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This chapter explores how technology availability and costs influence public opinion, vehicle ownership decisions, travel, and location choices. Attitudes towards electric vehicles (EVs) are considered within the broader context of other linked technological trends affecting automobility, with a particular focus on the shift to (electric powertrain) autonomous vehicles (AVs).

This chapter draws upon modelling of quantitative survey data from 1,426 Americans, which employed regression analysis to predict and understand variables linked to the preference for an AV over a human driver, percentage of trips taken by an AV, percentage of trips using dynamic ride-sharing (DRS) inside a shared autonomous vehicle (SAV), and factors affecting EV charging access in home and at work/school.

The findings show that full EV charging times significantly affect decisions for next household vehicle purchase. A lack of charging ability at home appears to be a significantly greater hindrance to respondents’ willingness to purchase full EVs than does a lack of charging ability at work. And home location choice impacts of AVs are not expected to be substantial. Considering future EV/AV ride-sharing (an important component of sustainable future mobility systems), DRS may ease congestion if SAV riders widely adopt DRS for work and school trips; however, sharing with strangers may not be popular in practice.

This chapter is useful to manufacturers and fleet operators for pricing and marketing decisions, and public transit authorities/providers can benefit from understanding evolving travel choices and land use patterns to craft equitable policies, and model future transportation demand to help plan services and infrastructure projects.

Apart from the challenges related to vehicle technology, the wide-scale deployment of autonomous vehicles (AVs) in cities is linked to unprecedented opportunities and unforeseen impacts. These refer to mobility conditions, infrastructure, land use, wider socio-economic factors, energy use and environmental and climate effects. AVs may affect all these in positive or negative ways, promoting or obstructing the promotion of specific aspects of sustainable urban development. An integrated planning framework is needed to maximise the positive impacts and mitigate the negative ones. The main obstacle in the process of developing such a framework is the absence of empirical data and experience from the implementation of this emerging technology. This chapter outlines the possible impacts of AVs and discusses their uncertainty and trade-offs in relation to sustainable urban development. The categorisation of impacts derives from the priorities of the UN Sustainable Development Goal (SDG) 11: Make cities and human settlements inclusive, safe, resilient, and sustainable. The chapter also highlights the lack of data for the development of an evidence-based planning approach and suggests relevant recommendations to planners. In contrast to the current lack of data, the future abundance of Big Data collected by autonomous road transport systems is discussed in the context of future urban planning purposes. Based on the above, the chapter concludes by stressing the importance of an integrated urban transport planning approach that ensures a positive contribution of AVs to sustainable urban development. Hence, it offers valuable recommendations for policymakers in a range of fields.

The purpose of this paper is to investigate problems in performing stable lane changes and to find a solution to reduce energy consumption of autonomous electric vehicles.

An optimization algorithm, model predictive control (MPC) and Karush–Kuhn–Tucker (KKT) conditions are adopted to resolve the problems of obtaining optimal lane time, tracking dynamic reference and energy-efficient allocation. In this paper, the dynamic constraints of vehicles during lane change are first established based on the longitudinal and lateral force coupling characteristics and the nominal reference trajectory. Then, by optimizing the lane change time, the yaw rate and lateral acceleration that connect with the lane change time are limed. Furthermore, to assure the dynamic properties of autonomous vehicles, the real system inputs under the restraints are obtained by using the MPC method. Based on the gained inputs and the efficient map of brushless direct-current in-wheel motors (BLDC IWMs), the nonlinear cost function which combines vehicle dynamic and energy consumption is given and the KKT-based method is adopted.

The effectiveness of the proposed control system is verified by numerical simulations. Consequently, the proposed control system can successfully achieve stable trajectory planning, which means that the yaw rate and longitudinal and lateral acceleration of vehicle are within stability boundaries, which accomplishes accurate tracking control and decreases obvious energy consumption.

This paper proposes a solution to simultaneously satisfy stable lane change maneuvering and reduction of energy consumption for autonomous electric vehicles. Different from previous path planning researches in which only the geometric constraints are involved, this paper considers vehicle dynamics, and stability boundaries are established in path planning to ensure the feasibility of the generated reference path.

