Intelligent Vehicle's Path Tracking Based on Fuzzy Control

Xiong, Bo; Qu, Shaojian

doi:10.1016/s1570-6672(09)60034-9

Cited by 24 publications

(13 citation statements)

References 1 publication

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“…The purpose of these studies is to enhance the transportation performance and safety. [1][2][3][4] Since commercial vehicles have a large share in transportation and transit systems, a number of vehicle manufacturers have recently introduced their self-steering articulated vehicles. This is an important step toward the fully autonomous versions.…”

Section: Introductionmentioning

confidence: 99%

Automatic steering control in tractor semi-trailer vehicles for low-speed maneuverability enhancement

Abroshan

Taiebat

Goodarzi

et al. 2016

Proceedings of the IMechE

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In this paper, a controller for an automated steering articulated vehicle with the special capability to reduce off-tracking in low-speed maneuvers is proposed. Conventional tractor-trailers have a large off-tracking in low-speed maneuvers. In the proposed vehicle, all wheels of the tractor and trailer are steerable (all wheel steering). The controllers of the tractor and trailer work independently, and each one consists of two layers. A fuzzy controller and a PID controller are designed in the upper and lower layer, respectively, to control the actuators. The aim of the controller is to ensure that the end points of both the tractor and the trailer exactly follow the path of tractor's first point. To assess the performance of proposed controller as well as steerability effect of all wheels in low speeds, the TruckSim simulation software is used. The simulation results confirm that the proposed approach improves the maneuverability and accuracy of path tracking not only compared to conventional vehicles but also to the conventional tractor-active trailer scheme, which was previously proposed by a number of studies. Additionally, it reduces lateral tire forces to enhance the working life.

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Section: Introductionmentioning

confidence: 99%

Automatic steering control in tractor semi-trailer vehicles for low-speed maneuverability enhancement

Abroshan

Taiebat

Goodarzi

et al. 2016

Proceedings of the IMechE

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“…In order to adaptive track the practical white path, the fuzzy algorithms are applied to handle the angel θ and deviation d (Xiong and Qu, 2010). Firstly, based on a large number of experiments, we establish the fuzzy control rules on steering angle regulation A and expected speed V. Path track diagram is shown in Figure 6.…”

Section: Path Trackmentioning

confidence: 99%

A small intelligent car system based on fuzzy control and CCD camera

Tian

Chan

et al. 2012

IJMIC

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A small intelligent car system based on MCU SPCE061A and MCU 89S52 was introduced. Firstly, CCD camera was used as its path recognition device to extract path information through image recognition. Based on fuzzy strategy and the least square method, two-dimensional information involving gear angle between the car and the path was measured. Then fuzzy PD controller was implemented based on MCU, which can guarantee to track accurately. Finally, experiment results are given to demonstrate that the designed system can track random path at smooth speed, and the overall system is stable and accurate. His main research interest is in the area of non-linear control theory, system modelling and control. He has published over 50 papers on these topics and provided consultancy to various industries. He has also published a monograph on sliding mode control theory and application in China.

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“…Additionally, for obstacle detection, ultrasonic as well as infrared (IR) sensors have been widely used in literature. IR sensors are based on sound sensor and cannot operate under dark condition, whereas ultrasonic sensors have linear output characteristics and can detect all types of obstacles [14][15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy-Based Approach Using IoT Devices for Smart Home to Assist Blind People for Navigation

Tayyaba

Ashraf

Alquthami

et al. 2020

Sensors

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The demand of devices for safe mobility of blind people is increasing with advancement in wireless communication. Artificial intelligent devices with multiple input and output methods are used for reliable data estimation based on maximum probability. A model of a smart home for safe and robust mobility of blind people has been proposed. Fuzzy logic has been used for simulation. Outputs from the internet of things (IoT) devices comprising sensors and bluetooth are taken as input of the fuzzy controller. Rules have been developed based on the conditions and requirements of the blind person to generate decisions as output. These outputs are communicated through IoT devices to assist the blind person or user for safe movement. The proposed system provides the user with easy navigation and obstacle avoidance.

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Intelligent Vehicle's Path Tracking Based on Fuzzy Control

Cited by 24 publications

References 1 publication

Automatic steering control in tractor semi-trailer vehicles for low-speed maneuverability enhancement

Automatic steering control in tractor semi-trailer vehicles for low-speed maneuverability enhancement

A small intelligent car system based on fuzzy control and CCD camera

Fuzzy-Based Approach Using IoT Devices for Smart Home to Assist Blind People for Navigation

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