Different Levels Of Automation Research Articles

Heterogeneous traffic flow of expressway with Level 2 autonomous vehicles considering moving bottlenecks

With the development of autonomous driving technology, autonomous vehicles (AV) will gradually replace human-driven vehicles (HDV), but it will still be a mixed traffic flow of autonomous vehicles with different levels of automation for a long time. In addition to cars, trucks regarded as moving bottleneck are also an important part of traffic flow of expressway. In this paper, the elimination rule of moving bottleneck is introduced into the traffic flow model, and the improved hybrid traffic flow cellular automata model is proposed. Next, through numerical simulation, the existence and influence of moving bottleneck caused by heavy duty trucks are hypothesized and verified. The simulation results show that with the proportion of trucks increases, the influence range of moving bottleneck expands, resulting in the decrease of capacity and traffic congestion. Then, the impact of Level 2 autonomous vehicles (hereinafter referred to as L2 AVs) on the traffic flow of moving bottlenecks is explored. The simulation results show that with the proportion of L2 AVs increases, traffic capacity increases, and traffic congestion ratio at medium and high density decreases. Under medium density, the average velocity fluctuates greatly, while under high density, the average velocity decreases due to limitation of density. In summary, L2 AVs can alleviate influence of moving bottlenecks, increase traffic capacity, improve traffic congestion, and lift road safety. The cellular automata model of traffic flow including moving bottleneck proposed in this paper is based on the actual road situation, considering the fact that most of autonomous vehicles on the expressway currently are L2 AVs, and moving bottleneck is mainly caused by heavy trucks. This research contributes to an in-depth analysis of L2 AVs on heterogeneous traffic flows under moving bottleneck environment.

The effect of human-machine interface modality, specificity, and timing on driver performance and behavior while using vehicle automation

The effectiveness of the human–machine interface (HMI) in a driving automation system during takeover situations is based, in part, on its design. Past research has indicated that modality, specificity, and timing of the HMI have an impact on driver behavior. The objective of this study was to examine the effectiveness of two HMIs, which vary by modality, specificity, and timing, on drivers’ takeover time, performance, and eye glance behavior. Drivers’ behavior was examined in a driving simulator study with different levels of automation, varying traffic conditions, and while completing a non-driving related task. Results indicated that HMI type had a statistically significant effect on velocity and off-road eye glances such that those who were exposed to an HMI that gave multimodal warnings with greater specificity exhibited better performance. There were no effects of HMI on acceleration, lane position, or other eye glance metrics (e.g., on road glance duration). Future work should disentangle HMI design further to determine exactly which aspects of design yield between safety critical behavior.

The fine line between automation and augmentation in website usability evaluation

Artificial Intelligence (AI) systems are becoming widespread in all aspects of society, bringing benefits to the whole economy. There is a growing understanding of the potential benefits and risks of this type of technology. While the benefits are more efficient decision processes and industrial productivity, the risks may include a potential progressive disengagement of human beings in crucial aspects of decision-making. In this respect, a new perspective is emerging that aims at reconsidering the centrality of human beings while reaping the benefits of AI systems to augment rather than replace professional skills: Human-Centred AI (HCAI) is a novel framework that posits that high levels of human control do not contradict high levels of computer automation. In this paper, we investigate the two antipodes, automation vs augmentation, in the context of website usability evaluation. Specifically, we have analyzed whether the level of automation provided by a tool for semi-automatic usability evaluation can support evaluators in identifying usability problems. Three different visualizations, each one corresponding to a different level of automation, ranging from a full-automation approach to an augmentation approach, were compared in an experimental study. We found that a fully automated approach could help evaluators detect a significant number of medium and high-severity usability problems, which are the most critical in a software system; however, it also emerged that it was possible to detect more low-severity usability problems using one of the augmented approaches proposed in this paper.

