Driving tomorrow: the bold road ahead for autonomous vehicles

Public perceptions have been playing an important role in the development of autonomous vehicle (AV) technology. Besides AV and non-AV users, the perceptions of vulnerable roadway users are critical, as AVs will become a part of multimodal transportation system. Pedestrians and bicyclists are among the vulnerable groups of roadway users, as they are relatively unprotected compared to the occupants of AVs or non-AVs. Although AV’s capability to monitor other vehicles has been documented in many studies, there are concerns about AV’s capability in monitoring pedestrians and bicyclists. The overarching goal of this dissertation is to investigate the perceptions of pedestrians and bicyclists on AVs to understand and incorporate their perceptions in AV technology development. The specific research objectives are to- (i) categorize the positive and negative perceptions and regulation expectations of pedestrians and bicyclists, (ii) identify factors influencing AV road sharing related safety perceptions among pedestrians and bicyclists, (iii) understand pedestrians’ and bicyclists’ expectations on AV regulations and identify relevant factors influencing their attitudes towards AV regulations, and (iv) investigate the effectiveness of widely used close-ended rating-based quantitative survey question to assess AV perceptions among pedestrians and bicyclists. Two surveys conducted by Bike Pittsburgh (BikePGH) were used to accomplish the research objectives. In addition to quantitative responses, BikePGH surveys collected open-ended responses to understand the reasons for pedestrians’ and bicyclists’ quantitative responses. A combined inductive and deductive qualitative data analysis approach was applied to classify pedestrians’ and bicyclists' positive and negative perceptions and regulation expectations. Pedestrians and bicyclists expressed comparatively fewer negative opinions towards AVs than positive opinions. Negative opinions included a lack of safety and comfort around AVs and trust in the AV technology. Respondents also concerned about AV technology issues (e.g., slow and defensive driving, disruptive maneuvers). Pedestrians’ and bicyclists’ opinions were significantly influenced by their views on AV safety, familiarity with the AV technology, exposure to AV-related news, and household automobile ownership. Regulating AV movement on public roadways, developing safety assessment guidelines, and controlling oversights of AV technology developers' improper practices were the survey participants' noteworthy suggestions. Non-parametric statistical tests were conducted to compare the safety perceptions of pedestrians and bicyclists based on their characteristics, experiences, and attitudes. An ordered probit model was estimated to quantify the influence of different factors on safety perceptions of pedestrians and bicyclists regarding road sharing with AVs. In addition, safety perceptions and the effect of various factors on AV safety perceptions

What influences vulnerable road users’ perceptions of autonomous vehicles? A comparative analysis of the 2017 and 2019 Pittsburgh surveys

Due to the ongoing enormous infrastructural developments and car ownership culture in Qatar, it could be one of those countries to introduce Autonomous Vehicles (AV) technology at the early stages. Therefore, this study surveyed a number of residents at the State of Qatar to improve our understandings of their perceptions regarding overall safety of AV (General_safety), safety due to the fact that AV could eliminate human errors (Human_errors), safety due to the interactions between Human-Driven Vehicles (HDV) and AV (HDV-AV_interactions), performance in harsh environmental conditions, security, comfort level, travel time, congestion and operational costs. In addition, the study uncovered the relationships of public perceptions towards AV and some other contextual factors with the willingness to adopt it in the future. To study these relations, we relied on a Structural Equation Modeling. Overall, the results showed that respondents had higher and positive perceptions regarding “General_safety” and “Human_errors”, however, they were more concerned about “HDV-AV_interactions” and its security. In addition, individuals’ preference to shift to AV in the future was positively correlated with their perception level of “General_safety”, “Human_errors”, Comfort and Travel_time. Regarding ethnicity of the respondents, non-Arabs reported higher concerns regarding AV security, compared to Arabs. Furthermore, interestingly the results revealed that individuals having higher knowledge about AV technology had more concerns on “General_safety” and “HDV-AV_interactions”, while they had positive perceptions that AV could eliminate human errors. The findings from this study are anticipated to allow AV manufacturers and other relevant authorities to enhance public confidence towards AV technology by targeting different sub-groups through particular safety or security awareness campaigns.

