scholarly journals Lane-change path planning and control method for self-driving articulated trucks

2020 ◽  
Vol 3 (2) ◽  
pp. 49-66
Author(s):  
Tao Peng ◽  
Xingliang Liu ◽  
Rui Fang ◽  
Ronghui Zhang ◽  
Yanwei Pang ◽  
...  
Keyword(s):  
Decision Making ◽  
Path Planning ◽  
Robust Stability ◽  
Feedback Linearization ◽  
Control Method ◽  
Intelligent Vehicles ◽  
Lane Change ◽  
Content Type ◽  
Trajectory Model ◽  
Articulated Vehicles

Purpose This study aims to develop an automatic lane-change mechanism on highways for self-driving articulated trucks to improve traffic safety. Design/methodology/approach The authors proposed a novel safety lane-change path planning and tracking control method for articulated vehicles. A double-Gaussian distribution was introduced to deduce the lane-change trajectories of tractor and trailer coupling characteristics of intelligent vehicles and roads. With different steering and braking maneuvers, minimum safe distances were modeled and calculated. Considering safety and ergonomics, the authors invested multilevel self-driving modes that serve as the basis of decision-making for vehicle lane-change. Furthermore, a combined controller was designed by feedback linearization and single-point preview optimization to ensure the path tracking and robust stability. Specialized hardware in the loop simulation platform was built to verify the effectiveness of the designed method. Findings The numerical simulation results demonstrated the path-planning model feasibility and controller-combined decision mechanism effectiveness to self-driving trucks. The proposed trajectory model could provide safety lane-change path planning, and the designed controller could ensure good tracking and robust stability for the closed-loop nonlinear system. Originality/value This is a fundamental research of intelligent local path planning and automatic control for articulated vehicles. There are two main contributions: the first is a more quantifiable trajectory model for self-driving articulated vehicles, which provides the opportunity to adapt vehicle and scene changes. The second involves designing a feedback linearization controller, combined with a multi-objective decision-making mode, to improve the comprehensive performance of intelligent vehicles. This study provides a valuable reference to develop advanced driving assistant system and intelligent control systems for self-driving articulated vehicles.

scholarly journals Automatic Parking Path Planning and Tracking Control Research for Intelligent Vehicles

2020 ◽  
Vol 10 (24) ◽  
pp. 9100
Author(s):  
Chenxu Li ◽  
Haobin Jiang ◽  
Shidian Ma ◽  
Shaokang Jiang ◽  
Yue Li
Keyword(s):  
Path Planning ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Vehicle Control ◽  
Path Tracking ◽  
Intelligent Vehicles ◽  
Parking System ◽  
Automatic Parking ◽  
Real Vehicle

As a key technology for intelligent vehicles, automatic parking is becoming increasingly popular in the area of research. Automatic parking technology is available for safe and quick parking operations without a driver, and improving the driving comfort while greatly reducing the probability of parking accidents. An automatic parking path planning and tracking control method is proposed in this paper to resolve the following issues presented in the existing automatic parking systems, that is, low degree of automation in vehicle control; lack of conformity between segmented path planning and real vehicle motion models; and low success rates of parking due to poor path tracking. To this end, this paper innovatively proposes preview correction which can be applied to parking path planning, and detects the curvature outliers in the parking path through the preview algorithm. In addition, it is also available for correction in advance to optimize the reasonable parking path. Meanwhile, the dual sliding mode variable structure control algorithm is used to formulate path tracking control strategies to improve the path tracking control effect and the vehicle control automation. Based on the above algorithm, an automatic parking system was developed and the real vehicle test was completed, thus exploring a highly intelligent automatic parking technology roadmap. This paper provides two key aspects of system solutions for an automatic parking system, i.e., parking path planning and path tracking control.

A novel decision-making unit for automated maneuver of articulated vehicles in real traffic situations

2019 ◽  
Vol 234 (1) ◽  
pp. 152-171 ◽  
Author(s):  
Saeed Shojaei ◽  
Ali Rahmani Hanzaki ◽  
Shahram Azadi ◽  
Mohammad Amin Saeedi
Keyword(s):  
Decision Making ◽  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Time Range ◽  
Lane Change ◽  
Mode Control ◽  
Articulated Vehicle ◽  
Double Lane Change ◽  
Real Traffic

In this paper, a new decision-making algorithm for double lane change maneuver of an articulated vehicle in real dynamic circumstances is studied. A novel method for determining the decision conditions is used based on the articulated vehicle kinematics and dynamics. Through this method, several points of the articulated vehicle are considered in various situations when conducting double lane change maneuver, and the critical points are determined. A new realistic dynamic method is used based on a 16-degrees of freedom dynamic model of the articulated vehicle. The sliding mode control method is utilized to increase the method efficiency. Therefore, the least safe time to perform the double lane change maneuver is extracted based on the sliding mode control method as tracking control. A new Articulated Vehicle Least safe time formulation is determined for dynamic circumstances. Based on the results of simulated test, the acceptable time range is also established for conducting the lane change maneuver. The lane change maneuver is generalized to the double lane change maneuver. Decision-making algorithm is introduced based on real traffic situations. The dynamic approach and the decision-making algorithm are verified. Results show the validity of the reflected method meaning that the decision-making algorithm is acceptable.