Pairing in-vehicle intelligent agents with different levels of automation: implications from driver attitudes, cognition, and behaviors in automated vehicles

ABSTRACT In-vehicle intelligent agents (IVIAs) have been developed to improve user experience in autonomous vehicles. Yet, the impact of the automation system on driver behavior and perception toward IVIAs is unclear. In this study, we conducted three experiments with 73 participants in a driving simulator to examine how automation system parameters (the level of automation system and IVIA features) influence driver attitudes, cognition, and behaviors when driving or riding in a simulated vehicle. We focused on subjective evaluations of driver-agent interaction and driver trust toward IVIAs to assess driver attitudes, driver situation awareness, and visual distraction to capture their cognition, and their driving performance to understand their behaviors. Our results show that the level of automation system affects drivers’ attitudes toward agent capabilities (e.g. perceived intelligence). Embodiment benefits are more pronounced with Level 5 systems, while speech style, in general, is more influential in determining affective aspects of user attitudes (e.g. Warmth, Likability). As the level of automation increases, drivers engage in more visual distractions. In addition, conversational speech style in general encouraged safer driving behaviors indicated by more stable lateral control under lower levels of automation. Our findings uncover the path of how system parameters affect driver behaviors through system evaluation and trust in agents. These findings have important implications for the development of cohesive user experiences in future transportation systems.

European Common Data Management Platform Definition for Railway AI Function Development

Digitalisation and automation of operations in the railway industry include the use of Automatic Train Operation systems that provide automated functions to reach different levels of automation, known as the Grade of Automation (GoA) levels. These levels go up to GoA4 in which the train is automatically controlled without any staff on board. Artificial intelligence has emerged as technology that can substitute humans in certain driving tasks, in GoA3 (driverless) and GoA4 (unattended) modes. AI capabilities include perception, decision-making, precise positioning, or optimization of communications. The success of AI models depends on the quality and diversity of the data used for training, along with the set-up of a data life-cycle framework that covers creation, training, testing, deployment and monitorisation. The management of training datasets implies both expensive and time-consuming data gathering, labelling, curation and formatting efforts, potentially hindering the development of reliable AI systems. This paper presents a Common Data Management Platform developed by a consortium of European railway stakeholders, devised to efficiently manage data for AI training, and which is demonstrated in two different Proofs of Concept.

Rig Automation Empowers Well Construction in Ecuador

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 216249, “Digital Innovation of Well-Construction Process in Ecuador Through Rig Automation,” by Karen Peña, Kevin Etcheverry, and Hugo Quevedo, SPE, SLB, et al. The paper has not been peer reviewed. _ Artificial intelligence (AI)-based digital drilling technology was implemented in two mature fields in Ecuador that represent 33% of the country’s oil production. The drilling campaign’s main strategy included the deployment of a novel automation solution on two rigs, resulting in the optimization of the well-construction process. In the complete paper, the authors present the results of implementation of a rig-automation solution applied to 20 wells in 2022. Scope of the Digital Solution The authors detail the validation, optimization, and implementation of a drilling software to automate work flows and the installation and commissioning of associated hardware components. The following key indicators and objectives were established: - Validation of drilling-software work flows - Achievement of a 75% average in automation control - Improvement of rate of penetration (ROP) by 5% - Reduction of pre- and post-connection times by at least 30% - Real-time tuning of parameters - Training of all personnel involved in the use of the drilling-software package - Installation and commission of hardware components Drilling-Software Implementation The digital solution is an advanced software system that brings automation capabilities to drilling rigs, analogous to the different levels of automation found in automobiles. By drawing a parallel to car automation, one can better understand the system’s functionality and benefits. Level 1 consists of task automation, comparable to automatic driving features such as cruise control. In this context, the drilling software takes on the role of automating specific tasks within the drilling process. Level 2 involves process automation, similar to a car’s ability to autonomously park itself. The digital solution automates selected processes in drilling operations that enable efficient and precise execution. Level 3 encompasses adaptive automation, akin to a self-driving car that dynamically adapts to its surroundings. The drilling software continuously analyzes the real-time conditions of the wellbore and suggests optimal drilling parameters based on proprietary algorithms that leverage the well-known DeTournay model principle. The drilling software actively controls four key rig machines: the drawworks, topdrive, automated driller, and mud pumps. The solution adjusts drilling parameters intelligently, optimizing the drilling process and improving overall efficiency and drilling stability.

