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Many governments find it challenging to set up a regulatory regime to govern rapidly developing Autonomous Vehicles (AVs) technologies empowered by Artificial Intelligence. This paper analyzes flexible regulation as a tool for assessing regulatory reforms that govern disruptive innovations such as AVs. After defining flexible regulation as regulation that gives regulated entities choices for how to comply with the regulatory objectives, this paper develops Regulatory Flexibility Indicators (RFI) for rule structure, enforcement structure, and regulatory feedback. We study AVs regulatory reforms that took place recently in the United Kingdom and South Korea, focusing on how such reforms have enhanced regulation flexibility. This paper finds that regulatory governance in the United Kingdom is more flexible than in South Korea, indicating aspects of further reforms for improving regulatory flexibility. [ABSTRACT FROM AUTHOR]

• Drivers on slip roads want vehicles on the target lane to decelerate. • Drivers in target lanes rate the behaviour of vehicles on slip roads ambiguously. • AVs are rated identically or even more positively than MVs with identical behaviour. • No different safety distance is kept from automated vehicles. • Results show that cross-border traffic between Germany and UK with AVs is feasible. • Intercultural aspects must still be considered in the development of AVs. To ensure safe and uninterrupted traffic flow, (semi-)automated vehicles must be capable of providing comprehensible and agreeable implicit communication cues to human drivers. This driving simulator study investigated the assessment of implicit communication at a motorway slip road through longitudinal driving dynamics (acceleration, deceleration, and maintaining speed). The second aim of the study was to determine whether expectations of automated vehicles are different from those of human drivers. And thirdly, we investigated whether these findings are country-specific or can be (partially) generalised to other countries. The perception of three means of communication in connection with the presence of a labelling as an automated vehicle (eHMI) was examined in two samples in Germany and England. 27 participants drove from a slip road onto the motorway and interacted with another vehicle. After a stretch on the motorway, they passed a second slip road on which there was a vehicle merging onto the participants lane. This was repeated six times to test all variables. After each situation, the perceived cooperativity and criticality was recorded, as well as the time headway (THW) to the other vehicle. This paper presents the findings from the UK sample and compares them with the German results, which were previously published. Results show, that when the cooperating vehicles are on the slip road, participants from both countries prefer this vehicle to decelerate. However, when participants themselves are on the slip road, expectations for vehicles on the target lane are ambiguous in the UK sample. Except for one aspect (perceived cooperativity of decelerating vehicles on the slip road), the perception of automated vehicles is similar to those of manual drivers. Also, UK participants do not maintain a different safety distance from these vehicles, while this is the case in the German sample. This paper contributes valuable insights into the cross-cultural evaluation of driving dynamics, shedding light on implications for the development and acceptance of automated vehicles. [ABSTRACT FROM AUTHOR]

Autonomous vehicles ('AVs') promise to revolutionise transportation. Such vehicles use advanced sensors and artificial intelligence to navigate roads and avoid obstacles in traffic with limited to no human intervention. As AVs become more widely used, a critical question arises concerning who should be held liable for the harm their use might cause. This article shall examine if the Automated and Electric Vehicles Act 2018, product liability laws, and the law of contract can appropriately identify on whom liability falls where AVs cause accidents. Additionally, this article shall explore the trolley problem which confronts liability for AV-caused accidents: faced with inevitable harm to one or others, an AV must promptly elect to whom amongst different persons it should direct that harm, raising the question of who must be liable when an AV so acts. This paper aims to demonstrate that, although the current legal framework allows for the deployment of AVs, it requires significant adaptation to speak to the full prism of issues concerning AV-caused accident liability. [ABSTRACT FROM AUTHOR]

