Human autonomy, technological automation (and reverse)

Nowadays, scientific developments in the vehicle and infrastructure automation sectors are developing steadily to benefit end users in ways like reducing traffic congestion, enhancing safety, facilitating stress-free travel, reducing fuel costs, and enabling smart parking. Autonomous vehicles sometimes known as self-driving cars, can entirely replace conventional automobiles to accomplish safe and reliable intelligent transportation systems (ITS). Autonomous vehicles have improved sensing capabilities and can drive on roads that would be difficult for humans. Software, technology, and people, together with their interactions, are the building blocks of Autonomous vehicles. Even though Autonomous vehicles have been studied extensively, many issues have yet to be fixed. One of the biggest obstacles to developing Autonomous vehicles is improving their ability to communicate with other vehicles and pedestrians. Second, it's unclear whether society will benefit or suffer from people's tendency to place an excessive amount of faith in Autonomous vehicles and assume that they will never malfunction. Capabilities analysis is essential to making sure autonomous vehicles are safe and widely accepted. The proposed review outlines the key benefits, drawbacks, and difficulties of autonomous vehicle technology and provides a detailed analysis of the different autonomous vehicle mechanisms. Further, the developed review intends to formulate future prospects by examining the advantages and disadvantages of autonomous driving technology to encourage the development of innovative autonomous vehicle technologies to prevent human error and increase road safety and security.

Currently, an increasing number of drivers are facing challenges associated with the decline in physical function as they age. The widespread adoption of autonomous vehicle technology holds the promise of addressing travel difficulties for older adults. However, older adults encounter difficulties in using autonomous vehicle technology due to their declining physiological conditions and cognitive abilities. Therefore, this paper aims to understand the readiness of older adults for autonomous vehicle technology. The paper applies Human Readiness Level (HRL) to discuss the performance of older adults using three specific autonomous vehicle features—Adaptive Cruise Control (ACC), Blind Spot Warning (BSW), and Lane Departure Warning (LDW). Employing a literature review approach, this paper conducts database screening on the research topics evaluating the readiness and driving performance of older adults for autonomous vehicle technology with the application of HRL and related theories. In total, 15 articles were selected as core literature. We propose recommendations and measures on how to enhance the readiness of older adults for autonomous vehicle technology from both technological and individual perspectives to enhance the readiness of older adults for autonomous vehicle technology and ensure safer travel for them.

The advent of innovative techniques, such as the CRISPR/Cas system, has opened up a new range of possibilities for modifying the genome, with the potential to address previously unmet therapeutic needs of patients with genetic diseases. These new possibilities have not only raised ethical concerns but also challenged existing classifications of genome modification techniques. While the legal status of some of these new therapies remains uncertain, there is an ongoing debate within philosophy of biology about the information-related metaphors adopted by scientists to describe and classify the genome and its therapeutic modification. Given the continuing advance of new genomic therapies, we show, employing an interdisciplinary approach, that a comprehensive framework for the classification of these technologies is needed to resolve legal and philosophical issues. The first section provides an analysis of the current state of novel genome-modifying techniques in medical genetics. In the second section, we assess the regulatory status of these techniques within the European regulatory framework for advanced therapy medicinal products (ATMPs). Drawing on these results, we argue in the third section from a philosophical perspective that metaphors, such as ‘editing’ the genome, which are based on a conception of the genome as linear information, cannot adequately capture the breadth of advanced genomic technologies. To accurately categorise these techniques in a manner that meets their diverse applications, we propose introducing the umbrella term ‘somatic genomic therapies’ (SGTs). Urging an integrative approach to defining and classifying new technologies in medical genetics, we advocate for the development of an integrative concept of SGTs.

The autonomous vehicular technology is approaching a level of maturity that gives confidence to end-users in many cities around the world for their usage so as to share the roads with manual vehicles. Autonomous and manual vehicles have different capabilities which may result in surprising safety, security, and resilience impacts when mixed together as a part of the intelligent transportation system (ITS). For example, autonomous vehicles can communicate electronically with one another, make fast decisions and associated actuation, and generally act deterministically. In contrast, manual vehicles cannot communicate electronically, are limited by the capabilities and slow reaction of human drivers, and may show some uncertainty and even irrationality in behavior due to the involvement of humans. At the same time, humans can react properly to more complex situations than autonomous vehicles. Unlike manual vehicles, the security of computing and communications of autonomous vehicles can be compromised thereby precluding them from achieving individual or group goals.