Automation of interaction—interaction design at the crossroads of user experience (UX) and artificial intelligence (AI)

AbstractInteraction design/HCI seems to be at a crossroads. On the one hand, it is still about designing for engaging user experiences (UX). Still, on the other hand, it seems to be increasingly about reducing interaction and automating human–machine interaction through the use of AI and other new technologies. In this paper, we explore this seemingly unavoidable gap. First, we discuss the fundamental design rationality underpinning interaction and automation of interaction from the viewpoints of classic theoretical standpoints. We then illustrate how these two come together in interaction design practice. Here we examine four examples from already published research on automation of interaction, including how different levels of automation of interaction affect or enable new practices, including coffee making, self-tracking, automated driving, and conversations with AI-based chatbots. Through an interaction analysis of these four examples, we show (1) how interaction and automation are combined in the design, (2) how interaction is dependent on a certain level of automation, and vice versa, and (3) how each example illustrates a different balance between, and integration of interaction and automation. Based on this analysis, we propose a two-dimensional design space as a conceptual construct that takes these aspects into account to understand and analyze ways of combining interaction and automation in interaction design. We illustrate the use of the proposed two-dimensional design space, discuss its theoretical implications, and suggest it as a useful tool—when designing for engaging user experiences (UX), with interaction and automation as two design materials.

Towards a novel intelligent and fully interactive IoT framework for residential buildings

Intelligent operation of buildings plays a crucial role in enhancing energy efficiency, especially in commercial buildings. However, residential buildings suffer from lack of management in energy consumption, contributing to global carbon emissions. Challenges include limited autonomous features, lack of scalability, and costly existing solutions. This paper presents a preliminary study toward the realization of a universal, scalable, and low-cost residential control framework to improve energy performance and reduce the cost of existing building retrofitting approaches. The residential system in its envisioned form may include thermostat, dimming, shading, and window-opening controls. For this study, a preliminary simulation-based investigation of a typical house in multiple climates is performed. To this end, the occupancy profiles data to layout different levels of automation of thermostats and shades have been employed, proposing 3 levels based on a variety of thermostat setpoints and shading. Data from the American Time Use Survey is utilized to inform occupancy and form the integrated automatic control strategy. This approach paves the way for building management systems in homes that integrate IoT-enabled devices for seamless operation, supporting decarbonization and creating interactive and smart buildings. The results showed that from 15% up to 70% reduction in heating and cooling loads are obtainable. This underscores the great potential of implementation of smart control systems in residential buildings.

Analysis of Australian public acceptance of fully automated vehicles by extending technology acceptance model

There has been an increasing trend in using user acceptance models to explore the public acceptance of automated vehicles (AVs) in different countries. Most of the previous studies have analysed perceived usefulness, behavioural attitude, subjective norms as well as perceived ease of use, but other important factors, such as trust and data privacy, have not been adequately considered. Likewise, public perceptions of fully AVs are limited in the literature as most studies focus on different levels of automation. This study aims to assess the behavioural intention to use fully AVs in Australia by extending the Technology Acceptance Model (TAM) that includes data privacy and trust in the TAM constructs. Based on a survey of 809 adult respondents from Australia, the model was evaluated with Structural Equation Modelling.The research revealed perceived trust and perceived data privacy is the first and second most important variable affecting the attitude, followed by perceived ease of use and usefulness. Perceived data privacy was discovered to positively impact attitude, perceived trust, perceived usefulness, perceived ease of use as well as behavioural intentions. The perceived trust mediated perceived data privacy on the attitudes in this study. Additionally, the two major variables in the proposed model – perceived trust and data privacy- affect attitudes of AVs significantly, with total effects being 0.637 and 0.604, respectively. Attitude is the most significant variable that correlates with behavioural intentions, which leads to acceptance of fully AVs. Multigroup analysis showed the gender, age and income related differences regarding the public acceptance of AVs. Several theoretical and practical implications are discussed in this paper.

HUs Fleet Management in an Automated Container Port: Assessment by a Simulation Approach

Freight fleet management (FM) can be defined as an optimization process of freight vehicles scheduling and routing, aimed at reducing time, costs, energy, and environmental impacts. In the specialized literature, there are many FM studies. The focus of this paper is on the FM in the context of a container port to increase the productivity and pursue the sustainability of the logistics node improving the performance by using freight advanced handling units (HUs). The use of automated HUs reduces the time and costs of each port activity, eliminating timewasters and increasing safety; however, it requires advanced intelligent management. Moreover, the automation is in line with energy and environmental sustainability. The paper aims to assess the impacts due to the automation of HUs by using a simulation approach. After a framework of traditional and automated HUs, allowing to highlight their main characteristics, the work considers the organizational problems of a container port and introduces a methodological approach to manage the FM of HUs. Finally, the application to a real context is presented to compare the present configuration of a container port with some project scenarios, considering different levels of automation, as the partial and total replacements of traditional HUs with advanced/automated vehicles.

