Different Levels Of Automation Research Articles

Festschrift in honour of Professor Neville Stanton: A lone crusader in a world of driving simulators

The automotive future has always pointed to a world of intelligent co-pilots and robot cars, but perhaps no more so than Knight Rider. In this 1980's television series the fictional Knight Industries Two Thousand (KITT) was a supercomputer on wheels with 1000 megabytes of memory. The protagonist was Michael Knight, a young loner on a crusade to champion the cause of the innocent and the helpless. This was a shadowy flight into the trials and tribulations of different levels of automation, re-claiming control when automation failed, and a wilful, chatty computer co-driver. An amusing metaphor, perhaps, for the research impact made by Neville Stanton in the field of vehicle automation. Without question – to paraphrase the Knight Rider outro – “one man can make a difference”. This festschrift in Neville's honour tells the story of how.

Human-machine sense of agency

Technological advances have resulted in highly automated systems increasing in number and popularity. However, the overarching issue continues to relate to how much autonomy to give to automation and whether it could degrade the human perception of control, which is referred to as Sense of Agency. When present, the operator will be aware that their actions will lead to a certain outcome, which in turn will improve the performance over the task. Furthermore, when Sense of Agency is present, the individuals underestimate the interval between their own actions and their outcomes. This effect, known as Intentional Binding, could provide feedback regarding the effect of both automation and mental workload in Human-Machine Interaction (HMI). The objective of this paper was to find out how Intentional Binding is affected by different levels of automation, mental workload, and time delay. Intentional Binding has been measured by using a time interval estimation task. Participants were asked to reproduce the time interval between a keypress and an acoustic tone presented with different time delays (500 to 1500 ms). Automation was manipulated at the time of the initial key press to create three conditions: a) Human Decision (keypress performed by the participants), b) System Warning (computer warned the participants to press a key), c) System Decision (keypress virtually performed by the computer). The mental workload was manipulated by adding a secondary memory task, with two or eight letters to remember. Results showed that Intentional Binding was greatest with decreasing automation intervention and mental workload. These findings suggest that automation and mental workload could play a key role in degrading the Sense of Agency. Further, the time delay was shown to have different effects on each automation condition. This new finding indicates that the time delay could be an important feature in HMI and needs to be carefully designed in automated systems.

Driver Confidence and Level of Automation Influencing Trust in Automated Driving Features

The goal of this study was to empirically examine the relationship between individuals’ reported trust in automated driving features and their level of self-confidence when driving. This study utilized a series of vignettes to depict three different levels of automation in accordance with the SAE International levels of Automation. The three levels portrayed low (level 1), moderate (level3), and high (level 5) functioning autonomous driving features. A driving self-efficacy scale and trust in automation scale were utilized to collect data about individuals attitudes towards the automation. It was hypothesized that self-confidence and level of automation would be significantly related to operator’s trust. In addition to this, it was also hypothesized that the level of automation would significantly affect the amount of trust placed in the autonomous features. Results indicated that there are significant relationships between self-confidence and trust, as well as level of automation and trust.

Not all technological change is equal: how the separability of tasks mediates the effect of technology change on skill demand

Abstract We measure the labor-demand effects of two simultaneous forms of technological change—automation of production processes and consolidation of parts. We collect detailed shop-floor data from four semiconductor firms with different levels of automation and consolidation. Using the O*NET survey instrument, we collect novel task data for operator laborers that contains process-step level skill requirements, including operations and control, near vision, and dexterity requirements. We then use an engineering process model to separate the effects of the distinct technological changes on these process tasks and operator skill requirements. Within an occupation, we show that aggregate measures of technological change can mask the opposing skill biases of multiple simultaneous technological changes. In our empirical context, automation polarizes skill demand as routine, codifiable tasks requiring low and medium skills are executed by machines instead of humans, whereas the remaining and newly created human tasks tend to require low and high skills. Consolidation converges skill demand as formerly divisible low and high skill tasks are transformed into a single indivisible task with medium skill requirements and higher cost of failure. We conclude by developing a new theory for how the separability of tasks mediates the effect of technology change on skill demand by changing the divisibility of labor.