The autonomous vehicle (AV) is one of the first commercialized AI-embedded robots to make autonomous decisions. Despite technological advancements, unavoidable AV accidents that result in life-and-death consequences cannot be completely eliminated. The emerging social concern of how an AV should make ethical decisions during unavoidable accidents is referred to as the moral dilemma of AV, which has promoted heated discussions among various stakeholders. However, there are research gaps in explainable AV ethical decision-making processes that predict how AVs’ moral behaviors are made that are acceptable from the AV users’ perspectives. This study addresses the key question: What factors affect ethical behavioral intentions in the AV moral dilemma? To answer this question, this study draws theories from multidisciplinary research fields to propose the “Integrative ethical decision-making framework for the AV moral dilemma.” The framework includes four interdependent ethical decision-making stages: AV moral dilemma issue framing, intuitive moral reasoning, rational moral reasoning, and ethical behavioral intention making. Further, the framework includes variables (e.g., perceived moral intensity, individual factors, and personal moral philosophies) that influence the ethical decision-making process. For instance, the framework explains that AV users from Eastern cultures will tend to endorse a situationist ethics position (high idealism and high relativism), which views that ethical decisions are relative to context, compared to AV users from Western cultures. This proposition is derived from the link between individual factors and personal moral philosophy. Moreover, the framework proposes a dual-process theory, which explains that both intuitive and rational moral reasoning are integral processes of ethical decision-making during the AV moral dilemma. Further, this framework describes that ethical behavioral intentions that lead to decisions in the AV moral dilemma are not fixed, but are based on how an individual perceives the seriousness of the situation, which is shaped by their personal moral philosophy. This framework provides a step-by-step explanation of how pluralistic ethical decision-making occurs, reducing the abstractness of AV moral reasoning processes.

Most of the issues addressed in the last four chapters fall within the ethics of neuroscience.This involves consideration of the benefits and risks of dif fer ent interventions in the brain and whether individuals have the cognitive and emotional capacity to consent to these interventions.It also involves the obligation of clinicians and researchers to protect patients and research subjects from harm regarding neuroimaging, psychopharmacology, or neuromodulation.This obligation consists in not exposing them to undue risk and upholding privacy and confidentiality of information about their brains.This is distinct from the neuroscience of ethics, which involves the neurobiological basis of moral reasoning and decision-making.More specifically, this branch of neuroethics involves the combination of neuroimaging and behavioral observation to assess people's cognitive and emotional capacity to recognize and respond to reasons for or against actions.Morality involves the intersection of ge ne tic, neurobiological, psychological, and social factors (Tancredi, 2005).As noted in chapter 1, the ethics of neuroscience and the neuroscience of ethics can overlap.The discussion of moral enhancement in chapter 5 involved both branches of neuroethics.Still, questions about rational and moral decision-making and be hav ior control require a more extended analy sis of the neurobiological basis of our mental states and actions, and I do that in this chapter.I discuss how theoretical and clinical neuroscientists attempt to explain moral reasoning by examining its neural correlates.I also discuss how they can administer brain-and mind-altering psychotropic drugs or neuromodulating techniques that can alter how we think and act.These may include individuals with neural pathologies resulting in criminal offenses.These

Autonomous vehicles (AVs) are receiving attention in many countries, including Thailand. However, implementing an intelligent transport system has many challenges, such as safety and reliability and the lack of policy supporting such technology use, leading to hazards for passengers and pedestrians. Hence, factors affecting the adoption of autonomous vehicles require better understanding. This research proposes and employs an extended Technology Acceptance Model (TAM) by integrating ethical standards, legal concerns, and trust to predict the intended use of autonomous vehicles by Thai citizens. A total of 318 questionnaires were collected from online panel respondents. Research hypotheses were tested using a structural equation modelling approach. The study results suggest that ethical standards have a significant positive effect on the intention to use the technology. Meanwhile, the intention was negatively affected by perceived usefulness, perceived ease of use and legal concerns. On the other hand, the results indicate that perceived ease of use directly affected trust, leading to AV adoption. However, other factors influenced trust insignificantly. This study demonstrates the vital role of trust in AV adoption. The study also suggests ideas for further study and discusses the implications for the government and autonomous vehicle companies. The article aims to forecast a success factor that the Thai government should use to consider the policy for autonomous vehicle adoption in Thailand. This paper relies on the technology acceptance model to assess and forecast autonomous vehicle adoption. The theoretical model also includes ethical issues, legal concerns and trust in technology. The model was analysed using the structure equation modelling technique to confirm the factor affecting Thailand’s successful autonomous vehicle adoption. This research confirmed that ethical standards, legal concerns, and trust in technology are the factors significantly affecting the intention to use an autonomous vehicle in Thailand. On the other hand, the perceived ease of use significantly affects the trust in autonomous vehicle technology. This research found that such social factors as ethical standards, legal concerns, and trust in technology affect technology adoption significantly, especially technology related to AI operation. Therefore, the technology acceptance model could be modified to confirm technology adoption in terms of social factors. The government could use the research results to develop a public policy for the regulation and standard supporting autonomous vehicle adoption in Thailand.