Configuration and Design Schemes of Environmental Sensing and Vehicle Computing Systems for Automated Driving: A Review

The recent proliferation of sensing and computing technologies has promoted the rapid development of automated driving. A series of automated driving systems are consecutively released by manufactures in recent years. These systems at different automated driving levels rely on various perception sensors and vehicle computing system to detect the environment and process the real-time data. The configuration of environmental sensing and vehicle computing in the system design stage for facilitating automated driving are attracting more and more attention. In this paper, we investigate the state-of-the-art configuration design schemes of perception system and computing system in automated driving at different levels of automation, involving up to thirty automated driving systems or vehicles. Comprehensive analysis by statistics approaches is followed with the emphasis of underlying design patterns and the cross relationships among environmental sensing, vehicle computing and automated driving levels. Furthermore, from a general perspective, we analyze and conclude the requirement on the perception system and the computing system in automated vehicles, considering typical features in each automated driving level. We expect that this work could serve as a reference for practical engineering on the configuration design for automated driving systems, and promote academic research on relative theories and methodologies for system design.

Research on Heterogeneous Traveler Travel Mode Choices with Differences under a Mixed Traffic Environment.

Autonomous vehicles (AVs) have been made possible by advances in sensing and computing technologies. However, the high cost of AVs makes privatization take longer. Therefore, companies with autonomous vehicles can develop shared autonomous vehicle (SAV) projects. AVs with a high level of automation require high upgrade and use costs. In order to meet the needs of more customers and reduce the investment cost of the company, SAVs with different levels of automation may coexist for a long time. Faced with multiple travel modes (autonomous cars with different levels of automation, private cars, and buses), travelers' travel mode choices are worth studying. To further differentiate the types of travelers, this paper defines high-income travelers and low-income travelers. The difference between these two types of travelers is whether they have a private car. The differences in time value and willingness to pay of the two types of travelers are considered. Based on the above considerations, this paper establishes a multi-modal selection model with the goal of maximizing the total utility of all travelers and uses the imperial competition algorithm to solve it. The results show that low-income travelers are more likely to choose buses and autonomous vehicles with lower levels of automation, while high-income travelers tend to choose higher levels of automation due to their high value of travel time.

ИСПОЛЬЗОВАНИЕ ПОЛУПРОВОДНИКОВЫХ ЭЛЕМЕНТОВ ПЕЛЬТЬЕ В ГАЗОИСПОЛЬЗУЮЩЕМ ВАРОЧНОМ КОТЛЕ

Cooking boilers powered by natural gas are promising equipment for the preparation of feed in private farms. Based on the patent search, it has been established that there is a wide choice of gas-using boilers with different levels of automation of the process of thermal processing of the product and ensuring safety during operation. At the preliminary stage of the study, it was found that with a smooth control of the power of the gas burner of the digester during the preparation of feed, gas savings of up to 19% are achieved. The principle of self-regulation of gas consumption by a gas burner is determined in proportion to the heat flow consumed by the digester. A working experimental sample was made on the basis of an automation kit for a digester with smooth control of the power of a gas burner. A mathematical model has been developed that describes the processes of heat and mass transfer in a feed boiler with self-regulation of power. Based on the analysis of energy supply systems in digesters and heating boilers, the expediency of developing a new promising power self-regulation scheme based on Peltier semiconductor thermoelements has been established. As shown by the results of experimental studies of automation in various operating modes, the voltage on thermoelectric elements changes in proportion to the temperature difference. It is established that the minimum voltage is 0.07V, the maximum is 0.7V. The voltage and temperature of the product and hot steam in the jacket were measured using TEK DT 830B multimeters. It has been established that the best sensitivity of the thermal regime control system is achieved if the thermoelectric converter module is equipped with nine elements that change the output voltage in proportion to the temperature difference in the steam jacket of the digester.

