Autonomous Reverse Parking System Based on Robust Path Generation and Improved Sliding Mode Control

Du, Xinxin; Tan, Kok Kiong

doi:10.1109/tits.2014.2354423

Cited by 82 publications

(44 citation statements)

References 24 publications

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“…For example, the steerable filter ( [69,85]) is based on second order derivatives of 2D Gaussians, and ridge detector ( [95,96]) is based on tensor field construction of first order derivatives. Both methods are able to obtain the response of gradient directions which facilitates to remove outliers if their directions deviate too much from the presumed lane line direction.…”

Section: Lane Line Marking Detectionmentioning

confidence: 99%

Perception, Planning, Control, and Coordination for Autonomous Vehicles

et al. 2017

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Autonomous vehicles are expected to play a key role in the future of urban transportation systems, as they offer potential for additional safety, increased productivity, greater accessibility, better road efficiency, and positive impact on the environment. Research in autonomous systems has seen dramatic advances in recent years, due to the increases in available computing power and reduced cost in sensing and computing technologies, resulting in maturing technological readiness level of fully autonomous vehicles. The objective of this paper is to provide a general overview of the recent developments in the realm of autonomous vehicle software systems. Fundamental components of autonomous vehicle software are reviewed, and recent developments in each area are discussed.

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Section: Lane Line Marking Detectionmentioning

confidence: 99%

Perception, Planning, Control, and Coordination for Autonomous Vehicles

et al. 2017

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“…This method can recognize various types of parking-slot-markings based on two points of a parking-slot entrance provided by the driver. In [33], Du and Tan developed a reverse parking system. To detect the parking-slot, they first applied a ridge detector on the image and then medial axes of the slot markings can be obtained after the steps of noise filtering, connected components labeling, and removal of components with a small number of pixels.…”

Section: Related Workmentioning

confidence: 99%

“…However, their system relies on human drivers to identify an empty parking-slot first before initiating the parking process. The apparent drawback of the methods in [31][32][33] is that they are not fully automatic.…”

Section: Related Workmentioning

confidence: 99%

Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach

Zhang

Huang

et al. 2018

Symmetry

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Recent years have witnessed a growing interest in developing automatic parking systems in the field of intelligent vehicles. However, how to effectively and efficiently locating parking-slots using a vision-based system is still an unresolved issue. Even more seriously, there is no publicly available labeled benchmark dataset for tuning and testing parking-slot detection algorithms. In this paper, we attempt to fill the above-mentioned research gaps to some extent and our contributions are twofold. Firstly, to facilitate the study of vision-based parking-slot detection, a large-scale parking-slot image database is established. This database comprises 8600 surround-view images collected from typical indoor and outdoor parking sites. For each image in this database, the marking-points and parking-slots are carefully labeled. Such a database can serve as a benchmark to design and validate parking-slot detection algorithms. Secondly, a learning-based parking-slot detection approach, namely PSD L , is proposed. Using PSD L , given a surround-view image, the marking-points will be detected first and then the valid parking-slots can be inferred. The efficacy and efficiency of PSD L have been corroborated on our database. It is expected that PSD L can serve as a baseline when the other researchers develop more sophisticated methods.

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“…25 With the constant improvement of popularity rate of car, there is less and less space for parking on urban roads, but assisted parking system provides a great help for solving the parking in a narrow space, so it has a wide application space in the future. 26 Refer to Figures 2 and 3 for the schematic diagrams of parking route design and parking effects.…”

Section: Preliminariesmentioning

confidence: 99%

Integrated model of assisted parking system and performance evaluation with entropy weight extended analytic hierarchy process and two-tuple linguistic information

Hua

Jiang

et al. 2016

Advances in Mechanical Engineering

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Evaluating comprehensive performance of assisted parking system has been a very important issue for car companies for years, because the overall performance of assisted parking system directly influences car intellectualization and customers' degree of satisfaction. Therefore, this article proposes two-tuple linguistic analytic hierarchy process to evaluate assisted parking system so as to avoid information loss during the processes of evaluation integration. The performance evaluation attributes for assisted parking system are established initially. Subsequently, the information entropy theory is proposed to improve the evaluation attribute weight determined by analytic hierarchy process for the influencing factors of the randomness in parking test process. Furthermore, the evaluation attribute measure values of comprehensive performance are calculated and the assisted parking system evaluation results are obtained with ordered weighted averaging operator. Finally, numerical examples of vehicle types equipped with eight different assisted parking systems and computational results are presented.

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Autonomous Reverse Parking System Based on Robust Path Generation and Improved Sliding Mode Control

Cited by 82 publications

References 24 publications

Perception, Planning, Control, and Coordination for Autonomous Vehicles

Perception, Planning, Control, and Coordination for Autonomous Vehicles

Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach

Integrated model of assisted parking system and performance evaluation with entropy weight extended analytic hierarchy process and two-tuple linguistic information

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