a linear extended state observer based on lateral displacement is designed. Considering yaw angle of vehicle, a non-linear combination function combined error of lateral displacement as well as error of yaw angle is designed according to monotone bounded hyperbolic of tangent function. Finally, a real vehicle test is executed to verify the rationality of the path tracking controller. At the same time, according to characteristics of pavement file in Carsim, a 3-D virtual pavement model is established and ride comfort simulation of random pavement is carried out in the software model. The results show that the minimum lateral position error of the generated path tracking trajectory can be good indicators of successful solving of the path tracking problem in inverse vehicle handling dynamics for ADRC. More precisely, there is higher calculation accuracy for the algorithm of the ADRC to solve the path tracking problem. The study can help drivers easily identify safe lane-keeping trajectories and area.

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Citations
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Journal ArticleDOI
Shuo Zhang1, Xuan Zhao1, Guohua Zhu1, Peilong Shi1, Hao Yue1, Kong Lingchen1 
TL;DR: Simulation results verify the adaptability, robustness, accuracy of the control strategy under which the intelligent vehicle has good handling stability.
Abstract: The trajectory tracking control strategy for intelligent vehicle is proposed in this article. Considering the parameters perturbations and external disturbances of the vehicle system, based on the ...

10 citations


Cites methods from "Path tracking control for inverse p..."

  • ...According to the reachable condition of the sliding mode surface, the Lyapunov function is constructed as shown as formula (13)...

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08 Dec 2016
TL;DR: In this paper, a new technique for vehicle handling inverse dynamics which can evaluate the emergency collision avoidance performance is proposed, and the results show that vehicle can well track the expected path in high speed.
Abstract: Vehicle driving safety is the urgent key problem to be solved of vehicle independent development while encountering emergency collision avoidance with high speed. And it is also the premise and one of the necessary conditions of vehicle active safety. A new technique for vehicle handling inverse dynamics which can evaluate the emergency collision avoidance performance is proposed. Firstly, the steering angle input of 3-DOF vehicle mode is established. The steering angle input imposed by driver is the control variable, and accurately tracking the expected path was the control object. The optimal control problem can be converted into a nonlinear programming problem while using the state variables conversion, which was solved by the sequential quadratic programming (SQP) algorithm. The results show that vehicle can well track the expected path in high speed.

2 citations

Journal ArticleDOI
01 Jul 2020
TL;DR: In this paper, a path tracking controller is designed to calculate the lateral deviation between the expected path and the actual path, and outputs the front wheel rotation angle through the controller, so that the autonomous vehicle can travel well according to the expected trajectory.
Abstract: In order to realize the path tracking of autonomous vehicles, this paper first simplifies the complex structure of the vehicle into a two-degree-of-freedom kinematic and dynamic vehicle model. based on PID control, the vehicle path tracking controller is designed to calculate the lateral deviation between the expected path and the actual path, and outputs the front wheel rotation angle through the controller, so that the autonomous vehicle can travel well according to the expected path. The control system model is built in the MATLAB/Simulink, and the vehicle path tracking control system is simulated and verified jointly with the CarSim software platform. Simulation results show that the designed control strategy can ensure the path tracking performance of intelligent vehicles at different speeds, and has good tracking accuracy, real-time performance and vehicle driving stability.

2 citations

References
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Journal ArticleDOI
TL;DR: In this paper, the authors proposed a dynamic automated lane change maneuver based on vehicle-to-vehicle communication to eliminate potential collisions during the lane change process and demonstrate that the maneuver can avoid potential collisions in a driving simulator.
Abstract: Automated driving is gaining increasing amounts of attention from both industry and academic communities because it is regarded as the most promising technology for improving road safety in the future. The ability to make an automated lane change is one of the most important parts of automated driving. However, there has been little research into automated lane change maneuvers, and current research has not identified a way to avoid potential collisions during lane changes, which result from the state variations of the other vehicles. One important reason is that the lane change vehicle cannot acquire accurate information regarding the other vehicles, especially the vehicles in the adjacent lane. However, vehicle-to-vehicle communication has the advantage of providing more information, and this information is more accurate than that obtained from other sensors, such as radars and lasers. Therefore, we propose a dynamic automated lane change maneuver based on vehicle-to-vehicle communication to accomplish an automated lane change and eliminate potential collisions during the lane change process. The key technologies for this maneuver are trajectory planning and trajectory tracking. Trajectory planning calculates a reference trajectory satisfying the demands of safety, comfort and traffic efficiency and updates it to avoid potential collisions until the lane change is complete. The trajectory planning method converts the planning problem into a constrained optimization problem using the lane change time and distance. This method is capable of planning a reference trajectory for a normal lane change, an emergency lane change and a change back to the original lane. A trajectory-tracking controller based on sliding mode control calculates the control inputs to make the host vehicle travel along the reference trajectory. Finally, simulations and experiments using a driving simulator are conducted. They demonstrate that the proposed dynamic automated lane change maneuver can avoid potential collisions during the lane change process effectively.