Connected and Autonomous Vehicles (CAVs) are promised by their developers to transform mobilities, making travel accessible to all – including those unable to drive due to age, affordability or disability – and thereby widen the distribution of what Urry calls 'network capital'. This paper interrogates promotional visualizations about CAVs as they imagine future automated mobilities and the scaling up of the technologies from small trials to mass roll-out. It analyses a wide range of images from a CAV trial in a UK city and demonstrates that these images reinforce rather than disrupt traditional gendered associations of automobility. This study further develops this work and notes other ways in which visualizations of CAV-enabled network mobility reiterate existing network capital inequalities. It also pays careful attention to the background urban environment in which CAVS are pictured. The paper argues that an absence of people and place specificity enable CAV technologies to be imagined as being used in other locations and contexts. Hence the visualizations of CAV that picture only specific forms corporeal mobility also work to envision the mobility of entrepreneurial capital, as the software and hardware behind the driverless vehicle is shown as transferable to, and profitable in, different contexts and situations. [ABSTRACT FROM AUTHOR]

This paper investigates the acceptance of Autonomous Vehicles (AVs) in Japan, the UK and Germany and speculates on the implications for policy and practice. Three on-line surveys of 3,000 members of the public in total, which were conducted in January 2017 (Japan), March 2018 (UK) and November/December 2018 (Germany) were analysed using Principal Component Analysis and then with an Ordered Logit Model. It finds that acceptance of AVs was higher amongst people with higher expectations of the benefits of AVs, those with less knowledge of AVs, and those with lower perceptions of risk. It also finds frequent drivers and car passengers to be more accepting, but that socio-economic factors were mostly insignificant. Finally, there were significant cultural differences between the levels of acceptance between Japan (broadly positive), the UK (broadly neutral) and Germany (broadly negative). These findings suggest that AV promoters should raise (or at least maintain) expectations of AVs among the public; engage with the public to reverse the negative perception of AVs; address AV-generated fears; not bother targeting people by socio-economic group; target frequent car drivers and passengers with information about what AVs could do for them; and target countries where AVs already enjoy a positive image. [ABSTRACT FROM AUTHOR]

Autonomous vehicles technology is an emerging area and has attracted lots of recognition in recent times. Accidents-free driving has always been the focal point of autonomous vehicles. Autonomous vehicles have the potential to eliminate human errors while driving, which has been argued as the predominant cause of traffic accidents. In autonomous vehicles technologies, a variety of efforts have been made to eliminate human drivers. The full elimination of humans is not possible at this moment, but some of the tasks can be automated to facilitate the drivers. In this paper, we investigate the leading causes of accidents based on UK vehicle safety data of 2017-2018. We analyze the data and investigate the leading factors which cause traffic crashes. Based on the leading features in the dataset, we then run different prediction algorithms to predict the severity of accidents under a given input feature set. The accuracy of the model with Decision Tree classifier, Random Forest, and Logistic Regression are compared, and it has been found that Random Forest performs best among others with 95% accuracy. The trained random forest model is deployed on the Internet of Things server based on Arduino, and a lightweight application is developed to get the vital data from the driver. The data is applied to the trained model to predict the risk index of driving. This application is lightweight but yet provide a significant contribution in terms of safety in autonomous vehicles. [ABSTRACT FROM AUTHOR]

• There has been a limited scope of investigation of the contextual factors affecting driver decision-making during narrow passage interactions. • The study found that the likelihood of giving way may alter due to characteristics of the interaction partners, including their vehicle type. • It was also found that factors, external to the direct interaction partners, may affect the likelihood of giving way, such as the presence of vehicles beyond the direct interaction partners. • This paper validates previous communication findings in a UK context. Narrow passage interactions have received increased attention from academics seeking to create behavioural models of the interaction and those looking to define how autonomous vehicles (AVs) should interact with their human counterparts in a composite road system. Despite this increased attention, many factors remain unexplored in the narrow passage literature, with the literature also encompassing few driving culture contexts. To this end, this study employs an explorative survey to identify additional factors that affect driver decision-making during narrow passage interactions, as well as driver perceptions of different communications in a UK context. The study's 243 participants were presented with a range of different narrow passage scenarios and asked to indicate how likely they were to give way/yield to a vehicle approaching the narrow passage from the opposite direction. In addition, they also completed the Multidimensional Driving Style Inventory to identify their driving styles and asked to identify which signals they look for from their interaction partner during narrow passage interactions, as well as the meaning of those signals. The results of the study show that situational characteristics such as the vehicle type being interacted with, being in a rush and being followed by vehicles alter the likelihood of drivers giving way at narrow passages, whilst a person's driving style can also indicate how likely someone is to give way to another vehicle. These results highlight the factors that are considered by drivers, increasing our understanding of the factors that need to be incorporated in driver behaviour models and in AV development. [ABSTRACT FROM AUTHOR]