Measuring drivers’ takeover performance in varying levels of automation: Considering the influence of cognitive secondary task

Mixed control by driver and automated system will remain in use for decades until fully automated driving is perfected. Thus, drivers must be able to accurately regain control of vehicles in a timely manner when the automated system sends a takeover request (TOR) at its limitation. Therefore, determining the factors that affect drivers’ takeover quality at varying levels of automated driving is important. Previous studies have shown that visually distracting secondary tasks impair drivers’ takeover performance and increase the subjective workload. However, the influence of purely cognitive distracting secondary tasks on drivers’ takeover performance and how this influence varies at different levels of automation are still unknown. Hence, a 5 (driving modes) × 3 (cognitive secondary tasks) factorial design with the within-subject factors was adopted for this driving simulator experiment. The sample consisted of 21 participants. The participants’ subjective workloads were recorded by the NASA-Task Load Index (NASA-TLX). Results showed that compared to manual driving conditions, the drivers’ subjective workloads were significantly reduced in both partially and highly automated driving conditions, even with a TOR, confirming the benefit of the automated driving system in terms of reducing the driving workload. Moreover, the drivers exhibited a lower takeover behavior quality at high levels of automation than manual driving in terms of increased reaction time, abnormal performance, standard deviation of lane position, lane departure probability, and reduced minimum of time to collision. However, at the highly automated driving condition, the drivers’ longitudinal driving safety and ability to follow instructions improved when performing a highly cognitive secondary task. This phenomenon possibly occurred because automated driving conditions lead to an underload phenomenon, and the execution of highly cognitive tasks transfers drivers into moderate load, which helps with the drivers’ takeover performance.

Driver’s views on driverless vehicles: Public perspectives on defining and using autonomous cars

ObjectivesTo investigate how members of the public define autonomous vehicles, including perceived advantages, disadvantages and reliability. MethodsA series of qualitative interviews were conducted with 16 members of the public in Switzerland who were recruited online and through snowballing. Interviews were transcribed and coded, before being subjected to thematic analysis. ResultsThree main themes emerged from the interviews. These included differing perceptions of the level of self-automation of smart cars, across a spectrum from partial automation to fully autonomous vehicles; a variety of views on the perceived pros and cons of smart cars, including fewer accidents and potential loss of freedom; and opinions concerning whether a car would be ‘better than human’, and related issues including whether such cars should or could be subject to human override. Almost all participants saw the introduction of truly smart cars as beneficial, although many said they would not be early adopters and would always want humans to have the ability to take control. SignificanceOur results reveal generally positive attitudes to smart cars, but also some poor understanding of the different levels of automation that such cars can have, and potentially unrealistic expectations regarding the capacity of humans to re-assume control in emergencies. These factors must be considered by legislators and others involved in the introduction of smart cars onto our roads.

Effects of Automation for Emergency Operating Procedures on Human Performance in a Nuclear Power Plant.

The digitization of the control systems in the main control room of a nuclear power plant has changed the operators’ role in coping with accidents and has thus brought about new human factor problems. This article focuses on the procedures that are used for guiding the emergency operating procedures in a nuclear power plant, and experimentally investigates the effects of the digitization of procedures on operators’ mental workload and situation awareness. In these experiments, the procedures at three different levels of automation, namely, paper-based procedures (PBPs), electronic procedures (EPs), and computer-based procedures (CBPs), are used as the independent variables. According to the experimental results, using these procedures at a high level of automation enables the operator to exhibit favorable operational performance with a decreased mental workload; however, the operator’s situation awareness (SA) is decreased. The research results presented here can provide a reference level for optimally setting the level of automation of the emergency operating procedures in a nuclear power plant and provide support for the optimization of a corresponding HRA (Human Reliability Analysis) model.

The Influence of Introducing Autonomous Vehicles on Conventional Transport Modes and Travel Time