Artificial Intelligence (AI) stands at the forefront of technological innovation, promising to reshape industries and improve human lives. However, as AI technologies proliferate, so do the ethical dilemmas they pose. This paper presents a comprehensive review of the ethical considerations surrounding AI, delving into nuanced discussions on privacy, bias, job displacement, autonomous decision-making, and accountability. Drawing on an extensive body of literature, industry reports, and real-world examples, this review elucidates the intricate interplay between technological advancement and societal values. Privacy concerns loom large in the era of AI, as algorithms increasingly rely on vast troves of personal data to fuel their decision-making processes. From social media platforms to healthcare systems, the collection and analysis of sensitive information raise profound questions about consent, data ownership, and individual autonomy. For instance, a study by Acquisti and Grossklags (2006) found that individuals are often unaware of the extent to which their personal data is being used and shared, highlighting the need for robust privacy protections in AI systems. Bias and fairness represent another ethical minefield in the realm of AI, with algorithms often reflecting and amplifying societal prejudices present in training data. Research by Obermeyer et al. (2019) revealed racial bias in a widely used healthcare algorithm, leading to disparities in patient care. Such instances underscore the urgency of addressing bias in AI systems through careful data curation, algorithmic transparency, and community engagement. The specter of job displacement looms large as AI-driven automation threatens to reshape labor markets worldwide. According to a report by the World Economic Forum (2020), an estimated 85 million jobs may be displaced by AI by 2025, with significant implications for income inequality and social stability. Mitigating the adverse effects of automation requires proactive measures, such as investment in education and training programs, as well as policies to ensure a just transition for displaced workers. Autonomous decision-making by AI systems raises complex ethical questions regarding accountability and liability. The opacity of many AI algorithms complicates efforts to attribute responsibility for algorithmic outcomes, particularly in cases of harm or discrimination. For instance, the emergence of autonomous vehicles has sparked debates about moral decision-making in life-or- death scenarios. Ethical frameworks for AI accountability emphasize the importance of transparency, explainability, and human oversight in algorithmic decision-making processes.

Autonomous vehicles can be operated without the need for human intervention by perceiving their physical environment, thanks to their automatic control systems. At present, extensive studies on autonomous land, sea, and air vehicles are ongoing all around the world. This project is focused on autonomous land vehicles. In the simplest examples, the speed and position of the vehicle can be controlled with the position sensor in the front wheel section and the speed sensors in the rear wheel section. Autonomy is achieved by generating signals for the control system by interpreting the data from various sensors on the vehicle with the aid of an algorithm. Different control methods can be applied for such vehicles. Within the scope of this project, the control of the vehicle will be provided by PID (Proportional-Integral-Derivative) control method, in order to constitute a basis for autonomous vehicle technology,

Autonomous vehicle technology is introducing new capabilities and challenges to the transportation system. Along with its inclusion in the on-road transportation, industries are also adapting this technology for ground vehicles to increase the efficiency and safety of material transport at their facilities. Similar to the issues concerning on-road autonomous vehicle and road-user communication, the implementation of autonomous ground vehicles in industrial settings also requires ways for the vehicles to communicate with operators and people nearby. This study created videos of a simulated autonomous industrial vehicle equipped with different types of communicating features. An online survey collected responses (n = 1008) testing twelve external features for people nearby and ten internal features for operators. The findings reveal that a great deal of training is required for people to understand the features based on colored lights. Redundant features and the inclusion of clear texts and audible messages would facilitate comprehending a vehicle’s intended action.