Governments, industry and academia are paying high attention to autonomous vehicles and platooning, due to their high potential to transform public and private transport and reduce carbon emissions generated by road transport. The road freight sector is expected to be an early adopter of the autonomous technology due to the potential cost reduction for logistics companies. However, despite the expected fuel savings and polluting emission reductions due to truck platooning, actual benefits would strongly depend on the adopted technology and the operational conditions of the system. This paper investigates the potential for truck platooning to reduce carbon emissions from road freight, presenting a series of scenarios that vary by adoption rates, operational models and platoon size. Scenarios were co-designed with freight stakeholders to build a Truck Platooning Roadmap (2025–2050), considering a specific case study: the UK. Polluting emissions and related external costs are calculated across the different scenarios. Results show that there is high uncertainty for the adoption of truck platooning, with a potential first phase involving a small pool of low-automated trucks, and a second phase with a larger pool of high-automated trucks, reflecting higher economic and environmental benefits. A series of other technological and policy considerations are presented to support policymakers to draw a zero-carbon road freight strategy. [ABSTRACT FROM AUTHOR]

• Acceptance of shared automated vehicles was investigated among United Kingdom private car owners through a focus group. • From a long list of factors based on previous research, three main factors (Service Quality, Trust, Price Value) came out as overwhelmingly discussed. • Shared Space Quality, Security and Trusting Co-passengers are introduced as important indicators to accept shared automated vehicles. • Trusting Co-passengers was found to be as important as Trusting Automated Vehicles. • An extended UTAUT2 is proposed for future acceptance research on shared automated vehicles. The development of Shared Automated Vehicles (SAVs) is well underway to provide mobility as a service (MaaS) and bring benefits such as reduced traffic congestion, reduced reliance on privately owned vehicles and increased independence to non-drivers. To realise the benefits of SAVs, adoption by private vehicle users is crucial. Previous research has shown this subset of users as the least likely to adopt SAVs, and it is not well understood what factors are important to achieve such adoption. The purpose of this study is to obtain an in-depth understanding of attitudes, perceptions and preferences that influence the acceptance of future SAVs for drivers. This paper presents the results from an online asynchronous focus group study with 21 British drivers as participants. From the analysis, Service Quality, Trust and Price Value emerged as the three most prominent factors to understand user acceptance of SAVs. These three main factors may be of prime importance for convincing naïve private car owners to accept high-speed SAVs. Productive use of travel time has been frequently mentioned in previous research as a benefit of vehicle automation but was scarcely mentioned by participants in this study. Shared Space Quality in introduced as an indicator for Service Quality, together with Security and Trusting Co-passengers as two indicators of Trust. Based on the findings, this paper concludes with a conceptual SAV technology acceptance model is introduced, with the results added as extended model predictors to the Unified Theory of Acceptance and Use of Technology (UTAUT2). [ABSTRACT FROM AUTHOR]