Introducing autonomous vehicles (AVs) on the market is likely to bring changes in the mobility of travelers. In this work, extensive research is conducted to study the impact of different levels of automation on the mobility of people, and full driving automation needs further study because it is still under development. The impacts of AVs on travel behavior can be studied by integrating AVs into activity-based models. The contribution of this study is the estimation of AVs’ impacts on travelers’ mobility when different travel demands are provided, and also the estimation of AVs’ impact on the modal share considering the different willingness of pay to travel by AVs. This study analyses the potential impacts of AVs on travel behavior by investigating a sample of 8500 travelers who recorded their daily activity plans in Budapest, Hungary. Three scenarios are derived to study travel behavior and to find the impacts of the AVs on the conventional transport modes. The scenarios include (1) a simulation of the existing condition, (2) a simulation of AVs as a full replacement for conventional transport modes, and (3) a simulation of the AVs with conventional transport modes concerning different marginal utilities of travel time in AVs. The simulations are done by using the Multi-Agent Transport Simulation (MATSim) open-source software, which applies a co-evolutionary optimization algorithm. Using the scenarios in the study, we develop a base model, determine the required fleet size of AVs needed to fulfill the demand of the different groups of travelers, and predict the new modal shares of the transport modes when AVs appear on the market. The results demonstrate that the travelers are exposed to a reduction in travel time once conventional transport modes are replaced by AVs. The impact of the value of travel time (VOT) on the usage of AVs and the modal share is demonstrated. The decrease in the VOT of AVs increases the usage of AVs, and it particularly decreases the usage of cars even more than other transport modes. AVs strongly affect the public transport when the VOT of AVs gets close to the VOT of public transport. Finally, the result shows that 1 AV can replace 7.85 conventional vehicles with acceptable waiting time.

Older adults and their willingness to use semi and fully autonomous vehicles: A structural equation analysis

Advanced Vehicle Technologies (AVTs) have been purported to improve the behind-the-wheel experience of older adults (65+ years) by making driving safer, easier, and more enjoyable. The autonomous vehicle, in particular, is viewed as a promising innovation for those in older age groups. However, little is known about how older adults perceive AVTs as well as their attitudes, concerns, and willingness to use different levels of vehicular automation.Using the results of an online survey of 1000 Canadians aged 65 and older (who live in the Greater Golden Horseshoe Region, Southern Ontario, Canada), this paper aims to identify and quantify key factors that can affect older adults' willingness to use vehicles with different levels of automation (e.g., semi vs. fully autonomous vehicles; SAV/FAV). Underlying this objective is a need to examine older adults' preferences and concerns for using emerging automotive technologies.Using factor analysis and structural equation modeling, several factors were also identified that can influence older adults' openness to use SAV/FAV including the perception that the AVTs would actually assist with performing driving-related tasks, participant concerns about using SAV/FAV (mainly concerns about inadequate testing on SAV/FAV and being legally responsible if SAV/FAV technology failure causes an accident), using automobile as a passenger, gender, level of education, and the need for assistance with driving. Moreover, almost two thirds of participants reported having concerns about liability if an AVT failed resulting in a crash.Findings of this study provide decision makers and car manufacturing companies with valuable insights regarding older adults' willingness and needs to use SAV/FAV.

Use of Unmanned Aircraft Systems for Bridge Inspection: A Review

This review describes the use of Unmanned Aircraft Systems (UAS) for bridge inspection, with an emphasis on Multi-rotor UAS. It depicts the different levels of automation and autonomy during UAS operation and what levels are achieved during inspections. A description of the payload of UAS consisting of the equipment required to acquire data and images is included. It also contains a compendium of the techniques used to create models from images in order to detect failures and perform Structural Health Monitoring (SHM) through techniques, such as: 3D reconstruction, infrared thermography, Structure From Motion (SFM), Convolutional Neural Network (CNN) and others. The software required to apply the mentioned techniques is also mentioned. It subsequently explains the generation of mathematical models to characterize the multirotor and generate efficient trajectories. Finally, the review concludes by describing the operational limitations of UAS and future challenges.

Levels of What?Investigating Drivers’ Understanding of Different Levels of Automation in Vehicles

Extant levels of automation (LoAs) taxonomies describe variations in function allocations between the driver and the driving automation system (DAS) from a technical perspective. However, these taxonomies miss important human factors issues and when design decisions are based on them, the resulting interaction design leaves users confused. Therefore, the aim of this paper is to describe how users perceive different DASs by eliciting insights from an empirical driving study facilitating a Wizard-of-Oz approach, where 20 participants were interviewed after experiencing systems on two different LoAs under real driving conditions. The findings show that participants talked about the DAS by describing different relationships and dependencies between three different elements: the context (traffic conditions, road types), the vehicle (abilities, limitations, vehicle operations), and the driver (control, attentional demand, interaction with displays and controls, operation of vehicle), each with associated aspects that indicate what users identify as relevant when describing a vehicle with automated systems. Based on these findings, a conceptual model is proposed by which designers can differentiate LoAs from a human-centric perspective and that can aid in the development of design guidelines for driving automation.

