Small Object Detection Algorithm Based on Improved YOLOv8 for Remote Sensing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2023, Номер 17, С. 1734 - 1747

Опубликована: Дек. 5, 2023

Due to the limitations of small targets in remote sensing images such as background noise, poor information, and so on, results commonly used detection algorithms target is not satisfactory. To improve accuracy results, we develop an improved algorithm based on YOLOv8, called LAR-YOLOv8. First, feature extraction network, local module enhanced by using dual-branch architecture attention mechanism, while vision transformer block maximize representation map. Second, attention-guided bi-directional pyramid network designed generate more discriminative information efficiently extracting from shallow through a dynamic sparse adding top-down paths guide subsequent modules for fusion. Finally, RIOU loss function proposed avoid failure shape consistency between predicted ground truth box. Experimental NWPU VHR-10, RSOD CARPK datasets verify that LAR-YOLOv8 achieves satisfactory terms mAP (small), mAP, model parameters FPS, can prove our modifications made original YOLOv8 are effective.

Язык: Английский

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A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles

IEEE Internet of Things Journal, Год журнала: 2023, Номер 10(24), С. 21892 - 21916

Опубликована: Авг. 21, 2023

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected automated (CAVs), it paramount vehicle safety, passenger comfort, transportation efficiency, energy saving. This survey attempts to provide a comprehensive thorough overview current state technology, focusing on evolution from estimation trajectory tracking AVs at microscopic level collaborative CAVs macroscopic level. First, this review starts with key estimation, specifically sideslip angle, which pivotal for control, discuss representative approaches. Then, we present symbolic approaches AVs. On top that, further frameworks corresponding applications. Finally, concludes discussion future research directions challenges. aims contextualized in-depth look art CAVs, identifying areas focus pointing out potential exploration.

Язык: Английский

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Connected and Automated Vehicles: Infrastructure, Applications, Security, Critical Challenges, and Future Aspects

Technologies, Год журнала: 2023, Номер 11(5), С. 117 - 117

Опубликована: Сен. 4, 2023

Autonomous vehicles (AV) are game-changing innovations that promise a safer, more convenient, and environmentally friendly mode of transportation than traditional vehicles. Therefore, understanding AV technologies their impact on society is critical as we continue this revolutionary journey. Generally, there needs to be detailed study available assist researcher in its challenges. This research presents comprehensive survey encompassing various aspects AVs, such public adoption, driverless city planning, traffic management, environmental impact, health, social implications, international standards, safety, security. Furthermore, it emerging artificial intelligence (AI), integration cloud computing, solar power usage automated It also forensics approaches, tools used, standards involved, challenges associated with conducting digital the context autonomous Moreover, provides an overview cyber attacks affecting vehicles, attack security devices, threat modeling, authentication schemes, over-the-air updates, zero-trust architectures, data privacy, corresponding defensive strategies mitigate risks. guidelines, best practices for AVs. Finally, outlines future directions AVs must addressed achieve widespread adoption.

Язык: Английский

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Integrated Inertial-LiDAR-Based Map Matching Localization for Varying Environments

IEEE Transactions on Intelligent Vehicles, Год журнала: 2023, Номер 8(10), С. 4307 - 4318

Опубликована: Июль 26, 2023

Localization is critical for automated vehicles as it provides essential position, velocity, and heading angle information to perform object tracking, trajectory prediction, motion planning, control. However, model/environmental uncertainties (including road friction) noises in sensor measurements have a significant effect on the accuracy of localization vehicle state estimation, specially perceptually degraded conditions. In this article, an integrated method based fusion inertial dead reckoning model 3D LiDAR-based map matching proposed experimentally verified urban environment with varying environmental Leveraging global navigation satellite system (GNSS), (INS), LiDAR point clouds, novel light cloud generation method, which only keeps necessary clouds (i.e., buildings roads regardless vegetation seasonal change), proposed. Subsequently, onboard sensors pre-built map, derived normal distribution transformation (NDT) algorithm by error-state-constrained Kalman filter limit error. On top filter, stability analysis estimator presented. Finally, performance validated real experiments under various Thorough winter summer associated results confirm advantages integrating terms reduced computational complexity.

Язык: Английский

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FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion

Mechanical Systems and Signal Processing, Год журнала: 2024, Номер 208, С. 111051 - 111051

Опубликована: Янв. 3, 2024

Язык: Английский

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Foundation Intelligence for Smart Infrastructure Services in Transportation 5.0

IEEE Transactions on Intelligent Vehicles, Год журнала: 2024, Номер 9(1), С. 39 - 47

Опубликована: Янв. 1, 2024

This perspective paper delves into the concept of foundation intelligence that shapes future smart infrastructure services as transportation sector transitions era Transportation 5.0. First, discussion focuses on a suite emerging technologies essential for intelligence. These encompass digital twinning, parallel intelligence, large vision-language models, traffic simulation and systems modeling, vehicle-to-everything (V2X) connectivity, decentralized/distributed systems. Next, introduces present landscape 5.0 applications illuminated by foundational casts vision towards including cooperative driving automation, intersection/infrastructure, management, virtual drivers, mobility planning operations, laying out prospects are poised to redefine ecosystem. Last, through comprehensive outlook, this aspires offer guiding framework intelligent evolution in data generation model calibration, twinning simulation, scenario development experimentation, feedback loop management control, continuous learning adaptation, fostering safety, efficiency, reliability, sustainability infrastructure.