Autonomous Vehicles (AVs) present enormous uncertainties and challenges for future urban transport and mobility. While urban and transportation planning have significant roles to play in shaping these futures, a critical challenge is identifying and reconciling divergent values and competing visions in relation to this potentially disruptive transport technology and the associated mobility services. In this paper, we demonstrate the use of a participatory multi-criteria visioning and appraisal framework and methodology to enable stakeholders to envision, identify and interrogate essential tensions between imagined AV futures and long-term transport and mobility imperatives. Based on workshops with stakeholders at the forefront of policy and practice, and academia in Greater Manchester (UK) and Melbourne (Australia), we reveal several insights. Regarding the prospects of AVs, our participants are neither 'opponents' nor 'evangelists', but instead, manifest the contrasting attitudes and perspectives of excitement, optimism, ambivalence, scepticism and uncertainty all at the same time. In the visions outlined and appraised, our stakeholders identify AVs prospects in various use cases, such as public transport, personal and shared-use and urban freight and delivery applications, while at the same time recognising the inherent contradictions between automated driving futures outlined and imperatives such as reversing auto-mobility and creating safe and inclusive urban environments. Finally, the study brings to the fore the significant role of governance in mediating the politics and resolving contestations in critical areas including data management and privacy, cybersecurity and implementing viable business models and ownership arrangements. • Develop and apply participatory multi-criteria framework to envision and appraise automated driving futures. • Identify and interrogate essential tensions between imagined AV futures and long-term transport and mobility imperatives. • Identify AVs prospects in various use cases, such as public transport, personal and shared-use. • Inherent contradictions between automated driving, reversing auto-mobility and creating safe urban environments. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the author discusses various reports within the issue on topics including studies on the role of planning in the housing crisis in Great Britain, the rise of autonomous vehicles, and community regeneration projects in Great Britain.

The Automated and Electric Vehicles Act 2018 (AEVA 2018) received Royal Assent in July 2018 as the UK's first piece of insurance legislation for Connected and Autonomous Vehicles (CAV). The legislation clearly only regulates vehicles of higher autonomy, that is vehicles which are 'capable of...driving themselves'. Interestingly, these vehicles are currently not available on public roads, meaning that the legislation is predictive of future challenges. Moreover, the legislation is rather broad, with an absence of precise definitions or application: such breadth is clearly to ensure that the legislation remains connected to the technology in the future. The UK has clearly been proactive in its approach; however, concerns are evident around the fact that the UK, in its attempt to legislate ahead of the arrival of the technology, is likely to cause confusion due to the unclear nature of the AEVA 2018's provisions. Both the issues of regulatory connection and proactive law are distinct areas of academic study which have not, as of yet been explored together in relation to a piece of legislation. The study of these issues in relation to the AEVA 2018 in this paper will further discuss the difficulty in balancing these. This paper will explore some of the insurance and liability difficulties with the current AEVA 2018. It will further uniquely discuss solutions to these challenges taking into account regulatory connection and proactive law. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs) are being developed and designed to operate on existing roads. Their safe and efficient operation during roadworks, where traffic management measures are often introduced, is crucial. Two alternative measures are commonly applied during roadworks on motorways: (i) closing one or multiple lanes (ii) narrowing one or all lanes. The former can cause delays and increased emissions, while the latter can pose safety risks. This study uses a VISSIM‐based traffic microsimulation to compare the effectiveness of these two strategies on traffic efficiency and safety, considering various market penetration rates (MPR) of CAVs. The model was calibrated and validated with the data collected from M1 motorway in the United Kingdom. Results show that average delays per vehicle‐kilometre‐travelled decreased from 102.7 to 2.5 s (with lane closure) and 23.6 to 0.6 s (with narrow lanes) with 0% and 100% CAV MPR, respectively. Moreover, safety in narrow lanes improved by 4.8 times compared to 1.5 times improvement in lane closure with a 100% CAV MPR; indicating that narrow lanes would result in better safety performance. These findings could assist transport authorities in designing temporary traffic management measure that results in better CAV performance when navigating through roadworks. [ABSTRACT FROM AUTHOR]

Autonomous vehicles technology is an emerging area and has attracted lots of recognition in recent times. Accidents-free driving has always been the focal point of autonomous vehicles. Autonomous vehicles have the potential to eliminate human errors while driving, which has been argued as the predominant cause of traffic accidents. In autonomous vehicles technologies, a variety of efforts have been made to eliminate human drivers. The full elimination of humans is not possible at this moment, but some of the tasks can be automated to facilitate the drivers. In this paper, we investigate the leading causes of accidents based on UK vehicle safety data of 2017-2018. We analyze the data and investigate the leading factors which cause traffic crashes. Based on the leading features in the dataset, we then run different prediction algorithms to predict the severity of accidents under a given input feature set. The accuracy of the model with Decision Tree classifier, Random Forest, and Logistic Regression are compared, and it has been found that Random Forest performs best among others with 95% accuracy. The trained random forest model is deployed on the Internet of Things server based on Arduino, and a lightweight application is developed to get the vital data from the driver. The data is applied to the trained model to predict the risk index of driving. This application is lightweight but yet provide a significant contribution in terms of safety in autonomous vehicles. [ABSTRACT FROM AUTHOR]