Autonomous vehicles have been in development for nearly thirty years and recently have begun to operate in real-world, uncontrolled settings. With such advances, more widespread research and evaluation of human interaction with autonomous vehicles (AV) is necessary. Here, we present an interview study of 32 pedestrians who have interacted with Uber AVs. Our findings are focused on understanding and trust of AVs, perceptions of AVs and artificial intelligence, and how the perception of a brand affects these constructs. We found an inherent relationship between favorable perceptions of technology and feelings of trust toward AVs. Trust in AVs was also influenced by a favorable interpretation of the company's brand and facilitated by knowledge about what AV technology is and how it might fit into everyday life. To our knowledge, this paper is the first to surface AV-related interview data from pedestrians in a natural, real-world setting.

The testing and pilot operations of autonomous vehicles are currently booming in terms of real-world operations. Although the validation and verification methods are not standardized, nor is the legislation, as well as the methodology of data collection on autonomous vehicles’ performance and safety. The safety of autonomous vehicles can be inferred from the collision and disengagement reports provided by manufacturers and operators. This report documents instances when a human driver or operator took control of an autonomous vehicle during testing in detail. Disengagement reports are primarily aimed at safety and performance evaluation of autonomous vehicles, but can they be the basis for determining the readiness of autonomous driving technology and technological progress? This study analyzes disengagement reports to assess their utility in determining autonomous vehicles’ progress and readiness. Our findings indicate a declining trend in reported disengagements, despite increased operational distances, suggesting possible improvements in autonomous vehicle technology. However, disparities in data collection, varying operational design domains, and inconsistent reporting practices among manufacturers limit direct comparability. These factors challenge the reliability of disengagement reports as a definitive measure of technological evolution. The study highlights the need for more standardized and transparent reporting to better assess autonomous vehicle safety and development trends.

The effect of ride experience on changing opinions toward autonomous vehicle safety

Autonomous vehicles (AVs) have the potential to transform the transportation industry by improving road safety, reducing traffic congestion, and enhancing fuel efficiency. Significant progress has been made in autonomous vehicle (AV) technologies, especially in sensor systems, machine learning, and artificial intelligence. These advancements enable vehicles to navigate complex environments and make real-time decisions. Despite these advancements, numerous challenges remain in ensuring the safety, reliability, and acceptance of AVs. Key issues include sensor fusion, the ability to handle unpredictable scenarios, the development of universally accepted regulatory frameworks, and public trust in autonomous systems. Furthermore, ethical dilemmas, such as decision-making in unavoidable accident situations, present additional concerns. The deployment of AVs also raises questions about the impact on employment in driving-dependent industries and the infrastructure needed to support these technologies. This paper reviews the current state of AV development, examining the progress made in simulation-based testing, sensor technology, and decision-making algorithms. Additionally, it discusses the challenges that still need to be addressed, including safety concerns, regulatory barriers, and societal implications. The paper concludes by outlining potential areas for future research, such as improving sensor reliability, enhancing machine learning algorithms, integrates an analysis of simulation-based testing, decision-making algorithms, and sensor technologies with a forward-looking discussion on legal frameworks, public trust, and employment impacts, offering a holistic perspective on the path toward AV integration.