Язык: Английский

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High-Definition Maps: Comprehensive Survey, Challenges, and Future Perspectives

IEEE Open Journal of Intelligent Transportation Systems, Год журнала: 2023, Номер 4, С. 527 - 550

Опубликована: Янв. 1, 2023

In cooperative, connected, and automated mobility (CCAM), the more vehicles can perceive, model, analyze surrounding environment, they become aware capable of understanding, making decisions, as well safely efficiently executing complex driving scenarios. High-definition (HD) maps represent road environment with unprecedented centimetre-level precision lane-level semantic information, them a core component in smart systems, key enabler for CCAM technology. These provide strong prior to understand environment. An HD map is also considered hidden or virtual sensor, since it aggregates knowledge (mapping) from physical sensors, i.e. LiDAR, camera, GPS IMU build model Maps are quickly evolving towards holistic representation digital infrastructure cities include not only geometry but live perception participants, updates on weather conditions, work zones accidents. Deployment autonomous at large scale necessitates building maintaining these by fleet which cooperatively continuously keep up-to-date function properly. This article provides an extensive review various applications highly (AD) systems. We state-of-the-art different approaches algorithms maintain maps. Furthermore, we discuss synthesise data, communication requirements distribution Finally, current challenges future research directions next generation mapping

Язык: Английский

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Small Object Detection and Tracking: A Comprehensive Review

Sensors, Год журнала: 2023, Номер 23(15), С. 6887 - 6887

Опубликована: Авг. 3, 2023

Object detection and tracking are vital in computer vision visual surveillance, allowing for the detection, recognition, subsequent of objects within images or video sequences. These tasks underpin surveillance systems, facilitating automatic annotation, identification significant events, abnormal activities. However, detecting small introduce challenges due to their subtle appearance limited distinguishing features, which results a scarcity crucial information. This deficit complicates process, often leading diminished efficiency accuracy. To shed light on intricacies object tracking, we undertook comprehensive review existing methods this area, categorizing them from various perspectives. We also presented an overview available datasets specifically curated aiming inform benefit future research domain. further delineated most widely used evaluation metrics assessing performance techniques. Finally, examined present field discussed prospective trends. By tackling these issues leveraging upcoming trends, aim push forward boundaries thereby augmenting functionality systems broadening real-world applicability.

Язык: Английский

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Towards the Next Level of Vehicle Automation Through Cooperative Driving: A Roadmap From Planning and Control Perspective

IEEE Transactions on Intelligent Vehicles, Год журнала: 2024, Номер 9(3), С. 4335 - 4347

Опубликована: Фев. 8, 2024

Cooperative Driving Automation (CDA) stands at the forefront of evolving landscape vehicle automation, elevating driving capabilities within intricate real-world environments. This research aims to navigate path toward future CDA by offering a thorough examination from perspective Planning and Control (PnC). It classifies state-of-the-art literature according classes defined Society Automotive Engineers (SAE). The strengths, weaknesses, requirements PnC for each class are analyzed. analysis helps identify areas that need improvement provides insights into potential directions. further discusses evolution directions CDA, providing valuable enhancement enrichment research. suggested include: robustness against disturbance; Risk-aware planning in mixed environment Connected Automated Vehicles (CAVs) Human-driven (HVs); Vehicle-signal coupled modeling coordination enhancement; Vehicle grouping enhance mobility platooning.

Язык: Английский

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Review of Integrated Chassis Control Techniques for Automated Ground Vehicles

Sensors, Год журнала: 2024, Номер 24(2), С. 600 - 600

Опубликована: Янв. 17, 2024

Integrated chassis control systems represent a significant advancement in the dynamics of ground vehicles, aimed at enhancing overall performance, comfort, handling, and stability. As vehicles transition from internal combustion to electric platforms, integrated have evolved meet demands electrification automation. This paper analyses structure automated with systems. Integration longitudinal, lateral, vertical presents complexities due overlapping regions various subsystems. The presented methodology includes comprehensive examination state-of-the-art technologies, focusing on algorithms manage actions prevent interference between results underscore importance allocation exploit additional degrees freedom offered by over-actuated systematically overviews methods applied path tracking. detailed perception decision-making, parameter estimation techniques, reference generation strategies, hierarchy controllers, encompassing high-level, middle-level, low-level components. By offering this systematic overview, aims facilitate deeper understanding diverse employed driving control, providing insights into their applications, strengths, limitations.

Язык: Английский

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