<p><em>This article examines the challenges of autonomous motor vehicles for Queensland road and criminal laws</em>. <em>Autonomous vehicles refer to motor vehicles where driver decision making has been augmented or replaced by intelligent systems. Proponents of autonomous vehicles argue that they will virtually eliminate road accidents, boost productivity and provide significant environmental benefits. The key issue is that autonomous vehicles challenge the notion of human responsibility which lies at the core of Queensland’s road and criminal laws. The road rules are predicated on a driver in control of the vehicle, the intoxication regime is concerned with the person in charge of the vehicle and the dangerous driving offences require a person who operates a vehicle. Notwithstanding this challenge, it can be seen that much of Queensland’s law is adaptable to autonomous vehicles. However, there are some identifiable anomalies that require reform.</em></p>

The autonomous vehicle technology is considered as a significant market disruptor for multiple industries. However, to reach this potential and to be accepted by the public, autonomous vehicles must be proven to be reliable and safe. Therefore, validation is essential for improving the public trust for autonomous vehicles and deploying them for everyday transportation activities. There have been a number of significant efforts on validation of autonomous vehicles; and real-life testing and test tracks have been the major platforms for these activities. However, simulation has also been gaining popularity due to its advantages in cost, time and safety. In this paper, we present a simulation scenario generation methodology with pseudo-random test generation to validate the decision-making system of autonomous vehicles. The methodology separates the validation concerns and focuses on generating scenarios that test the decisions taken by the vehicle. The implementation demonstrates the capabilities and the efficiency of the approach.

QCAE-QOC-SVM: A hybrid quantum machine learning model for DoS and Fuzzy attack detection on autonomous vehicle CAN bus.

As autonomous vehicles (AVs) evolve recently, it is necessary to address the unique needs of the aging population group. They can get a significant benefit from this technology. This scoping review focus the role of machine learning and vision neural networks in autonomous vehicles. A focus on enhancing safety, usability, and trust for elderly users will be mentioned as well. It systematically reviews existing literature to identify how these technologies address the cognitive and physical challenges faced by older adults. The review highlights key advancements in AV technology, such as adaptive interfaces and assistive features. That can enhance the driving experience for the elderly. Additionally, it investigates factors influencing trust and acceptance of AVs among older adults, emphasizing the importance of transparent and user-friendly design. Although, the despite notable progress has been made, the significant gaps remain in understanding how to optimize these technologies to meet the diverse needs of elderly passengers. The review identifies areas for future research, including personalized AV systems and regulatory frameworks that support designs friendly to the elderly. By addressing these gaps, the study aims to contribute to developing autonomous vehicles that are inclusive and accessible. It will make the mobility and quality of life for the aging population increased. This review underscores the importance of integrating machine learning and vision neural networks in designing AVs that cater to the unique needs of older adults. It was also offering valuable insights for researchers, policymakers, and industry stakeholders advancing autonomous vehicle technology.

The pursuit of autonomous vehicles has led to a growing interest in understanding Public Acceptance (PA), particularly within the Malaysian context. This study explores the intricate relationships between autonomous vehicle acceptance and various contributing factors. Drawing inspiration from a comprehensive hypothesis testing analysis, the research investigates the influence of Effort Expectancy (EE), Social Influence (SI), Relative Advantage (RA), Perceived Risk (PR), Self-Efficacy (SE), Anxiety (AN), and Attitude (AT) on Malaysian acceptance of autonomous vehicles. The presented findings offer nuanced insights that mirror the hypothesis test outcomes to illuminate potential determinants of Malaysian ATs toward autonomous vehicles. The results reveal the significance of SI, PR, SE, and AT in shaping Malaysian acceptance of autonomous vehicles. These determinants are consistent with theoretical expectations and provide empirical support for their influence on individuals’ willingness to embrace autonomous vehicle technology. Conversely, the complex interplay observed between factors like EE, RA, and AN points to a need for further investigation and contextual exploration. These findings enrich the understanding of autonomous vehicle acceptance and serve as a guiding compass for stakeholders seeking to foster an environment conducive to the successful integration of autonomous vehicles in the Malaysian landscape. The implications of these findings extend beyond academia, offering practical insights for policymakers, industry stakeholders, and researchers alike. This study contributes to the ongoing dialogue surrounding innovative transportation technologies and their societal implications by bridging the research outcomes with the Malaysian context. The outcomes provide a foundation for future research endeavors and interventions to enhance autonomous vehicle acceptance and contribute to the sustainable advancement of transportation systems within Malaysia.