scholarly journals Investigating the Impact of Energy Source Level on the Self-Guided Vehicle System Performances, in the Industry 4.0 Context

2020 ◽  
Vol 12 (20) ◽  
pp. 8541
Author(s):  
Massinissa Graba ◽  
Sousso Kelouwani ◽  
Lotfi Zeghmi ◽  
Ali Amamou ◽  
Kodjo Agbossou ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Industry 4.0 ◽  
True Path ◽  
Long Term Effect ◽  
Industrial Operations ◽  
Single Vehicle ◽  
Energy Consideration ◽  
Source Level ◽  
Unmanned Autonomous Vehicles ◽  
The Impact

Automated industrial vehicles are taking an imposing place by transforming the industrial operations, and contributing to an efficient in-house transportation of goods. They are expected to bring a variety of benefits towards the Industry 4.0 transition. However, Self-Guided Vehicles (SGVs) are battery-powered, unmanned autonomous vehicles. While the operating durability depends on self-path design, planning energy-efficient paths become crucial. Thus, this paper has no concrete contribution but highlights the lack of energy consideration of SGV-system design in literature by presenting a review of energy-constrained global path planning. Then, an experimental investigation explores the long-term effect of battery level on navigation performance of a single vehicle. This experiment was conducted for several hours, a deviation between the global trajectory and the ground-true path executed by the SGV was observed as the battery depleted. The results show that the mean square error (MSE) increases significantly as the battery’s state-of-charge decreases below a certain value.

Environmental Management of Coastal Development, State of Kuwait

1999 ◽  
Vol 40 (7) ◽  
pp. 47-53 ◽  
Author(s):  
Y. R. Marmoush
Keyword(s):  
Environmental Impact ◽  
Practical Experience ◽  
Term Effect ◽  
Marine Ecology ◽  
Coastal Development ◽  
Long Term Effect ◽  
Environmental Measures ◽  
Environmental Feasibility ◽  
Development State ◽  
The Impact

The impact of coastal development in Kuwait is to be assessed as per the following environmental conditions: water circulation, sediment behavior, water quality, and marine ecology and fisheries. The objectives of this assessment are to identify and predict the environmental impact associated with coastal development and the various activities involved in any coastal project. These activities and their associated impact can be grouped into two categories: those that occur during construction (short-term effect), and those that occur after construction (long-term effect). This paper attempts to present the fundamental issues related to the environmental measures and the practical experience required to evaluate the potential environmental impact of coastal development in Kuwait. The conclusions and general considerations regarding the environmental feasibility of coastal development are given, and measures to minimize the adverse impact on the environment are recommended.

scholarly journals Connectivity as a Design Feature for Industry 4.0 Production Equipment: Application for the Development of an In-Line Metrology System

2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Design Feature ◽  
Production Equipment ◽  
Smart Manufacturing ◽  
Process Data ◽  
Industrial Sectors ◽  
Advanced Manufacturing Technologies ◽  
Manufacturing Technologies ◽  
Equipment Application ◽  
The Impact

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.

scholarly journals The Impact of Force Factors on the Benefits of Digital Transformation in Romania

2021 ◽  
Vol 11 (5) ◽  
pp. 2365
Author(s):  
Sorinel Căpușneanu ◽  
Dorel Mateș ◽  
Mirela Cătălina Tűrkeș ◽  
Cristian-Marian Barbu ◽  
Adela-Ioana Staraș ◽  
...  
Keyword(s):  
Perceived Risk ◽  
Industry 4.0 ◽  
Business Models ◽  
Structural Model ◽  
Digital Transformation ◽  
Sample Survey ◽  
Intention To Use ◽  
Online Questionnaire ◽  
Use Of Technology ◽  
The Impact

The digital transformation has produced changes in all existing areas of activity worldwide. There are many factors that can influence the intention to use Industry 4.0 processes and solutions and change the behavior of organizations and their business models. The aim of this study is to validate the econometric model on assessing the significant impact of distinct factors on the intention to use Industry 4.0 processes and solutions, the benefits of digital transformation perceived by organizational management and the differences between distinct groups analyzed. The research method used within the quantitative study was the sample survey, using the online questionnaire as a data collection tool. Three hundred forty-seven valid questionnaires were collected and the response rate of the respondents was 64.25%. A new structural model was generated based on the elements of the Unified Theory of Acceptance and Use of Technology (UTAUT). The results of the study indicated that Perceived competitiveness and Perceived risk have a significant impact on Intention to Use Industry 4.0 processes while Perceived vertical networking solutions and Perceived integrated engineering solutions have a significant influence on the Intention to Use Industry 4.0 solutions. In conclusion, there is a positive and significant association between Intention to Use Industry 4.0 solutions and Benefits of Digital Transformation.