A MATLAB application for automated H-Reflex measurements and analyses

ObjectiveH-Reflex is a test that is carried out to measure the relative excitability of reflex pathways. Although reliable, conventional methods consist of performing many small steps, which requires a high level of attentiveness, and thus can carry an elevated risk of human error, despite proper training. Equipment that is available to perform those tests with different levels of automation are typically proprietary, inextensible by the user, and expensive. Here we present a novel MATLAB application that can accurately and reliably perform automated H-Reflex measurements, test the stimulating electrodes, and carry out typical subsequent analyses. MethodsThis application is a Graphical User Interface that works with inexpensive equipment and offers many important features such as measuring electrode impedance in-situ, automating lengthy measurements like recruitment curves and frequency response trials, standardizing electric stimulation properties, automatic exporting of digital data and metadata, and immediately analyzing acquired data with single-click events. ResultsOur new method was validated against conventional H-Reflex measurement methods with 2 anesthetized rats. The difference between acquired data using both methods was negligible (mean difference=0.0038; std=0.0121). Our app also detected electrode impedance with high accuracy (94%). ConclusionThe method presented here allows reliable and efficient automated H-reflex measurements and can accurately analyze the collected data. SignificanceThe features provided by our app can speed up data collection and reduce human error, and unlike conventional methods, allow the user to analyze data immediately after the record. This can result in higher research quality and give broader access to the technique.

Influence of levels of automation on the sense of agency during continuous action

Recent advances in automation technology can lead to unsafe situations where operators lose their sense of agency over the automated equipment. On the other hand, increasing evidence has shown that providing operators with opportunities of continuous operation and helping them improve their performance on tasks through automation can boost their sense of agency. However, it is challenging to ensure that the operator maintains a sense of agency when working with a fully automated tool that removes him/her from the control loop. By demonstrating a tracking task in which participants continuously tracked a moving target through a cursor controlled by a joystick under different levels of automation, we illustrate how the participants’ sense of agency and tracking performance were altered in accordance with the level of automation. The results showed that their sense of agency was enhanced by increasing automation but began to decline when the level of automation exceeded 90%. More generally, this suggests that allowing operators a little contribution to control over the continuous operation of an automated tool may be sufficient to maintain their sense of agency while yielding the maximum improvement in performance.

Economic evaluation of automated guided vehicles usage in a food company

Abstract Nowadays, companies are more and more attracted and interested by the possibility of automating processes which can be easily carried out by devices or machines instead of employees, allowing saving in costs, higher productivity and flexibility. Among the most spread ways of automating processes, more precisely in this specific case the flow of materials, the Automated Guided Vehicles (AGVs) stand out. But the main question that everyone asks is the following: is it convenient or not? In this paper, the answer is provided for a company operating in the food context, which intends to automate the transport of raw ingredients from the kitchens where they are produced and prepared to the filling lines; to this end, an economic feasibility study is carried out, taking into account three different levels of automation for three different lines. Results from all the three scenarios demonstrate the convenience in terms of achievable revenues, saved hours and manpower, and will support the management in their operational decisions.

Effects of Automated Vehicles on Traffic Flow With Different Levels of Automation

Highly automated vehicles are regarded as the next revolution of the transport system. Automated vehicles include a spectrum from vehicles with driver assistance systems through to highly automated vehicles. These vehicles will only gradually appear in the overall vehicle fleet. Their impact as part of future traffic is of reference value for transport decision-makers. The present paper starts from assumptions for the shares of vehicles with different levels of automation in 2030 and 2050 (representing the near and far-distant future) and compares the effects of these automated vehicles on traffic flow using microscopic traffic simulations. The simulated vehicles include non-assisted vehicles, semi-automated vehicles with driver assistance systems, and fully autonomous vehicles. To obtain a more realistic result, a traffic scenario of the city of Duisburg is used in this thesis. With the support of the city administration, existing data of the origin/target matrix, detector data including induction loops, and cameras were available. Thus, the data of the origin/target matrix are used to generate the real traffic scenario and the detector data to investigate the accuracy of the generated traffic. The result shows that automated vehicles would have a positive impact on traffic, a proportion of automated vehicles can reduce the average travel time. For areas with different traffic conditions, the degree of impact of automated vehicles can be very different.

