Algorithm and hardware implementation for visual perception system in autonomous vehicle: A survey

Shi, Weijing; Alawieh, Mohamed Baker; Li, Xin; Yu, Huafeng

doi:10.1016/j.vlsi.2017.07.007

Cited by 132 publications

(66 citation statements)

References 16 publications

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“…MLS data can be used for perceiving street environments [82] and detecting the precise position, orientation and geometric features of vehicles [91]. Therefore, MLS is a crucial component for visual perception system in autonomous vehicle [17]. For autonomous vehicle driving, three MLS applications are particularly important: vehicle and pedestrian detection, lane detection, and drivable surface detection [18,19,92].…”

Section: Autonomous Vehicle Drivingmentioning

confidence: 99%

“…Given those advantages, MLS data have been used in recent years in a wide range of urban applications, including urban land cover analysis [6][7][8][9], digital 3D city modeling [10,11], urban environment monitoring [12][13][14][15][16], and autonomous vehicle driving [17][18][19]. The use of these data has However, in contrast to the rapid development of MLS technology and its huge potential in various applications, we still lack a comprehensive review of the latest progresses, common issues, and remaining challenges of MLS applications over urban areas.…”

Section: Introductionmentioning

confidence: 99%

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A Survey of Mobile Laser Scanning Applications and Key Techniques over Urban Areas

et al. 2019

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Urban planning and management need accurate three-dimensional (3D) data such as light detection and ranging (LiDAR) point clouds. The mobile laser scanning (MLS) data, with up to millimeter-level accuracy and point density of a few thousand points/m2, have gained increasing attention in urban applications. Substantial research has been conducted in the past decade. This paper conducted a comprehensive survey of urban applications and key techniques based on MLS point clouds. We first introduce the key characteristics of MLS systems and the corresponding point clouds, and present the challenges and opportunities of using the data. Next, we summarize the current applications of using MLS over urban areas, including transportation infrastructure mapping, building information modeling, utility surveying and mapping, vegetation inventory, and autonomous vehicle driving. Then, we review common key issues for processing and analyzing MLS point clouds, including classification methods, object recognition, data registration, data fusion, and 3D city modeling. Finally, we discuss the future prospects for MLS technology and urban applications.

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Section: Autonomous Vehicle Drivingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Survey of Mobile Laser Scanning Applications and Key Techniques over Urban Areas

et al. 2019

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“…The problem is that validating a complex autonomous system accurately and efficiently is non-trivial. Any visual perception system based on machine learning cannot be 100 [2]. Hence, the system may fail for a specific input pattern and accurately estimating its failure rate can be extremely time-consuming [3].…”

Section: Introductionmentioning

confidence: 99%

Robust Control for Over-Actuated Vehicles

Kissai

Monsuez

Martinez

et al. 2019

2019 IEEE Conference on Control Technology and Applications (CCTA)

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Many car manufacturers are equipping their vehicles with advanced systems to win the race towards autonomous vehicles. In order to ensure multiple objectives, different embedded systems influencing differently the same physical variable are often implemented in the same vehicle. Most of car manufacturers tend to activate one system at a time, especially when the low-level control of actuators is developed by different equipment suppliers, making the inner dynamics uncertain. However, this limits the potential of the vehicle. This paper discusses the feasibility of coordinating these systems when activated at the same time, while ensuring an acceptable robustness regarding the uncertain dynamics. Results showed good performance in severe maneuvers when combining robust control synthesis and optimization-based control allocation algorithms. Therefore, several embedded systems may be activated at the same time to expand the overall potential of the vehicle and deal with more difficult situations.

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“…General Purpose Graphics Processing Units (GPGPUs) are largely used in applications aiming at efficiently processing large amounts of data (such as in scientific computing and in multimedia applications). Nowadays, these devices are also adopted in complex safety-critical applications, such as the automotive ones [1]. GPGPUs are designed targeting performance and power constraints and thus employ aggressive technology scaling solutions.…”

Section: Introductionmentioning

confidence: 99%

Untestable faults identification in GPGPUs for safety-critical applications

Condia

Silva

Hamdioui

et al. 2019

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS)

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1-Nowadays, General Purpose Graphics Processing Units (GPGPUs) devices are considered as promising solutions for high-performance safety-critical applications, such as those in the automotive field. However, their adoption requires solutions to effectively detect faults arising in the device during the operative life. Hence, effective in-field test solutions are required to guarantee high-reliability levels. In this paper, we leverage the results of Software-Based Self-Test (SBST) based approaches for GPGPUs by deploying new techniques for automating the identification of untestable faults (UF). Our methodology has achieved fault coverage of 82.8% when applied to an open-source implementation of the NVIDIA G80 GPU architecture. The proposed approach combining SBSTs and UFs identification appears as an effective solution for the reliability analysis of GPGPUs.

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Algorithm and hardware implementation for visual perception system in autonomous vehicle: A survey

Cited by 132 publications

References 16 publications

A Survey of Mobile Laser Scanning Applications and Key Techniques over Urban Areas

A Survey of Mobile Laser Scanning Applications and Key Techniques over Urban Areas

Robust Control for Over-Actuated Vehicles

Untestable faults identification in GPGPUs for safety-critical applications

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