Research on Automatic Parking Systems Based on Parking Scene Recognition

Ma, Shidian; Jiang, Haobin; Han, Mu; Xie, Ju; Li, Chenxu

doi:10.1109/access.2017.2760201

Cited by 54 publications

(28 citation statements)

References 17 publications

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“…However, both methods do not consider the conditions that obstacles locate around parking slots. An automatic parking system based on scene recognition is proposed to recognize a perpendicular parking scenario and have potential to complete parking mission by developed motion planner and vehicle controller [31]. Unfortunately, the vehicle controller is not simulated to track a perpendicular parking path.…”

Section: Literature Surveymentioning

confidence: 99%

See 1 more Smart Citation

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

Jhang

Lian

2020

IEEE Access

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Autonomous parking techniques can be used to tackle the lacking problem of parking spaces. In this paper, a sampling-based motion planner consisting of optimizing bidirectional rapidly-exploring random trees* (Bi-RRT*) and parking-oriented model predictive control (MPC) is proposed to properly deal with various parking scenarios. The optimal Bi-RRT* approach aims to improve the common defects of traditional sampling-based motion planners, such as uncertainties of path quality and consistency, and exploring inefficiency in narrow spaces. For this reason, the proposed motion planner is able to overcome strict environments with obstacles and narrow spaces. The parking-oriented MPC is then designed for steering and speed controls simultaneously for accurately and smoothly tracking parking paths. Furthermore, the proposed controller is dedicated to work under the practical scenarios, such as vehicle considerations, realtime control, and signal delay. To verify the effects of the proposed autonomous parking system, extensive simulations and experiments are conducted in common and strict parking scenarios, such as perpendicular parking, parallel parking. The simulation results not only verify the effects of each technical element, but also show the capability to deal with the various parking scenarios. Furthermore, various on-car experiments sufficiently demonstrate that the proposed system can be actually implemented in everyday life. INDEX TERMS Autonomous parking system, sampling-based motion planning, parking-oriented vehicle control, bidirectional rapidly-exploring random trees* (Bi-RRT*), model predictive control (MPC), perpendicular parking, parallel parking.

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Section: Literature Surveymentioning

confidence: 99%

“…Unfortunately, the vehicle controller is not simulated to track a perpendicular parking path. That is, the motion planner and vehicle controller have not been combined to deal with perpendicular parking scenario in [31].…”

Section: Literature Surveymentioning

confidence: 99%

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

Jhang

Lian

2020

IEEE Access

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“…The current intelligent parking system has excellent advantages in terms of rapid vehicle approach, parking space guidance and fast payment. However, the function of reverse car search needs to be improved, especially in realizing real-time path guidance for vehicle owners [25][26] . The algorithm commonly used in parking guidance systems is Dijkstra, A-star path-finding algorithm for path planning.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case

Wei¹,

Dong²,

Liao³

2020

SRR

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In order to solve the problems of low utilization rate of large parking lots and low efficiency of parking turnover, it is proposed to use A-star algorithm to plan the shortest path for finding a car, and run it in Android system to realize reverse car-searching. By analyzing the current situation of large underground parking lot barriers, A-star algorithm converts the starting point to the destination route into the corresponding parking space to the destination parking space path, calculates the optimal path and provides real-time path car navigation for the vehicle owner. According to the path searched by the A-star algorithm in the Android system, the time spent by the user to blindly search for the vehicle is largely saved, and the parking space utilization rate and the parking turnover rate are effectively improved. Therefore, the research has certain application value in the large parking lots.

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“…Path tracking controls the lateral movement of vehicle during the parking process and requires the path tracking error to be as small as possible. Ma et al [22] designed an automatic parking path tracking controller based on the vehicle dynamics model to control the vehicle tracking planning route. However, the design of the controller system is more complicated and the accuracy is difficult to control.…”

Section: Introductionmentioning

confidence: 99%

Laser‐based SLAM automatic parallel parking path planning and tracking for passenger vehicle

Song

Zhang

et al. 2019

IET Intelligent Transport Systems

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Research on Automatic Parking Systems Based on Parking Scene Recognition

Cited by 54 publications

References 17 publications

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

An Autonomous Parking System of Optimally Integrating Bidirectional Rapidly-Exploring Random Trees and Parking-Oriented Model Predictive Control

Application of Reverse Car-seeking in Large Underground Parking Lot Based on A Star Algorithm: A Real Case

Laser‐based SLAM automatic parallel parking path planning and tracking for passenger vehicle

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