Understanding acceptance of Autonomous Mobility Services using statistical and deep learning approaches

The emergence of vehicle automation and its subsequent growth has led to new transport service offerings, generally known as Autonomous Mobility Services (AMS), that have the potential to facilitate or even replace human-operated vehicles. AMS contains different forms of potential mobility options which may contradict current transport modal concepts in terms of functionalities. For example, an autonomous shuttle bus which is a form of autonomous transit may serve similarly as an autonomous taxi/robo-taxi in terms of functionalities, coinciding with the concept of Shared Autonomous Mobility Services (SAMS). Even if the functionalities or operational principles are different, peoples' perceptions of sharing rides in any of these services may be alike. Apart from these confusions in functionalities mentioned above, peoples' attitudes and acceptance of AMS, once it's implemented in any form in the public road environment, remains a significant research aspect. To address these issues, this thesis tried to first clearly distinguish different types of AMS. Second, it tried to assemble the progress till now in acceptance-related research of AMS while reviewing the previous study approaches, outcomes, policy implications, and future research directions. Third, this study attempted to understand the acceptance of AMS using statistical and deep learning approaches leveraging both survey and social media data. Fourth, this study tried to present the consequent applicabilities and limitations of using both types of data sources for autonomous vehicle acceptance research. Eventually, this thesis intends to present an overall idea of the AMS acceptance research with future directions leveraging both data sources in an individualistic or combined manner.Includes bibliographical references

High-speed civil transport flight- and propulsion-control technological issues

Technology advances required in the flight and propulsion control system disciplines to develop a high speed civil transport (HSCT) are identified. The mission and requirements of the transport and major flight and propulsion control technology issues are discussed. Each issue is ranked and, for each issue, a plan for technology readiness is given. Certain features are unique and dominate control system design. These features include the high temperature environment, large flexible aircraft, control-configured empennage, minimizing control margins, and high availability and excellent maintainability. The failure to resolve most high-priority issues can prevent the transport from achieving its goals. The flow-time for hardware may require stimulus, since market forces may be insufficient to ensure timely production. Flight and propulsion control technology will contribute to takeoff gross weight reduction. Similar technology advances are necessary also to ensure flight safety for the transport. The certification basis of the HSCT must be negotiated between airplane manufacturers and government regulators. Efficient, quality design of the transport will require an integrated set of design tools that support the entire engineering design team

How machine learning informs ride-hailing services: A survey

In recent years, online ride-hailing services have emerged as an important component of urban transportation system, which not only provide significant ease for residents’ travel activities, but also shape new travel behavior and diversify urban mobility patterns. This study provides a thorough review of machine-learning-based methodologies for on-demand ride-hailing services. The importance of on-demand ride-hailing services in the spatio-temporal dynamics of urban traffic is first highlighted, with machine-learning-based macro-level ride-hailing research demonstrating its value in guiding the design, planning, operation, and control of urban intelligent transportation systems. Then, the research on travel behavior from the perspective of individual mobility patterns, including carpooling behavior and modal choice behavior, is summarized. In addition, existing studies on order matching and vehicle dispatching strategies, which are among the most important components of on-line ride-hailing systems, are collected and summarized. Finally, some of the critical challenges and opportunities in ride-hailing services are discussed

Collaborative Consumption as a Source of Market Disruption

The concept of collaborative consumption has been developed in consumer studies to define new consumption opportunities which are facilitated by information systems. Accordingly, novel services such as the ridesharing service Uber, for transport, and the hospitality-brokering service Airbnb, for accommodation, successfully employ collaboration in consumption and provide consumers with novel types of access to services. Yet while the identification of this new characteristic of consumption is of great merit, less attention has been paid in consumer studies to how it challenges existing market arrangements. It is against this background that this article examines collaborative consumption as a source of market disruption. The article applies the concept to the empirical case of a pilot scheme in collaborative public transport (Kutsuplus), which essentially consisted of a taxi-like bus service in Helsinki, Finland. It argues that collaborative consumption may tend to contribute premium rather than standard quality in public services, which is apt to disrupt both public and private service markets. The analysis further affirms that the concept of collaborative consumption is well suited to the assessment of novel services and their disruptive characteristics.Peer reviewe

Exploring Concepts of Operations for On-Demand Passenger Air Transportation

In recent years, a surge of interest in "flying cars" for city commutes has led to rapid development of new technologies to help make them and similar on-demand mobility platforms a reality. To this end, this paper provides analyses of the stakeholders involved, their proposed operational concepts, and the hazards and regulations that must be addressed. Three system architectures emerged from the analyses, ranging from conventional air taxi to revolutionary fully autonomous aircraft operations, each with vehicle safety functions allocated differently between humans and machines. Advancements for enabling technologies such as distributed electric propulsion and artificial intelligence have had major investments and initial experimental success, but may be some years away from being deployed for on-demand passenger air transportation at scale

Data enabling digital ecosystem for sustainable shared electric mobility-as-a-service in smart cities-an innovative business model perspective

Increase in urbanization drives the need for municipalities to make mobility more efficient, both to address climate goals as well as creating a smart living environment for citizens, with less noise congestion, and pollution. As vehicles are being electrified, further advances will be needed to meet social, environmental, and economic sustainability targets, and a more efficient use of vehicles and public transport is central in this endeavor. Accordingly, Electric Mobility as a Service (eMaaS) has developed as a concept with the potential to increase sustainability mobility in cities and been designated as a phenomenon with potential to radically change how people move in the future. But presently there is the lack of a common business model that supports complex integration of all actors, digital technologies, and infrastructures involved in the eMaaS business ecosystem. This study aims to support the further development of eMaaS by providing a state of the art of eMaaS and further proposes a digital ecosystem as a business model for eMaaS sharing in smart cities. Accordingly, a systematic literature review was adopted grounded on secondary data from the literature to offers a new approach to urban mobility and demonstrate the suitability of the eMaaS concept in smart communities. The digital ecosystem is designed based on system design approach. Findings from this study provides a sustainable policy perspective, discusses the challenges and opportunities towards the development of eMaaS and its impact on electrification of vehicles. Overall, findings from this study considers the role of electric vehicles as part of the mobility sharing economy. Recommendations from this study provides designs and strategies for eMaaS, the interrelations between eMobility and other everyday practices, strategically highlighting the positive benefits of eMaaS and broader policies to limit private car usage in cities.publishedVersio

Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning

Autonomous Mobility-on-Demand (AMoD) systems are an evolving mode of transportation in which a centrally coordinated fleet of self-driving vehicles dynamically serves travel requests. The control of these systems is typically formulated as a large network optimization problem, and reinforcement learning (RL) has recently emerged as a promising approach to solve the open challenges in this space. Recent centralized RL approaches focus on learning from online data, ignoring the per-sample-cost of interactions within real-world transportation systems. To address these limitations, we propose to formalize the control of AMoD systems through the lens of offline reinforcement learning and learn effective control strategies using solely offline data, which is readily available to current mobility operators. We further investigate design decisions and provide empirical evidence based on data from real-world mobility systems showing how offline learning allows to recover AMoD control policies that (i) exhibit performance on par with online methods, (ii) allow for sample-efficient online fine-tuning and (iii) eliminate the need for complex simulation environments. Crucially, this paper demonstrates that offline RL is a promising paradigm for the application of RL-based solutions within economically-critical systems, such as mobility systems