Expectations about emerging innovations are an important part of innovation pathways that can help to overcome uncertainties and build hype. Such sociotechnical expectations have been studied extensively by social scientists but the focus is often on collective, widely shared expectations and much less on individuals' specific expectations. Examining the latter can nonetheless aid understanding of the development of, buy-in into and power dynamics around collective sociotechnical expectations. This paper therefore examines individually articulated expectations about vehicle automation in the trucking industry in the UK. It draws on 61 in-depth interviews with freight transport actors, including truck drivers, freight company management, industry representatives, and representative from government departments. It demonstrates alignment of individual expectations on some aspects of vehicle automation, including the difficulty of expression them in terms of chronological (calendar) time and the belief that automation will be quicker and easier on motorways than on other kinds of road. Multiple differences in expectations are identified, in particular regarding the practical feasibility of truck platooning and the role of truck drivers. In all cases, it is clear that individual expectations are shaped strongly by people's current and past professional experience and practices and how these have been affected by wider technological and organisational changes in the freight and logistics sector. • examines individually articulated expectations of automated freight and logistical futures • recognises alignment and differentiation of individually articulated sociotechnical expectations • shows how individuals' expectations are tethered to past and current practices and professional lifeworld • signals the importance of everyday, spatialised experiences of industry actors for automated futures [ABSTRACT FROM AUTHOR]

This study examines the willingness of a sample of 526 current UK non-drivers to travel in driverless vehicles (DVs). Road traffic is predicted to increase between 10%-40% consequent to current non-drivers taking to the road; the new market including individuals who are unable or unwilling to drive: the aged, people with physical and/or mental impairments, and those who possess phobias about driving. Behavioural Reasoning Theory is employed to explore explicit and implicit attitudes of non-drivers towards DVs. Implicit attitudes towards this 'really new' product are measured via an Affect Misattribution Procedure (AMP). Sample members completed an online questionnaire containing the AMP plus items on reasons for and against DVs, beliefs and values concerning new technologies, and covariates suggested by literature in the transport marketing field. [ABSTRACT FROM AUTHOR]

In recent years, there has been a remarkable development in the technology and legislation related to electric and autonomous vehicles (i.e., EVs/AVs). This technological advancement requires the deployment of the most up-to-date supporting infrastructure to achieve safe operation. Further infrastructure is needed for Level 5 vehicles, namely the introduction of super-fast wireless 5G technology. To achieve harmony between the rapid technological advancement of EVs/AVs and environmental preservation, enacting legislation related to their sustainable use is vital. Thus, this manuscript provides a review of the technological development of EVs/AVs, with a special focus on carbon footprints and the implementation of additive manufacturing using recycled materials. While EVs have a 12.13% increased carbon footprint compared to conventional vehicles, AVs with basic and advanced intelligence features have an increased carbon footprint of 41.43% and 99.65%, respectively. This article emphasizes that the integration of 3D-printed components has the potential to offset this impact with a substantial 60% reduction. As a result, custom-made solutions involving 3D printing are explored, leading to greater speed, customization, and cost-effectiveness for EVs/AVs. This article also lists the advantages and disadvantages of the existing legislation in Spain, the United Kingdom, and the western Balkans, demonstrating various approaches to promoting electric mobility and the development of autonomous vehicles. In Spain, initiatives like the MOVES program incentivize EV adoption, while the UK focuses on expanding the EV market and addressing concerns about EVs' quiet operation. In the western Balkans, the adoption of legislation lags behind, with limited incentives and infrastructure for EVs. To boost sales, legal mechanisms are necessary to reduce costs and improve accessibility, in addition to offering subsidies for the purchase of EVs. To this end, an analysis of the incentive measures proposed for the development and use of renewable power sources for the supply of energy for EVs/AVs is presented. [ABSTRACT FROM AUTHOR]