This study aimed two objectives: The first objective was to explore carriers' intentions to use cargo electric vehicles (EVs) and the factors influencing these intentions in last-mile delivery (LMD). The other objective was to provide recommendations for policymakers and manufacturers to promote and customize cargo EVs to meet the requirements of carriers in the LMD sector.

In this study the authors constructed a research framework that adjusted and extended the original technology acceptance model (TAM). The proposed model combines eight psychological factors, including attitude, perceived usefulness, perceived ease of use, perceived risk, public engagement, face consciousness, financial incentive policy and carrier intention, in which four factors, namely attitude, perceived usefulness, perceived ease of use and intention, were obtained from the original TAM and the four remaining factors, namely perceived risk, public engagement, face consciousness and financial incentive policy, were added.

The results showed that psychological factors such as attitude, perceived ease of use, perceived risk, public engagement and face consciousness might affect carriers' intentions to use electric cargo vehicles in LMD service in Vietnamese cities. These results agree with the previous studies and confirm that attitude, perceived ease of use, perceived risk, public engagement and face consciousness might be important for shaping intention to use electric cargo vehicles in emerging markets.

This study has several limitations, first, the data were collected in Vietnam, a country with weak academic contributions. Therefore, these findings might not be generalizable to other areas. The authors expect to apply the same research framework to other countries to explore the similarities and differences across the countries. Second, the authors conducted the surveys in three cities; except for Hanoi, the other two cities are not really large markets in the LMD service sector. Third, the authors ignored the relationship between the demographic characteristics and electric cargo vehicles. Further studies should address this gap.

Based on the findings, manufacturers should ensure the high-quality performance of electric cargo vehicles in terms of extending driving range and shortening recharging time. Policymakers should develop the roadmaps for electric cargo vehicles, starting from switching from conventional cargo motorcycles to electric motorcycles. In addition, developing public charging infrastructure should be prioritized, which is the fundamental basis for operating electric cargo vehicles. Finally, manufacturers should research and develop a product that would improve the reputation of carriers because carriers with higher face consciousness are more likely to pursue brand-name and high-priced products in order to enhance their reputation.

This study contributes to the literature in two aspects: First, the authors investigated intentions to use electric cargo vehicles in LMD service, which is rare from other studies, and they further identified the psychological determinants of carriers' intentions. Second, the findings increase the knowledge of carriers' intentions and suggest implications for policymakers and manufacturers to promote the adoption of electric cargo vehicles in last-mile deliver service.

Connected and autonomous mobility may be an imminent game-changing reality, still in its embryonic form, that is set to disrupt a century-long ‘driver-centric’ status quo and recalibrate transport in unprecedented and possibly entirely unexpected ways. Autonomous vehicles (AVs) may have among others, a major impact on sustainability which in an era where concerns about the urgency and magnitude of climate change threats are voiced more and louder than ever before, needs to be a positive one for helping societies to enjoy liveable futures. This might not be an easy task to accomplish, however. This chapter, using a thematically organised narrative review approach, tries to give a well-rounded answer on whether driverless technology can yield sustainability benefits (or not) by looking at all three spheres of sustainability referring to environmental, economic and social implications. Agendas like motor traffic, air pollution, energy consumption, employment dynamics, inclusion, cybersecurity and privacy are all explored, and a conclusion is derived highlighting the need to package automation with connectivity, alternative fuelling and multimodality and building it around public transport (and to a lesser extent sharing service) provision. The road to make driverless transport genuinely sustainable is ‘bumpy’ and ‘uphill’ and requires the development of an appetite not for technology excellence per se, but rather for travel behaviour change. Achieving this needs serious strategic and coordinated multi-stakeholder efforts in terms of pro-active policy reform, user (and transport provider) education and training initiatives, infrastructure investment, business plan development, and living lab experimentation.

Modelling has been a mainstay of conventional planning support tools (PSTs) since the 1960s and is instrumental in transport and land use planning decision-making. Numerous studies have been conducted to model the potential impacts of emerging vehicle automation and sharing technologies. A systematic review of recent modelling studies of autonomous and shared vehicles in the research literature examines the extent of their contribution to ‘smart’ mobility knowledge. The findings suggest a limited knowledge base from which to support future planning. PSTs that can offer more pluralistic, discursive, and transparent methods in order to understand and proactively shape a transition to a planned urban future are also needed.