One of the primary impediments hindering the widespread acceptance of autonomous vehicles (AVs) among pedestrians is their limited comprehension of AVs. This study employs virtual reality (VR) to provide pedestrians with an immersive environment for engaging with and comprehending AVs during unmarked midblock multilane crossings. Diverse AV driving behaviors were modeled: negotiation behavior with a yellow signal indication and non-yielding behavior with a blue signal indication. This paper aims to investigate the impacts of various factors, such as AV behavior and signaling and pedestrian past behavior, on pedestrians’ perception of AVs. Before and after the VR experiment, participants completed surveys that assessed their perceptions of AVs and focused on two main aspects: attitude and system effectiveness. The Wilcoxon signed-rank test results demonstrated that both the pedestrians’ overall attitude score toward AVs and their trust in the effectiveness of AV systems significantly increased following the VR experiment. Notably, individuals who exhibited a greater trust in the yellow signals were more inclined to display a higher attitude score toward AVs and to augment their trust in the effectiveness of AV systems. This indicates that the design of the yellow signal instills pedestrians with greater confidence in their interactions with AVs. Further, pedestrians who exhibit more aggressive crossing behavior are less likely to change their perception toward AVs as compared with pedestrians with more positive crossing behaviors. It is concluded that integrating the AV behavior and signaling devised in this paper within an immersive VR setting facilitated pedestrian engagement with AVs, thereby changing their perception of AVs.

The deployment of autonomous vehicles (AVs) powered by artificial intelligence (AI) raises profound ethical questions regarding the balance between safety and privacy. While AI-driven AVs promise to revolutionize transportation by potentially reducing accidents and increasing efficiency, concerns regarding data privacy, liability, and decision-making algorithms persist. This paper explores the ethical considerations surrounding AI-driven AVs, focusing particularly on the delicate equilibrium required to ensure both safety and privacy. Drawing upon existing literature and case studies, the paper examines the ethical dilemmas inherent in AV technology, including issues of consent, data collection, and algorithmic bias. Additionally, it delves into the regulatory frameworks and industry standards aimed at addressing these concerns. By highlighting the complexities of navigating safety and privacy in AI-driven AVs, this research contributes to the ongoing discourse on ethical AI development and deployment.

Artificial intelligence (AI) is poised to revolutionize the automotive industry through the development of fully autonomous vehicles. Self-driving cars powered by AI have the potential to dramatically improve road safety, reduce traffic congestion, increase mobility access, and transform transportation as we know it. However, the deployment of AI in vehicles also presents significant technological challenges that must be overcome, raises complex ethical considerations, and creates novel regulatory issues that policymakers will need to address. This paper provides an overview of the key opportunities and benefits of AI-driven autonomous vehicles, discusses the major challenges and open problems that remain to be solved, and explores the regulatory landscape and policy implications surrounding self-driving cars. We argue that while autonomous vehicle technology is rapidly advancing thanks to breakthroughs in AI, there are still substantial challenges to be overcome before fully self-driving cars can be safely deployed at scale. Policymakers will need to create new regulatory frameworks and standards to govern the testing and deployment of autonomous vehicles, address issues of liability and insurance, ensure safety and security, and promote public trust in the technology. With the right technological developments and policy choices, autonomous vehicles could yield immense benefits to society, but concerted collaboration between industry, academia, and government will be essential to realize this potential

The integration of Autonomous Vehicles (AVs) into modern systems of transportation brings with it a new and transformative era. Central to the successful realisation of this transformation is the public’s trust in these vehicles and their safety, particularly in the aftermath of cyber security breaches. The following research therefore explores the various factors underpinning this trust in the context of cyber security incidents. A dual-methodological approach was used in the study. Quantitative data was gathered from structured questionnaires distributed to and completed by a cohort of 151 participants and qualitative data, from comprehensive semi-structured interviews with AV technology and cyber security experts. Rigorous Structural Equation Modelling of the quantitative data then allowed for the identification of the key factors influencing public trust from the standpoint of the research participants including the perceived safety of AV technology, the severity of cyber security incidents, the historic cyber security track record of companies and the frequency of successful cyber security breaches. The role of government regulations, though also influential, emerged as less so. The qualitative data, processed via thematic analysis, resonated with the findings from the quantitative data. This highlighted the importance of perceived safety, incident severity, regulatory frameworks and corporate legacy in shaping public trust. Whilst cyber incidents no doubt erode trust in AVs, a combination of technological perception, regulatory scaffolding and corporate history critically impacts this. These insights are instrumental for stakeholders, from policymakers to AV manufacturers, in charting the course of AV assimilation successfully in future.