Traffic Simulation of Future Intelligent Vehicles in Duisburg City Inner Ring

Intelligent vehicles gradually enter the vehicular fleet with advanced driver-assistance technologies. Their impact on traffic should, therefore, be considered by transportation decision-makers. This paper examines the effect of vehicles with different levels of automation on traffic flow, such as non-assisted vehicles, vehicles with driver assistance systems, and fully autonomous vehicles. The accuracy of the examined traffic scenario is also an important factor in microscopic traffic simulation. In this paper, the central part of the city of Duisburg, Duisburg’s inner ring, is chosen for the traffic scenario. Through the cooperation with local government, official data of Origin/Destination matrices, induction loops, and traffic light plans are provided for this work. Thus, traffic demand from Origin/Destination matrices and induction loops are generated and compared, respectively. Finally, vehicles with different levels of automation are simulated in the Duisburg inner ring scenario.

Cyber-Attacks Risk Analysis Method for Different Levels of Automation of Mining Processes in Mines Based on Fuzzy Theory Use.

The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan’s and Garrick’s approach and fuzzy theory. The proposed approach takes into account the level of automation of the operating mining processes. Moreover, it follows five main steps, including identifying the automation level in a selected mine, definition of cyber-attack targets, identification of cyber-attack techniques, definition of cyber-attack consequences, and risk ratio assessment. The proposed risk assessment procedure was performed according to three cyber-attack targets (databases, internal networks, machinery) and seven selected types of cyber-attack techniques. The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry. To illustrate the given method’s applicability, seven scenarios for three levels of mine automation are analyzed. The proposed method may be used to reveal the current cybersecurity status of the mine. Moreover, it will be a valuable guide for mines in which automation is planned in the near future.

Experience with Varied Levels of Automation Influences User Response Speed

When presenting an automated aid to a user, there is variation in how much a human or the automation is involved in making and acting on the decision. Level of automation describes the balance between human and computer in making decisions and selecting actions. In this study, we presented subjects with a speeded length-judgment task at two different levels of automation, manipulating the order of the automation level between subjects. We found a significant effect that subjects who were presented first with the condition where the automated aid allowed them to directly select a response (i.e., lower automation level) responded faster in later trials when then presented with the condition where the automated aid required them to agree or disagree with the aid’s response (i.e., higher automation level). This effect was not found when the higher level of automation was presented first.

Grounding the case for a European approach to the regulation of automated driving: the technology-selection effect of liability rules

In the current paper, we discuss the need for regulation at EU level of Connected and Automated Driving solutions (henceforth CAD) based on multiple considerations, namely (i) the need for uniformity of criteria across European Member States, and (ii) the impact that regulation—or the absence of it—has on the proliferation of specific technological solutions. The analysis is grounded on legal and economic considerations of possible interactions between vehicles with different levels of automation, and shows how the existing framework delays innovation. A Risk-Management Approach, identifying one sole responsible party ex ante (one-stop-shop), liable under all circumstances—pursuant to a strict, if not absolute liability rule—is to be preferred. We analyse the solution adopted by some Member States in light of those considerations and conclude that none truly corresponds to a RMA approach, and differences will also cause market fragmentation. We conclude that because legal rules determine what kind of technological application is favoured over others—and thence they are not technology-neutral—uniformity across MSs is of essential relevance, and discuss possible policy approaches to be adopted at European level.

Intelligent Agents to Improve Thermal Satisfaction by Controlling Personal Comfort Systems Under Different Levels of Automation

Heating, ventilation, and air conditioning (HVAC) systems account for 43% of building energy consumption, yet only 38% of commercial building occupants are satisfied with the thermal environment. The primary reasons for low occupant satisfaction are that HVAC operations do not integrate occupant comfort requirements nor control the thermal environment at the individual level. Personal comfort systems (PCSs) enable local control of the thermal environment around each occupant. However, full manual control of PCS can be inefficient, and fully automated PCS reduces an occupant’s perceived control over the environment, which can then lead to lower satisfaction. A better solution might lie somewhere between fully manual and fully automated environmental control. In this article, we describe the development and implementation of an Internet-of-Things (IoT)-based intelligent agent that learns individual occupant comfort requirements and controls the thermal environment using PCS (i.e., a local fan and a heater). We tested different levels of automation where control is shared between an intelligent agent and the end user. Our results show that PCS use improves occupant satisfaction and including some level of automation can improve occupant satisfaction further than what is possible with manually operated PCS. Among the levels of automation investigated, inquisitive automation, where the user approves/declines the control actions of the intelligent agent before execution, led to highest occupant satisfaction with the thermal environment.