The Impact of Mental States on Semi-autonomous Driving Takeover Performance: A Systematic Review

2020 ◽  
Vol 64 (1) ◽  
pp. 1372-1376
Author(s):  
Gaojian Huang ◽  
Christine Petersen ◽  
Brandon J. Pitts
Keyword(s):  
Systematic Review ◽  
Autonomous Vehicles ◽  
Response Times ◽  
Autonomous Driving ◽  
Mental States ◽  
Manual Control ◽  
Monitoring Systems ◽  
Wide Range ◽  
Different Types ◽  
The Impact

Semi-autonomous vehicles still require drivers to occasionally resume manual control. However, drivers of these vehicles may have different mental states. For example, drivers may be engaged in non-driving related tasks or may exhibit mind wandering behavior. Also, monitoring monotonous driving environments can result in passive fatigue. Given the potential for different types of mental states to negatively affect takeover performance, it will be critical to highlight how mental states affect semi-autonomous takeover. A systematic review was conducted to synthesize the literature on mental states (such as distraction, fatigue, emotion) and takeover performance. This review focuses specifically on five fatigue studies. Overall, studies were too few to observe consistent findings, but some suggest that response times to takeover alerts and post-takeover performance may be affected by fatigue. Ultimately, this review may help researchers improve and develop real-time mental states monitoring systems for a wide range of application domains.

scholarly journals An Efficiency Enhancing Methodology for Multiple Autonomous Vehicles in an Urban Network Adopting Deep Reinforcement Learning

2021 ◽  
Vol 11 (4) ◽  
pp. 1514 ◽  
Author(s):  
Quang-Duy Tran ◽  
Sang-Hoon Bae
Keyword(s):  
Reinforcement Learning ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Effective Means ◽  
Urban Network ◽  
Learning Agents ◽  
Policy Optimization ◽  
The Impact

To reduce the impact of congestion, it is necessary to improve our overall understanding of the influence of the autonomous vehicle. Recently, deep reinforcement learning has become an effective means of solving complex control tasks. Accordingly, we show an advanced deep reinforcement learning that investigates how the leading autonomous vehicles affect the urban network under a mixed-traffic environment. We also suggest a set of hyperparameters for achieving better performance. Firstly, we feed a set of hyperparameters into our deep reinforcement learning agents. Secondly, we investigate the leading autonomous vehicle experiment in the urban network with different autonomous vehicle penetration rates. Thirdly, the advantage of leading autonomous vehicles is evaluated using entire manual vehicle and leading manual vehicle experiments. Finally, the proximal policy optimization with a clipped objective is compared to the proximal policy optimization with an adaptive Kullback–Leibler penalty to verify the superiority of the proposed hyperparameter. We demonstrate that full automation traffic increased the average speed 1.27 times greater compared with the entire manual vehicle experiment. Our proposed method becomes significantly more effective at a higher autonomous vehicle penetration rate. Furthermore, the leading autonomous vehicles could help to mitigate traffic congestion.

scholarly journals Collision Avoidance on Unmanned Aerial Vehicles Using Neural Network Pipelines and Flow Clustering Techniques

2021 ◽  
Vol 13 (13) ◽  
pp. 2643
Author(s):  
Dário Pedro ◽  
João P. Matos-Carvalho ◽  
José M. Fonseca ◽  
André Mora
Keyword(s):  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
High Demand ◽  
Novel Approach ◽  
Vision Sensors ◽  
Learning Techniques ◽  
Stationary Objects ◽  
Computationally Intensive ◽  
Unmanned Autonomous Vehicles ◽  
Positive Results

Unmanned Autonomous Vehicles (UAV), while not a recent invention, have recently acquired a prominent position in many industries, and they are increasingly used not only by avid customers, but also in high-demand technical use-cases, and will have a significant societal effect in the coming years. However, the use of UAVs is fraught with significant safety threats, such as collisions with dynamic obstacles (other UAVs, birds, or randomly thrown objects). This research focuses on a safety problem that is often overlooked due to a lack of technology and solutions to address it: collisions with non-stationary objects. A novel approach is described that employs deep learning techniques to solve the computationally intensive problem of real-time collision avoidance with dynamic objects using off-the-shelf commercial vision sensors. The suggested approach’s viability was corroborated by multiple experiments, firstly in simulation, and afterward in a concrete real-world case, that consists of dodging a thrown ball. A novel video dataset was created and made available for this purpose, and transfer learning was also tested, with positive results.

scholarly journals Impacts of Autonomous Vehicles on Greenhouse Gas Emissions—Positive or Negative?