236 citations


"Path tracking control for inverse p..." refers methods in this paper

  • ...[8], designed a dynamic automated lane change maneuver based on vehicle-tovehicle communication to accomplish an automated lane change and eliminate potential collisions during the lane change process....

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Journal ArticleDOI
TL;DR: A lane changing assistance system that advises drivers of safe gaps for making mandatory lane changes at lane drops is developed and predicts driver decisions on whether to merge or not as a function of certain input variables using Bayes and decision-tree methods.
Abstract: A lane changing assistance system that advises drivers of safe gaps for making mandatory lane changes at lane drops is developed. Bayes classifier and decision-tree methods were applied to model lane changes. Detailed vehicle trajectory data from the Next Generation Simulation (NGSIM) data set were used for model development (U.S. Highway 101) and testing (Interstate 80). The model predicts driver decisions on whether to merge or not as a function of certain input variables. The best results were obtained when both Bayes and decision-tree classifiers were combined into a single classifier using a majority voting principle. The prediction accuracy was 94.3% for nonmerge events and 79.3% for merge events. In a lane change assistance system, the accuracy of nonmerge events is more critical than merge events. Misclassifying a nonmerge event as a merge event could result in a traffic crash, whereas misclassifying a merge event as a nonmerge event would only result in a lost opportunity to merge. Sensitivity analysis performed by assigning higher misclassification cost for nonmerge events resulted in even higher accuracy for nonmerge events but lower accuracy for merge events.

163 citations


"Path tracking control for inverse p..." refers methods in this paper

  • ...[13], proposed an algorithm which is distributed in nature and made use of vehicle-to-vehicle and/or vehicle-to-infrastructure communication technologies to judiciously make local lane-change decisions while guaranteeing that no collisions will occur....

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Journal ArticleDOI
TL;DR: A Fuzzy Inference System (FIS) which models a driver’s binary decision to or not to execute a discretionary lane changing move on freeways and has a potential to be implemented in lane change advisory systems, in autonomous vehicles, as well as microscopic traffic simulation tools.
Abstract: This paper presents a Fuzzy Inference System (FIS) which models a driver’s binary decision to or not to execute a discretionary lane changing move on freeways. It answers the following question “Is it time to begin to move into the target lane?” after the driver has decided to change lane and have selected the target lane. The system uses four input variables: the gap between the subject vehicle and the preceding vehicle in the original lane, the gap between the subject vehicle and the preceding vehicle in the target lane, the gap between the subject vehicle and the following vehicle in the target lane, and the distance between the preceding and following vehicles in the target lanes. The input variables were selected based on the outcomes of a drivers survey, and can be measured by sensors instrumented in the subject vehicle. The FIS was trained with Next Generation SIMulation (NGSIM) vehicle trajectory data collected at the I-80 Freeway in Emeryville, California, and then tested with data collected at the U.S. Highway 101 in Los Angeles, California. The results of the test have shown that the system made lane change recommendations of “yes, change lane” with 82.2% accuracy, and “no, do not change lane” with 99.5% accuracy. These accuracies are better than the same performance measures given by the TRANSMODELER’s gap acceptance model for discretionary lane change on freeways, which is also calibrated with NGSIM data. The developed FIS has a potential to be implemented in lane change advisory systems, in autonomous vehicles, as well as microscopic traffic simulation tools.

134 citations


"Path tracking control for inverse p..." refers methods in this paper

  • ...[9], presented a Fuzzy Inference System (FIS) which models a driver’s binary decision to or not to execute a discretionary lane changing move...

    [...]

Journal ArticleDOI
TL;DR: This study proposes a novel coordinated ACC system with a lane-change assistance function, which enables dual-target tracking, safe lane change, and longitudinal ride comfort, and develops a coordinated control algorithm using model predictive control theory.
Abstract: To address the problem caused by a conventional adaptive cruise control (ACC) system, which hinders drivers from changing lanes, in this study we propose a novel coordinated ACC system with a lane-change assistance function, which enables dual-target tracking, safe lane change, and longitudinal ride comfort We first analyze lane-change risk by calculating minimum safety spacing between the host vehicle and surrounding vehicles and then develop a coordinated control algorithm using model predictive control theory Tracking performance is designed on the basis of tracking errors of the host car and two leading vehicles, safety performance is realized by considering the safe distance between the host car and surrounding vehicles, and ride comfort performance is realized by limiting the vehicle's longitudinal acceleration Driver-in-the-loop tests performed on a driving simulator confirm that the proposed ACC system can overcome the disadvantages of conventional ACC and achieves multiobjective coordination in the lane-change process

91 citations


"Path tracking control for inverse p..." refers methods in this paper

  • ...[15], proposed a multiple cycle sine-wave steering input (MCSSI) maneuver to solve the single lane-change maneuvers problem exploring the effect of the transient response....

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Journal ArticleDOI

62 citations


"Path tracking control for inverse p..." refers background in this paper

  • ...Then the equation of the transfer function between yaw rate and front steering angle is obtained [20]:...

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