There are ethical, legal, social and economic arguments surrounding the subject of autonomous vehicles. This paper aims to discuss some of the arguments to communicate one of the current issues in the rising field of artificial intelligence.

Making use of widely available literature that the author has read and summarised showcasing her viewpoints, the author shows that technology is progressing every day. Artificial intelligence and machine learning are at the forefront of technological advancement today. The manufacture and innovation of new machines have revolutionised our lives and resulted in a world where we are becoming increasingly dependent on artificial intelligence.

Technology might appear to be getting out of hand, but it can be effectively used to transform lives and convenience.

From robotics to autonomous vehicles, countless technologies have and will continue to make the lives of individuals much easier. But, with these advancements also comes something called “future shock”.

Future shock is the state of being unable to keep up with rapid social or technological change. As a result, the topic of artificial intelligence, and thus autonomous cars, is highly debated.

The study will be of interest to researchers, academics and the public in general. It will encourage further thinking.

This is an original piece of writing informed by reading several current pieces. The study has not been submitted elsewhere.

The purpose of this paper is to analyse how start-ups with a clear sustainability focus collaborate with multiple actors at different levels to pursue business ideas and develop sustainable freight transport solutions.

This paper builds on a theoretical approach that includes three levels of analysis: the actor level (micro), business-network level (meso) and society and government level (macro). An embedded case study is used of a focal start-up aiming to innovate on networked platforms and electric and autonomous vehicles (EAVs).

Activities and resources are developed at the firm (micro), network (meso) and societal levels (macro), and all three levels need to be considered for a start-up, with a clear sustainability focus. Interaction within as well as between levels affects the innovation development, integration and implementation. The many-folded collaborations at the meso level serve as a locus for the integration of EAVs. The start-up’s networking activities with actors at meso and macro levels contribute to it gaining legitimacy in the transport system.

This paper focuses on the importance of collaboration in the context of developing innovative solutions for environmental sustainability and freight transport and provides a unique case of how a start-up company manages collaborations at the micro, meso and macro levels.

This paper aims to set out a vision of the advent of autonomous electric vehicles (AEV), piloted by artificial intelligence and serviced by other “intelligent” machines, a scenario that poses vast implications for business strategy in many industries.

Given the speed with which business leaders today must assess and react to the business risks and opportunities engendered by breakthrough technological change, their plans to navigate an autonomous electric vehicle-based transportation future can benefit from a scenario map to the roadblocks and the richest prospects.

Self-driving electric cars and trucks, which are expected to transform the transportation landscape over the next decade. A smart charging grid is a critical technology development.

Business opportunities to transform ground transport in areas such as operations and supply chain management are significant as well, particularly with unsupervised AEVs, which could slash labor costs and transport times.

AEVs are expected to free up more than 30 billion hours per year in the U.S. alone currently spent driving, sitting in traffic or searching for a parking space.

Offers a look at the technology evolution needed for the AEV transportation revolution.

With various challenges in the digital era, stakeholders are expressing growing interests in understanding the impact of emerging and disruptive technologies on freight transportation. This paper provides a systematic literature review of the current state of affairs as well as future trends and aims to support stakeholders' decision-making in logistics management in the era of disruptive technologies.

Several recent and representative articles from academic, industrial and governmental perspectives were investigated to set the scene for this research and to serve as a baseline for electing nine emerging technologies, which were then used to conduct a systematic literature review covering the literature within the area during the past twelve years.

3D printing, artificial intelligence, automated robots, autonomous vehicles, big data analytics, blockchain, drones, electric vehicles and the Internet of Things were identified as the emerging technologies. The current state of existing research and potential future opportunities were analyzed.

Since the potential literature body is almost impossible to fully cover, a tradeoff between the number of emerging technologies and the related literature reviewed has been performed. However, the paper provides a novel approach to select the emerging and disruptive technologies and a systematic literature review to fill the identified research gap in the related literature.

The research support various stakeholders to better capture the current status of and the future opportunities in freight transportation and gain a clearer understanding of the disruptive technologies as well as to guide them in how to deploy these initiatives in future decision-making.

By providing a systematic literature review on the trends, themes and research opportunities in the era of disruptive technologies, the papers bring about broad and comprehensive review on the impact of disruptive technologies on logistics and transportation as well as opportunities to support management decision support in the logistics industry.