The Department of Transport in the United Kingdom recorded 25,080 motor vehicle fatalities in 2019. This situation stresses the need for an intelligent transport system (ITS) that improves road safety and security by avoiding human errors with the use of autonomous vehicles (AVs). Therefore, this survey discusses the current development of two main components of an ITS: (1) gathering of AVs surrounding data using sensors; and (2) enabling vehicular communication technologies. First, the paper discusses various sensors and their role in AVs. Then, various communication technologies for AVs to facilitate vehicle to everything (V2X) communication are discussed. Based on the transmission range, these technologies are grouped into three main categories: long-range, medium-range and short-range. The short-range group presents the development of Bluetooth, ZigBee and ultra-wide band communication for AVs. The medium-range examines the properties of dedicated short-range communications (DSRC). Finally, the long-range group presents the cellular-vehicle to everything (C-V2X) and 5G-new radio (5G-NR). An important characteristic which differentiates each category and its suitable application is latency. This research presents a comprehensive study of AV technologies and identifies the main advantages, disadvantages, and challenges. [ABSTRACT FROM AUTHOR]

Design of appropriate interaction and human–machine interfaces for the handover of control between vehicle automation and human driver is critical to the success of automated vehicles. Problems in this interfacing between the vehicle and driver have led, in some cases, to collisions and fatalities. In this project, Operator Event Sequence Diagrams (OESDs) were used to design the handover activities to and from vehicle automation. Previous work undertaken in driving simulators has shown that the OESDs can be used to anticipate the likely activities of drivers during the handover of vehicle control. Three such studies showed that there was a strong correlation between the activities drivers represented in OESDs and those observed from videos of drivers in the handover process, in driving simulators. For the current study, OESDs were constructed during the design of the interaction and interfaces for the handover of control to and from vehicle automation. Videos of drivers during the handover were taken on motorways in the UK and compared with the predictions from the OESDs. As before, there were strong correlations between those activities anticipated in the OESDs and those observed during the handover of vehicle control from automation to the human driver. This means that OESDs can be used with some confidence as part of the vehicle automation design process, although validity generalisation remains an important goal for future research. [ABSTRACT FROM AUTHOR]

The United Kingdom has enacted legislation to govern the liability of highly autonomous vehicles. The chosen method is peculiar, with liability placed on motor (auto) insurers despite the lack of a corresponding liability on road users. This article seeks to explain why the UK government was so invested in maintaining mass market motor insurance policies (instead of a system based on motor manufacturer liability) and suggests that the answer lies in insurers' desire to harvest customer data. We are the product. [ABSTRACT FROM AUTHOR]

Usually, the design of an Autonomous Vehicle (AV) does not take into account traffic rules and so the adoption of these rules can bring some challenges, e.g., how to come up with a Digital Highway Code which captures the proper behaviour of an AV against the traffic rules and at the same time minimises changes to the existing Highway Code? Here, we formally model and implement three Road Junction rules (from the UK Highway Code). We use timed automata to model the system and the MCAPL (Model Checking Agent Programming Language) framework to implement an agent and its environment. We also assess the behaviour of our agent according to the Road Junction rules using a double-level Model Checking technique, i.e., UPPAAL at the design level and AJPF (Agent Java PathFinder) at the development level. We have formally verified 30 properties (18 with UPPAAL and 12 with AJPF), where these properties describe the agent's behaviour against the three Road Junction rules using a simulated traffic scenario, including artefacts like traffic signs and road users. In addition, our approach aims to extract the best from the double-level verification, i.e., using time constraints in UPPAAL timed automata to determine thresholds for the AVs actions and tracing the agent's behaviour by using MCAPL, in a way that one can tell when and how a given Road Junction rule was selected by the agent. This work provides a proof-of-concept for the formal verification of AV behaviour with respect to traffic rules. [ABSTRACT FROM AUTHOR]