Guest Editorial Introduction to the Special Issue on Deployment of Connected and Automated Vehicles in Mixed Traffic Environment and the Implications on Traffic Safety and Efficiency

The gradual deployment of Connected and Automated Vehicles (CAV) in traffic will result in a transition period in which vehicles with various levels of automation and connectivity will have to co-exist with non-connected and non-automated road users for quite some time. Consequently, new types of interactions will emerge (and old types of interactions are likely to become more complicated) between vehicles at different levels of automation and other road users which could have significant implications on traffic safety and efficiency. Understanding the nature of these interactions, how humans might adapt their behavior, how connectivity can be utilized to proactively enhance drivers char63 driving performance, and how automated vehicles can be programmed to behave in different driving situations to guarantee safety and efficiency remain among the key knowledge gaps that require scientific research. This knowledge is crucial for the development of adequate integration policies of connected and automated vehicles in mixed traffic environment, for updating and improving automated vehicles char63 algorithms and software, for designing the physical and digital road infrastructure, and for operating and managing traffic on the road network.

Studying Traffic Safety During the Transition Period Between Manual Driving and Autonomous Driving: A Simulation-Based Approach

Connected and Autonomous Vehicles (CAVs) are becoming a reality and are progressively penetrating the markets level by level. CAVs are a promising solution for traffic safety. However, robust studies are needed to explore and assess the expected behavior. This study attempts to evaluate traffic safety resulting from a near-real introduction of CAVs with different levels of automation (from Level 1 to Level 4). The investigation consisted of modeling different CAV levels using Gipps’ model, followed by the simulation of nine mixed fleets at a motorway segment. Subsequently, the Surrogate Safety Assessment Model was used for safety analysis. According to the results: (1) the gradual penetration of CAV levels led to a progressive reduction in traffic conflicts, ranging from 18.9% when the penetration of high levels of automation (Level 3 and Level 4 vehicles) is 5%, to 94.1% when all the vehicles on the traffic flow are Level 4; (2) human-driven vehicles and vehicles with low levels of automation (Level 1 and Level 2 vehicles) are more frequently involved in conflicts (as follower vehicles) than vehicles with high automation levels. E.g. human-driven vehicles are involved in conflicts from 8% to 122% more, while vehicles with high automation levels are involved in conflicts from 80% to 18% less than their sharing percentages, respectively, depending on different mixed fleets. This study confirms the theory and conclusions from previous literature that indicate a safety gain due to CAV penetration. Moreover, it provides a broader perspective and support for the introduction of CAVs levels.

A Novel Framework for Operation of Capacitor Banks in Non/Semi/Fully-Automated Distribution Networks

Nowadays, distribution systems have different levels of automation due to the need for massive investment. The optimal operation of capacitor banks (CBs) is a widely-used approach to improve the performance of these systems. Therefore, the optimal operation of CBs in distribution systems with any level of automation is essential. This paper introduces a novel framework for the operation of CBs in the non/semi/fully-automated distribution networks based on two timescales of day-ahead and near-to-real-time applications. In this framework, the linear current injection power flow method to properly study CB effects on the system is developed, including i) modeling vector group transformer, ii) modeling induction motors, iii) plotting the PV curve of motor loads as indices to assess the efficiency of CB on the voltage system, and iv) developing a fast power flow method with a low computational burden. Besides, the optimization problem of CBs control as the core of the proposed framework is reformulated, considering the level of network automation. The accuracy of the developed framework is evaluated on the IEEE 37-bus and 123-bus test systems. The obtained results verify the efficiency and superiority of the proposed framework.

