Driving assistance system based on data fusion of multisource sensors for autonomous unmanned ground vehicles

Yang, Jiachen; Liu, Shan; Su, Hansong; Tian, Ying

doi:10.1016/j.comnet.2021.108053

Cited by 27 publications

(10 citation statements)

References 42 publications

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“…Other recent works, such as lane detection [23,24,25], real-time pedestrian detection [26,27,28], and driving assistance systems [29,30,31,32,33], have also contributed to the development of high-quality image segmentation systems in AVs.…”

Section: Related Workmentioning

confidence: 99%

Data Handling for Assuring Production Quality of Image Intensive Autonomous Drive Systems: An Industrial Case Study

Pandey,

Mosin,

Durisic

et al. 2023

JSEAS

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Automotive software uses new Machine Learning (ML) algorithms in increased number of systems, including active safety ones. However, with this new paradigm, new challenges arise in the domain of safety-critical automotive software. This article reports on a case study of the development of ML-based vision perception systems at one vehicle Original Equipment Manufacturer (OEM). We investigate how image-intensive perception systems are developed, both from the perspective of ML development processes and automotive software development processes. We conducted interviews with four engineers who were involved in the development process and subsequently performed thematic coding to extract key findings. We focus on how the teams are involved in the process of assuring the production quality of the Society of Automotive Engineers (SAE) level 3 functionality in modern passenger cars. We examine how the ML development process phases (e.g., data collection, model training, and model validation) align with the automotive software development phases (prototype development, software development, validation, deployment). The study found that the development process for ML-based vision perception systems in active safety allows for flexibility to adapt to changes in data collection, and integrates ML model development into the software development process. The investigated approach combines the Agile SAFe model, ML-model development, and the standard automotive V-process model. This study shows an example of combining these development processes using an industrial case study and presents the essential alignment points between different phases of these processes. The study also recommends best practices for developing similar systems in other companies.

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Section: Related Workmentioning

confidence: 99%

Data Handling for Assuring Production Quality of Image Intensive Autonomous Drive Systems: An Industrial Case Study

Pandey,

Mosin,

Durisic

et al. 2023

JSEAS

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“…These countries use UGVS in various military roles, such as reconnaissance, patrolling, and military law enforcement (Cohen, 1995;FARRELL, 2008;RIGGS, 2009;Scobell & Nathan, 2012). The use of UGVS offers a number of benefits, such as reduced risk to military personnel, improved mobility and accessibility, and enhanced intelligence capabilities in support of humanitarian assistance and disaster management (Naglak et al, 2021;Weitz, 2023;Yang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Systematic Literature Review on the Implementation of Unmanned Ground Vehicle System (UGVS) for Defense in Indonesia

La Ode Murgazali Bakasa,

S Martha,

S. Arief

et al. 2024

IJHESS

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This research conducts a systematic literature review to examine the implementation of Unmanned Ground Vehicle System (UGVS) in the context of defense in Indonesia. Given the geographical and operational challenges faced by Indonesian military personnel, UGVS offers an innovative solution to improve the efficiency and effectiveness of military and non-military operations. This study considers the application of UGVS that has been adopted in several developed countries, such as the United States, the United Kingdom, Israel, China and Russia, to explore its potential in enhancing Indonesia's defense capacity. The review covers aspects such as the potential of UGVS in enhancing defense capabilities, technical challenges in the integration of UGVS into existing defense systems, and strategies to overcome these challenges. The research also evaluates the performance of UGVS in combat situations and its impact on defense operations. Using a systematic literature review method, this research presents an in-depth analysis of UGVS applications and highlights the need for integration of this technology in Indonesia's defense system to improve operational effectiveness and efficiency.

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“…Automotive radar systems are responsible for the detection of objects and obstacles, their position, and their speed relative to the vehicle [ 14 ]. However, each sensor of the environmental sensing system can sense environmental information individually, but the single device has high limitations, large errors, and different dimensions of collected information [ 15 ], which makes it difficult to achieve the detection of targets in complex scenarios [ 16 ]. With the continuous development of intelligent networked vehicle technology, the field of intelligent driving has higher requirements for the precision, accuracy, and real-time performance of sensor-perceived information [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Target Detection System for Intelligent Vehicles Based on Multi-Source Data Fusion

Zou

Zheng

Wang

2023

Sensors

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To improve the identification accuracy of target detection for intelligent vehicles, a real-time target detection system based on the multi-source fusion method is proposed. Based on the ROS melodic software development environment and the NVIDIA Xavier hardware development platform, this system integrates sensing devices such as millimeter-wave radar and camera, and it can realize functions such as real-time target detection and tracking. At first, the image data can be processed by the You Only Look Once v5 network, which can increase the speed and accuracy of identification; secondly, the millimeter-wave radar data are processed to provide a more accurate distance and velocity of the targets. Meanwhile, in order to improve the accuracy of the system, the sensor fusion method is used. The radar point cloud is projected onto the image, then through space-time synchronization, region of interest (ROI) identification, and data association, the target-tracking information is presented. At last, field tests of the system are conducted, the results of which indicate that the system has a more accurate recognition effect and scene adaptation ability in complex scenes.

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Driving assistance system based on data fusion of multisource sensors for autonomous unmanned ground vehicles

Cited by 27 publications

References 42 publications

Data Handling for Assuring Production Quality of Image Intensive Autonomous Drive Systems: An Industrial Case Study

Data Handling for Assuring Production Quality of Image Intensive Autonomous Drive Systems: An Industrial Case Study

Systematic Literature Review on the Implementation of Unmanned Ground Vehicle System (UGVS) for Defense in Indonesia

Real-Time Target Detection System for Intelligent Vehicles Based on Multi-Source Data Fusion

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