Flight controller design for aircraft low altitude airdrop

2016 ◽  
Vol 88 (6) ◽  
pp. 689-696 ◽  
Author(s):  
Ri Liu ◽  
Xiuxia Sun ◽  
Wenhan Dong
Keyword(s):  
Flight Control ◽  
Feedback Linearization ◽  
Control Method ◽  
Controller Design ◽  
Sliding Mode ◽  
Integral Term ◽  
Content Type ◽  
Integral Sliding Mode ◽  
Sliding Manifold ◽  
Low Altitude

Purpose During low altitude airdrop operations, the heavy cargo moving inside and the sudden dropping out exert serious threats on the aircraft safety and mission performance. This paper aims to propose an efficient flight control method for the airdrop operations. Design/methodology/approach A novel controller which combines feedback linearization with nonlinear integral sliding mode control is proposed. The aircraft airdrop model is decoupled and linearized by using the feedback linearization technique. On this basis, an integral sliding mode controller is designed to stabilize the speed and pitch attitude of the aircraft. In the sliding manifold, one class of nonlinear functions with the property of “smaller errors correspond to bigger gains and bigger errors correspond to saturated gains” is introduced to form the integral term; thus, the overcompensation of the integral term to big errors is omitted, and the dynamic response performance is improved. Lyapunov-based stability analysis shows that the controller could completely reject model uncertainties by choosing proper controller parameters. Findings The flight control system with strong robustness could meet the low altitude airdrop indexes in the maximum weight cargo airdrop task. Originality/value This paper fulfils an urgent need to study how to control the aircraft to guarantee mission performance and flight safety during the low altitude airdrop operations.

Design, Modeling, and Control of a New Manipulating Climbing Robot Through Infrastructures Using Adaptive Force Control Method

Robotica ◽  
2020 ◽  
Vol 38 (11) ◽  
pp. 2039-2059
Author(s):  
V. Boomeri ◽  
H. Tourajizadeh
Keyword(s):  
Path Planning ◽  
Force Control ◽  
Feedback Linearization ◽  
Inverse Dynamics ◽  
Control Method ◽  
Climbing Robot ◽  
Modeling And Control ◽  
Risk Of Death ◽  
And Control ◽  
Adaptive Force Control

SUMMARYIn this paper, design, modeling, and control of a grip-based climbing robot are performed, which consists of a triangular chassis and three actuating legs. This robot can climb through any trusses, pipeline, and scaffolds structures and can perform any inspectional and operational tasks in the high height which decreases the falling danger of operation and increases the safety of the workers. The proposed robot can be substituted for the workers to decrease the risk of death danger and increase the safety of the operation. Since these kinds of infrastructures are truss shaped, the traditional wheel-based climbing robots are not able to travel through these structures. Therefore, in this paper, a grip-based climbing robot is designed to accomplish the climbing process through the trusses and infrastructures in order to perform inspecting and manipulating tasks. Hence, a proper mechanism for the mentioned robot is designed and its related kinematic and kinetic models are developed. Robot modeling is investigated for two different modes including climbing and manipulating phases. Considering the redundancy of the proposed robot and the parallel mechanism employed in it, the active joints are selected in a proper way and its path planning is performed to accomplish the required missions. Concerning the climbing mode, the required computed torque method (CTM) is calculated by the inverse dynamics of the robot. However, for the manipulation mode, after path planning, two controlling strategies are employed, including feedback linearization (FBL) and adaptive force control, and their results are compared as well. It is shown that the latter case is preferable since the external forces implemented on the end effector tool is not exactly predetermined and thus, the controller should adapt the robot with the exerted force pattern of the manipulator. The modeling correctness is investigated by performing some analytic and comparative simulation scenarios in the MATLAB and comparing the results with the MSC-ADAMS ones, for both climbing and manipulating phases. The efficiency of the designed controller is also proved by implementing an unknown force pattern on the manipulator to check its efficiency toward estimating the mentioned implemented forces and compensating the errors. It is shown that the designed robot can successfully climb through a truss and perform its operating task by the aid of the employed adaptive controller in an accurate way.

