Automatic Parking Path Planning and Tracking Control Research for Intelligent Vehicles

Li, Chenxu; Jiang, Haobin; Ma, Shidian; Jiang, Shaokang; Li, Yue

doi:10.3390/app10249100

Cited by 20 publications

(9 citation statements)

References 22 publications

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“…It is based on the local outlier factor detection algorithm, in which adaptive diagnosis and compensation are made for data anomalies of four-wheel speedometers. The preview correction method is used for parking path planning in [20]. This method can not only detect the curvature outliers in the parking path, but also correct and optimize a reasonable parking trajectory in advance.…”

Section: Related Workmentioning

confidence: 99%

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Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State

Piao

Zhang

Chang

et al. 2021

Sensors

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The goal of automatic parking system is to accomplish the vehicle parking to the specified space automatically. It mainly includes parking space recognition, parking space matching, and trajectory generation. It has been developed enormously, but it is still a challenging work due to parking space recognition error and trajectory generation for vehicle nonparallel initial state with parking space. In this study, the authors propose multi-sensor information ensemble for parking space recognition and adaptive trajectory generation method, which is also robust to vehicle nonparallel initial state. Both simulation and real vehicle experiments are conducted to prove that the proposed method can improve the automatic parking system performance.

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Section: Related Workmentioning

confidence: 99%

“…The experimental process is the same as that of single sensor application. Figure 15 shows the measured and reference data obtained by Equation (20). In the double sensor method experiments, the ranging sensors are located on the right-hand side of the vehicle.…”

Section: Analysis and Comparisonmentioning

confidence: 99%

Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State

Piao

Zhang

Chang

et al. 2021

Sensors

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“…The method of path planning based on geometry has high computational efficiency, good real-time performance, and is convenient for engineering implementation [4]. Common parking path curves designed include fifth-order polynomial [5], arc [6], Bézier curve, etc. For example, the path in parallel parking is divided into the entry section to guide the car to approach the parking space and the adjustment section to guide the car to adjust the target pose.…”

Section: Introductionmentioning

confidence: 99%

Path Planning Optimization for Driverless Vehicle in Parallel Parking Integrating Radial Basis Function Neural Network

Wang

Hou

et al. 2021

Applied Sciences

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To optimize performances such as continuous curvature, safety, and satisfying curvature constraints of the initial planning path for driverless vehicles in parallel parking, a novel method is proposed to train control points of the Bézier curve using the radial basis function neural network method. Firstly, the composition and working process of an autonomous parking system are analyzed. An experiment concerning parking space detection is conducted using an Arduino intelligent minicar with ultrasonic sensor. Based on the analysis of the parallel parking process of experienced drivers and the idea of simulating a human driver, the initial path is planned via an arc-line-arc three segment composite curve and fitted by a quintic Bézier curve to make up for the discontinuity of curvature. Then, the radial basis function neural network is established, and slopes of points of the initial path are used as input to train and obtain horizontal ordinates of four control points in the middle of the Bézier curve. Finally, simulation experiments are carried out by MATLAB, whereby parallel parking of driverless vehicle is simulated, and the effects of the proposed method are verified. Results show the trained and optimized Bézier curve as a planning path meets the requirements of continuous curvature, safety, and curvature constraints, thus improving the abilities for parallel parking in small parking spaces.

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“…Similar to previous methods, both of these approaches utilize their sensors to detect a parking slot or avoid curbs and corners of the parked vehicles along with the parking space. A similar approach can also be found in [9]. All of these methods utilize a fuzzy logic theory to implement human intelligence linguistically.…”

Section: Introductionmentioning

confidence: 99%

An adaptive motion planning algorithm for obstacle avoidance in autonomous vehicle parking

Nakrani

Joshi

2021

IJ-AI

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In the recent era, machine learning-based autonomous vehicle parking and obstacle avoidance navigation have drawn increased attention. An intelligent design is needed to solve the autonomous vehicles related problems. Presently, autonomous parking systems follow path planning techniques that generally do not possess a quality and a skill of natural adapting behavior of a human. Most of these designs are built on pre-defined and fixed criteria. It needs to be adaptive with respect to the vehicle dynamics. A novel adaptive motion planning algorithm is proposed in this paper that incorporates obstacle avoidance capability into a standalone parking controller that is kept adaptive to vehicle dimensions to provide human-like intelligence for parking problems. This model utilizes fuzzy membership thresholds concerning vehicle dimensions and vehicle localization to enhance the vehicle’s trajectory during parking when taking into consideration obstacles. It is generalized for all segments of cars, and simulation results prove the proposed algorithm’s effectiveness.

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Automatic Parking Path Planning and Tracking Control Research for Intelligent Vehicles

Cited by 20 publications

References 22 publications

Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State

Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State

Path Planning Optimization for Driverless Vehicle in Parallel Parking Integrating Radial Basis Function Neural Network

An adaptive motion planning algorithm for obstacle avoidance in autonomous vehicle parking

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