In Search of Severity Dimensions of Traffic Conflicts for Different Simulated Mixed Fleets Involving Connected and Autonomous Vehicles

This study aims to estimate the severity of conflicts that may arise from the introduction of connected and automated vehicles (CAVs) by examining the vehicle paths generated by microsimulations of mixed fleets of human-driven vehicles and CAVs with different levels of automation (L1-L4 vehicles). The study assesses the severity of conflicts using a holistic approach that considers three dimensions: (1) proximity to collision, via the time-to-collision (TTC) indicator; (2) potential consequences of a conflict, via single surrogate safety measures such as maximum speed (MaxS) and vehicle speed difference (DeltaS); and (3) a combination of both dimensions to assign severity scores, via TTC and velocity vectors. The study’s findings suggest that moderate penetration rates of L3 and L4 vehicles (35–55%) show significant differences in the number of traffic conflicts with varying TTC values. Additionally, high penetration rates of L3 and L4 vehicles (above 55%) result in lower values of conflict consequences measures such as MaxS and DeltaS. Furthermore, the study shows that conflict consequences decrease if the follower is a L3 or L4 vehicle. The study’s findings also reveal that there is a considerable reduction in high severity conflicts when the penetration rate of CAV levels reaches 50%, and the full operation of L4 vehicles results in a 75.5% reduction in high severity conflicts. Therefore, this study provides valuable insight into the potential severe conflicts during the transition period from manual vehicle operation to full CAV operation. Overall, the study’s findings highlight the importance of assessing the severity of potential conflicts arising from the introduction of CAVs. By considering the proximity to collision and the potential consequences of conflicts, the study provides a comprehensive assessment of the severity of conflicts. This information can inform the development of policies and strategies to ensure the safe and responsible introduction of CAVs into our transportation systems.

Waste tire remanufacturing: Quantitative‐aided qualitative sustainability analysis

AbstractWaste tires contain a large amount of embodied energy and useful materials that can be recovered. In an existing remanufacturing process, the waste tire components are separated, thermomechanical devulcanization is used to restore the formability of the waste rubber for recycling, and waste rubber powder is mixed with chemical agents and subjected to hot rolling and extrusion to form rubber sheet products. Here, the quadruple‐bottom‐line sustainability of this remanufacturing process was studied for the first time based on the global availability of waste tires, and four technical alternatives based on different levels of automation and order of the processing steps were evaluated. The numbers of each machine for separating the tire components and processing the rubber were optimized. Quantitative sustainability analysis was conducted to calculate the sustainability index (SI) of four remanufacturing alternatives based on the technological feasibility of each processing step. Furthermore, a quantitative–qualitative sustainability assessment was performed to weight a criteria performance matrix of the technical alternatives qualitatively to overcome the lack of experience in the field. Waste‐tire remanufacturing has final SI values of ∼0.69–0.79, which exceed literature threshold values, indicating that it is a sustainable business strategy.

Smart navigation via strategic communications in a mixed autonomous paradigm

AbstractMotivated by the emerging mixed autonomous paradigm in cobotic order picking operations, we investigate the optimal information design to navigate human workers (HWs) who cooperate with autonomous mobile robots (AMRs) within an intralogistics system. We incorporate asymmetric information between AMRs and HWs in a routing game where connected AMRs are informed of the congestion state while HWs rely on information provided by the system. The system designs a communication policy aiming to navigate HWs away from congestion. Without strategic communications, we show that the deployment of AMRs cannot mitigate congestion unless the automation level reaches a threshold. Interestingly, we illustrate a substitution effect between automation and strategic communications when information distortion is mild. In contrast, severe information distortion complements automation due to exacerbated congestion. Furthermore, an in‐house AMR fleet is economically more efficient than a third‐party logistics service. Consequently, in‐house automation can be achieved with mild information distortion, while severe information distortion is required to complement the lack of efficiency in the third‐party AMR fleet. With simulated numerical examples to complement the analytical results, we provide managerial insights concerning the optimal information policies under different levels of automation, guiding warehouse managers in their communications with workers to achieve the best performance of the cobotic system.

Conflict Analysis for Cooperative Maneuvering With Status and Intent Sharing via V2X Communication

In this paper, we establish the concept of conflict analysis and demonstrate its applicability to aid the decision making of vehicles at different levels of automation and cooperation. In particular, we assume that the participating vehicles are equipped with vehicle-to-everything (V2X) communication and study cooperative maneuvers under status sharing and intent sharing. Conflict-free maneuvering strategies are developed and communication requirements for such strategies are determined. To demonstrate the developed framework, we investigate a scenario with an ego vehicle merging to a main road while another vehicle is approaching on that road. The results are demonstrated by both experimental data using real vehicles on a test track and simulations based on real highway data.