Sharing the road with autonomous vehicles: A qualitative analysis of the perceptions of pedestrians and bicyclists

Autonomous vehicles (AVs) have generated excitement for the future of transportation. Public transit agencies and companies (i.e., Uber) have begun developing shared autonomous transportation services. Most AV surveys focus on public opinion of perceived benefits and concerns of AVs but are not directly tied to field implementation of AVs. Experience and exposure to new technology affect adults’ perceptions and level of technology acceptance. As such, the Autonomous RideShare Services Survey (ARSSS) was developed to assess adults’ perceptions of AVs before and after being exposed to AVs. Face validity and content validity were established via focus groups and subject-matter experts (CVI = 0.95). Adults in the U.S. (N = 553) completed the ARSSS, and a subsample (N = 100) completed the survey again after two weeks. An exploratory and confirmatory factor analysis demonstrated that the ARSSS consists of three factors that can be used to reliably quantify users’ perceptions of AVs: (a) Intention to Use, Trust, and Safety (r = 0.85, p < 0.001, ICC = 0.99); (b) Potential Benefits (r = 0.70, p < 0.001, ICC = 0.97); and (c) Accessibility (r = 0.78, p < 0.001, ICC = 0.96) of AVs. These are key factors in predicting intention to use and acceptance of AVs. Results from the ARSSS may inform the acceptance among users of these AV technologies.

The successful integration of autonomous vehicles (AVs) into society hinges on public acceptance, which is closely linked to trust. This study investigates the factors influencing initial trust and specific trust requirements for the acceptance of AVs among Spanish population. A national survey was conducted with 400 participants, selected to represent the demographic diversity of Spain. The survey assessed participants' prior experience with AVs, demographic characteristics, ethical concerns, and trust levels. The findings indicate that individuals with prior direct experience with AVs exhibit higher initial trust levels. Demographic variables such as age, gender, and education significantly influence trust requirements; notably, younger and higher-educated individuals demonstrate lower trust thresholds. Ethical concerns, including data privacy and algorithmic transparency, emerge as significant predictors of trust levels. When contextualized with international studies, these findings highlight unique cultural and regulatory influences on trust in AVs within Spain. These insights are crucial for policymakers and manufacturers aiming to enhance public trust promote the ethical development and public acceptance of AVs to facilitate the widespread adoption of AVs.

Intelligent Automation (IA) in automobiles combines robotic process automation and artificial intelligence, allowing digital transformation in autonomous vehicles. IA can completely replace humans with automation with better safety and intelligent movement of vehicles. This work surveys those recent methodologies and their comparative analysis, which use artificial intelligence, machine learning, and IoT in autonomous vehicles. With the shift from manual to automation, there is a need to understand risk mitigation technologies. Thus, this work surveys the safety standards and challenges associated with autonomous vehicles in context of object detection, cybersecurity, and V2X privacy. Additionally, the conceptual autonomous technology risks and benefits are listed to study the consideration of artificial intelligence as an essential factor in handling futuristic vehicles. Researchers and organizations are innovating efficient tools and frameworks for autonomous vehicles. In this survey, in-depth analysis of design techniques of intelligent tools and frameworks for AI and IoT-based autonomous vehicles was conducted. Furthermore, autonomous electric vehicle functionality is also covered with its applications. The real-life applications of autonomous truck, bus, car, shuttle, helicopter, rover, and underground vehicles in various countries and organizations are elaborated. Furthermore, the applications of autonomous vehicles in the supply chain management and manufacturing industry are included in this survey. The advancements in autonomous vehicles technology using machine learning, deep learning, reinforcement learning, statistical techniques, and IoT are presented with comparative analysis. The important future directions are offered in order to indicate areas of potential study that may be carried out in order to enhance autonomous cars in the future.