2021 ◽  
Vol 18 (11) ◽  
pp. 5567
Author(s):  
Moneim Massar ◽  
Imran Reza ◽  
Syed Masiur Rahman ◽  
Sheikh Muhammad Habib Abdullah ◽  
Arshad Jamal ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Autonomous Vehicles ◽  
Significant Contribution ◽  
Ghg Emissions ◽  
Interval Estimate ◽  
Modal Shift ◽  
Vehicle Mile Travel ◽  
Emission Changes ◽  
Negative Impacts ◽  
The Impact

The potential effects of autonomous vehicles (AVs) on greenhouse gas (GHG) emissions are uncertain, although numerous studies have been conducted to evaluate the impact. This paper aims to synthesize and review all the literature regarding the topic in a systematic manner to eliminate the bias and provide an overall insight, while incorporating some statistical analysis to provide an interval estimate of these studies. This paper addressed the effect of the positive and negative impacts reported in the literature in two categories of AVs: partial automation and full automation. The positive impacts represented in AVs’ possibility to reduce GHG emission can be attributed to some factors, including eco-driving, eco traffic signal, platooning, and less hunting for parking. The increase in vehicle mile travel (VMT) due to (i) modal shift to AVs by captive passengers, including elderly and disabled people and (ii) easier travel compared to other modes will contribute to raising the GHG emissions. The result shows that eco-driving and platooning have the most significant contribution to reducing GHG emissions by 35%. On the other side, easier travel and faster travel significantly contribute to the increase of GHG emissions by 41.24%. Study findings reveal that the positive emission changes may not be realized at a lower AV penetration rate, where the maximum emission reduction might take place within 60–80% of AV penetration into the network.

scholarly journals Feedforward ins aiding: an investigation of maneuvers for in-flight alignment

2007 ◽  
Vol 18 (4) ◽  
pp. 459-470 ◽  
Author(s):  
Jacques Waldmann
Keyword(s):  
Autonomous Vehicles ◽  
Inertial Sensors ◽  
Low Cost ◽  
Measurement Unit ◽  
Model Mismatch ◽  
External Data ◽  
Rate Gyro ◽  
External Position ◽  
The Impact ◽  
Gyro Drift

Navigation in autonomous vehicles involves integrating measurements from on-board inertial sensors and external data collected by various sensors. In this paper, the computer-frame velocity error model is augmented with a random constant model of accelerometer bias and rate-gyro drift for use in a Kalman filter-based fusion of a low-cost rotating inertial navigation system (INS) with external position and velocity measurements. The impact of model mismatch and maneuvers on the estimation of misalignment and inertial measurement unit (IMU) error is investigated. Previously, the literature focused on analyzing the stripped observability matrix that results from applying piece-wise constant acceleration segments to a stabilized, gimbaled INS to determine the accuracy of misalignment, accelerometer bias, and rate-gyro drift estimation. However, its validation via covariance analysis neglected model mismatch. Here, a vertically undamped, three channel INS with a rotating IMU with respect to the host vehicle is simulated. Such IMU rotation does not require the accurate mechanism of a gimbaled INS (GINS) and obviates the need to maneuver away from the desired trajectory during in-flight alignment (IFA) with a strapdown IMU. In comparison with a stationary GINS at a known location, IMU rotation enhances estimation of accelerometer bias, and partially improves estimation of rate-gyro drift and misalignment. Finally, combining IMU rotation with distinct acceleration segments yields full observability, thus significantly enhancing estimation of rate-gyro drift and misalignment.

The Impact of the Reformation

2019 ◽  
pp. 40-61
Author(s):  
Martin Pugh
Keyword(s):  
Sixteenth Century ◽  
Protestant Reformation ◽  
Elizabeth I ◽  
Long Term Effect ◽  
Queen Elizabeth I ◽  
The Reformation ◽  
The Impact ◽  
European Diplomacy ◽  
Francis I

This chapter focuses on the Protestant Reformation of the sixteenth century. Following Henry VIII's break with Rome in 1531, the English Reformation led Britain into a protracted struggle with the two great Catholic powers, Spain and France, for the next 300 years. The long-term effect was to define Britain as the leading Protestant power; but more immediately, it posed a far greater threat to England than Islam, and effectively destroyed the rationale for crusading activities. In this situation, the Islamic empires actually became a valuable balancing factor in European diplomacy. Henry's readiness to deal with the Muslim powers was far from eccentric during the sixteenth century. Both King Francis I of France and Queen Elizabeth I of England took the policy of collaboration much further.

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