Impact of relatedness, uncertainty and slack on corporate entrepreneurship decisions

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Robert Garrett ◽  
Shaunn Mattingly ◽  
Jeff Hornsby ◽  
Alireza Aghaey
Keyword(s):  
Decision Making ◽  
Hierarchical Linear Modeling ◽  
Cognitive Strategies ◽  
Corporate Entrepreneurship ◽  
New Venture ◽  
Organizational Level ◽  
Linear Modeling ◽  
Slack Resources ◽  
Content Type ◽  
Positive Effect

PurposeThe purpose of this study is to evaluate the effect of opportunity relatedness and uncertainty on the decision of a corporate entrepreneur to pursue a venturing opportunity.Design/methodology/approachThe study uses a conjoint experimental design to reveal the structure of respondents' decision policies. Data were gathered from 47 useable replies from corporate entrepreneurs and were analyzed with hierarchical linear modeling (HLM).FindingsResults show that product relatedness, market relatedness, perceived certainty about expected outcomes and slack resources all have a positive effect on the willingness of a corporate entrepreneur to pursue a new venture idea. Moreover, slack was found to diminish the positive effect of product relatedness on the likelihood to pursue a venturing opportunity.Practical implicationsBy providing a better understanding of decision-making schemas of corporate entrepreneurs, the findings of this study help improve the practice of entrepreneurship at the organizational level. In order to make more accurate opportunity assessments, corporate entrepreneurs need to be aware of their cognitive strategies and need to factor in the salient criteria affecting such assessments.Originality/valueThis paper adds to the limited understanding of corporate-level decision-making with regard to pursuing venturing opportunities. More specifically, the paper adds new insights regarding how relatedness and uncertainty affect new venture opportunity assessments in the presence (or lack thereof) of slack resources.

Making investment decisions in stock markets using a forecasting-Markowitz based decision-making approaches

2019 ◽  
Vol 15 (2) ◽  
pp. 647-659 ◽  
Author(s):  
Zahra Moeini Najafabadi ◽  
Mehdi Bijari ◽  
Mehdi Khashei
Keyword(s):  
Decision Making ◽  
Time Series ◽  
Stock Markets ◽  
Time Series Prediction ◽  
Investment Decisions ◽  
Rate Of Return ◽  
Expected Returns ◽  
Prediction Methods ◽  
Content Type ◽  
Markowitz Model

Purpose This study aims to make investment decisions in stock markets using forecasting-Markowitz based decision-making approaches. Design/methodology/approach The authors’ approach offers the use of time series prediction methods including autoregressive, autoregressive moving average and artificial neural network, rather than calculating the expected rate of return based on distribution. Findings The results show that using time series prediction methods has a significant effect on improving investment decisions and the performance of the investments. Originality/value In this study, in contrast to previous studies, the alteration in the Markowitz model started with the investment expected rate of return. For this purpose, instead of considering the distribution of returns and determining the expected returns, time series prediction methods were used to calculate the future return of each asset. Then, the results of different time series methods replaced the expected returns in the Markowitz model. Finally, the overall performance of the method, as well as the performance of each of the prediction methods used, was examined in relation to nine stock market indices.

scholarly journals Automatic Lane-Changing Decision Based on Single-Step Dynamic Game with Incomplete Information and Collision-Free Path Planning

Actuators ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 173
Author(s):  
Hongbo Wang ◽  
Shihan Xu ◽  
Longze Deng
Keyword(s):  
Path Planning ◽  
Dynamic Game ◽  
Single Step ◽  
Bézier Curve ◽  
Vehicle Safety ◽  
Bezier Curve ◽  
Lane Change ◽  
Hardware In The Loop ◽  
Power Performance ◽  
Lane Changing

Traffic accidents are often caused by improper lane changes. Although the safety of lane-changing has attracted extensive attention in the vehicle and traffic fields, there are few studies considering the lateral comfort of vehicle users in lane-changing decision-making. Lane-changing decision-making by single-step dynamic game with incomplete information and path planning based on Bézier curve are proposed in this paper to coordinate vehicle lane-changing performance from safety payoff, velocity payoff, and comfort payoff. First, the lane-changing safety distance which is improved by collecting lane-changing data through simulated driving, and lane-changing time obtained by Bézier curve path planning are introduced into the game payoff, so that the selection of the lane-changing start time considers the vehicle safety, power performance and passenger comfort of the lane-changing process. Second, the lane-changing path without collision to the forward vehicle is obtained through the constrained Bézier curve, and the Bézier curve is further constrained to obtain a smoother lane-changing path. The path tracking sliding mode controller of front wheel angle compensation by radical basis function neural network is designed. Finally, the model in the loop simulation and the hardware in the loop experiment are carried out to verify the advantages of the proposed method. The results of three lane-changing conditions designed in the hardware in the loop experiment show that the vehicle safety, power performance, and passenger comfort of the vehicle controlled by the proposed method are better than that of human drivers in discretionary lane change and mandatory lane change scenarios.

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