Autonomous Driving Architectures, Perception and Data Fusion: A Review

Velasco-Hernandez, Gustavo; Yeong, De Jong; Barry, John M.; Walsh, Joseph T.

doi:10.1109/iccp51029.2020.9266268

Cited by 44 publications

(27 citation statements)

References 52 publications

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“… Architecture of an autonomous driving (AD) system from, ( a ) a technical perspective that describes the primary hardware and software components and their implementations; ( b ) a functional perspective that describes the four main functional blocks and the flow of information based on [ 15 ]. …”

Section: Figurementioning

confidence: 99%

“…While AV systems may vary slightly from one to another, all are complex systems that consists of many subcomponents. In [ 15 ], the architecture of an AD system is introduced from a technical perspective, which incorporates the hardware and software components of the AD system, and from a functional perspective, which describes the processing blocks required within the AV, from data collection to the control of the vehicle. The hardware and software are the two primary layers from the technical perspective, and each layer includes various subcomponents that represent different aspects of the overall system.…”

Section: Introductionmentioning

confidence: 99%

“…The description of the technical and functional perspective of the architecture of an AV is represented in Figure 2 . The detailed discussion of the AV architectures is beyond the scope of this paper (see [ 15 ] for a more detailed overview).…”

Section: Introductionmentioning

confidence: 99%

“…Several reviews have been published recently on the topic of multi-sensor fusion, some of them describing the architectural structure and sensor technologies in AVs [ 15 , 20 , 21 ], or focusing on the processing stages like sensor calibration, state estimation, object and tracking [ 22 , 23 , 24 ], or detailing techniques used for multi-sensor fusion, like deep learning-based approaches [ 19 , 25 , 26 ]. Table 1 below summarizes some of the recent studies in sensor and sensor fusion technologies in AD systems.…”

Section: Introductionmentioning

confidence: 99%

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Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

Yeong

Velasco-Hernandez

Barry

et al. 2021

Sensors

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484

133

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With the significant advancement of sensor and communication technology and the reliable application of obstacle detection techniques and algorithms, automated driving is becoming a pivotal technology that can revolutionize the future of transportation and mobility. Sensors are fundamental to the perception of vehicle surroundings in an automated driving system, and the use and performance of multiple integrated sensors can directly determine the safety and feasibility of automated driving vehicles. Sensor calibration is the foundation block of any autonomous system and its constituent sensors and must be performed correctly before sensor fusion and obstacle detection processes may be implemented. This paper evaluates the capabilities and the technical performance of sensors which are commonly employed in autonomous vehicles, primarily focusing on a large selection of vision cameras, LiDAR sensors, and radar sensors and the various conditions in which such sensors may operate in practice. We present an overview of the three primary categories of sensor calibration and review existing open-source calibration packages for multi-sensor calibration and their compatibility with numerous commercial sensors. We also summarize the three main approaches to sensor fusion and review current state-of-the-art multi-sensor fusion techniques and algorithms for object detection in autonomous driving applications. The current paper, therefore, provides an end-to-end review of the hardware and software methods required for sensor fusion object detection. We conclude by highlighting some of the challenges in the sensor fusion field and propose possible future research directions for automated driving systems.

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Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

Yeong

Velasco-Hernandez

Barry

et al. 2021

Sensors

Self Cite

484

133

View full text Add to dashboard Cite

show abstract

“…While the various AV systems may vary slightly from one to the other, autonomous driving (AD) systems are profoundly complex systems that consists of many subcomponents. In [12], the architecture of an AD system is introduced from a technical perspective, which incorporates the hardware and software components of the AD system, and from a functional perspective, which describes the processing blocks required within the AV, from data collection to the control of the vehicle. The hardware and software are the two primary layers from the technical perspective, and each layer includes various subcomponents that represent different aspects of the overall system.…”

Section: Introductionmentioning

confidence: 99%

Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

Yeong¹,

Velasco-Hernandez²,

Barry³

et al. 2021

Preprint

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148

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The market for autonomous vehicles (AV) is expected to experience significant growth over the coming decades and to revolutionize the future of transportation and mobility. The AV is a vehicle that is capable of perceiving its environment and perform driving tasks safely and efficiently with little or no human intervention and is anticipated to eventually replace conventional vehicles. Self-driving vehicles employ various sensors to sense and perceive their surroundings and, also rely on advances in 5G communication technology to achieve this objective. Sensors are fundamental to the perception of surroundings and the development of sensor technologies associated with AVs has advanced at a significant pace in recent years. Despite remarkable advancements, sensors can still fail to operate as required, due to for example, hardware defects, noise and environment conditions. Hence, it is not desirable to rely on a single sensor for any autonomous driving task. The practical approaches shown in recent research is to incorporate multiple, complementary sensors to overcome the shortcomings of individual sensors operating independently. This article reviews the technical performance and capabilities of sensors applicable to autonomous vehicles, mainly focusing on vision cameras, LiDAR and Radar sensors. The review also considers the compatibility of sensors with various software systems enabling the multi-sensor fusion approach for obstacle detection. This review article concludes by highlighting some of the challenges and possible future research directions.

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State-of-the-Art Analysis of the Performance of the Sensors Utilized in Autonomous Vehicles in Extreme Conditions

Meydani

2023

Communications in Computer and Information Science

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Autonomous Driving Architectures, Perception and Data Fusion: A Review

Cited by 44 publications

References 52 publications

Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

Sensor and Sensor Fusion Technology in Autonomous Vehicles: A Review

State-of-the-Art Analysis of the Performance of the Sensors Utilized in Autonomous Vehicles in Extreme Conditions

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