MethOds and tools for comprehensive impact Assessment of the CCAM solutions for passengers and goods. D1.1: CCAM solutions review and gaps

Review of the state-of-the-art on Cooperative, Connected and Automated mobility use cases, scenarios, business models, Key Performance Indicators, impact evaluation methods, technologies, and user needs (for organisations & citizens)

No woman's land:Feminist approaches to the ride-hailing sector and digital labor platforms in India

In this dissertation, I investigate the concerns, issues and opportunities for platform labor reform with a focus on the ride-hailing sector using Bardzell (2010)’s feminist lens. The feminist viewpoint keeps the marginal user at the center committing to equity, diversity, identity, empowerment, and social justice to improve the work conditions of gig workers in the Global South. By conducting in-depth qualitative interviews with the different stakeholders of the ride-hailing sector, and analysing case studies, media coverage, policy papers, and research reports, I suggest guidelines for redesigning the digital labor platforms

No woman's land:Feminist approaches to the ride-hailing sector and digital labor platforms in India

In this dissertation, I investigate the concerns, issues and opportunities for platform labor reform with a focus on the ride-hailing sector using Bardzell (2010)’s feminist lens. The feminist viewpoint keeps the marginal user at the center committing to equity, diversity, identity, empowerment, and social justice to improve the work conditions of gig workers in the Global South. By conducting in-depth qualitative interviews with the different stakeholders of the ride-hailing sector, and analysing case studies, media coverage, policy papers, and research reports, I suggest guidelines for redesigning the digital labor platforms

The future of mobility impact of robotaxis on the european passenger transportation industry

Automation, connectivity, electrification, and shared mobility are the dominant trends transforming the passenger transportation industry. Together they form what is considered one of the most disruptive means of transportation of the future, the robotaxi. This master thesis explores the impact of robotaxis on the future of the passenger transportation industry, with particular attention to the usage perspectives and mobility behavior of consumers. The results are based on an exploratory analysis involving seven in-depth semi-structured expert interviews, a consumer survey, and existing literature. Usage perspectives were observed through a use case analysis that identified work-related commuting as the use case with the highest application potential. In the light of work-related commuting, the thesis revealed that robotaxis significantly reduce commuters’ value of time and display an attractive mobility alternative from a cost perspective. In addition, it is shown that in the next ten years, consumer preferences regarding consumers’ transportation choice significantly shift towards robotaxis. The research reveals that the industry’s most likely future state is characterized by the gradual introduction of robotaxis. Therefore, in five to ten years, robotaxis are used by early adopters and will impose significant changes in industry dynamics as competition increases and new revenue streams emerge. The results intend to enable industry players to target specific consumers, derive strategic implications, business models, and vehicle concepts. Further, they contribute to an objective scientific, political, and social discussion and serve as a basis for further research in the field of robotaxis.Automação, conectividade, eletrificação, e mobilidade partilhada são as tendências dominantes que têm transformado a indústria de transporte de passageiros. Juntos, formam um dos meios de transporte mais disruptivos, o robotáxi. Esta tese explora o impacto dos robotáxis no futuro desta indústria, focando-se nas perspetivas de utilização e no comportamento de mobilidade dos consumidores. Os resultados baseiam-se numa análise que inclui sete entrevistas feitas a peritos, um inquérito aos consumidores e na literatura existente. As perspetivas de utilização foram observadas através de uma análise de caso de uso que identificou as deslocações para o trabalho como o caso com maior potencial de aplicação. Revela-se que os robotáxis reduzem significativamente a perceção de tempo gasto nestas deslocações e constituem uma alternativa de mobilidade atrativa do ponto de vista monetário. Adicionalmente, mostra-se que, nos próximos dez anos, as preferências dos consumidores em relação à escolha de transporte mudarão significativamente havendo uma tendência para a adoção de robotáxis. Este estudo revela que o futuro da indústria será marcado pela introdução gradual de robotáxis. Assim, dentro de cinco a dez anos, os robotáxis serão utilizados pelos consumidores pioneiros na adoção e irão impor mudanças significativas na dinâmica da indústria à medida que a concorrência aumente e surjam novos fluxos de receitas. Os resultados do estudo pretendem permitir aos agentes desta indústria focar-se em consumidores específicos, retirar implicações estratégicas, modelos empresariais, e conceitos relacionados com veículos. Adicionalmente, contribuem para uma discussão científica, política e social e servem de base para mais investigação no campo dos robotáxis

Carpooling Liability?: Applying Tort Law Principles to the Joint Emergence of Self-Driving Automobiles and Transportation Network Companies

Self-driving automobiles have emerged as the future of vehicular travel, but this innovation is not developing in isolation. Simultaneously, the popularity of transportation network companies functioning as ride-hailing and ride-sharing services have altered traditional conceptions of personal transportation. Technology companies, conventional automakers, and start-up businesses each play significant roles in fundamentally transforming transportation methods. These transformations raise numerous liability questions. Specifically, the emergence of self-driving vehicles and transportation network companies create uncertainty for the application of tort law’s negligence standard. This Note addresses technological innovations in vehicular transportation and their accompanying legislative and regulatory developments. Then, this Note discusses the implications for vicarious liability for vehicle owners, duties of care for vehicle operators, and corresponding insurance regimes. This Note also considers theoretical justifications for tort concepts including enterprise liability. Accounting for the inevitable uncertainty in applying tort law to new invention, this Note proposes a strict and vicarious liability regime with corresponding no-fault automobile insurance

Trends in life cycle greenhouse gas emissions of future light duty electric vehicles

The majority of previous studies examining life cycle greenhouse gas (LCGHG) emissions of battery electric vehicles (BEVs) have focused on efficiency-oriented vehicle designs with limited battery capacities. However, two dominant trends in the US BEV market make these studies increasingly obsolete: sales show significant increases in battery capacity and attendant range and are increasingly dominated by large luxury or high-performance vehicles. In addition, an era of new use and ownership models may mean significant changes to vehicle utilization, and the carbon intensity of electricity is expected to decrease. Thus, the question is whether these trends significantly alter our expectations of future BEV LCGHG emissions. To answer this question, three archetypal vehicle designs for the year 2025 along with scenarios for increased range and different use models are simulated in an LCGHG model: an efficiency-oriented compact vehicle; a high performance luxury sedan; and a luxury sport utility vehicle. While production emissions are less than 10% of LCGHG emissions for today's gasoline vehicles, they account for about 40% for a BEV, and as much as two-thirds of a future BEV operated on a primarily renewable grid. Larger battery systems and low utilization do not outweigh expected reductions in emissions from electricity used for vehicle charging. These trends could be exacerbated by increasing BEV market shares for larger vehicles. However, larger battery systems could reduce per-mile emissions of BEVs in high mileage applications, like on-demand ride sharing or shared vehicle fleets, meaning that trends in use patterns may countervail those in BEV design

Knowledge Discovery and Data Mining for Shared Mobility and Connected and Automated Vehicle Applications

The rapid development of shared mobility and connected and automated vehicles (CAVs) has not only brought new intelligent transportation system (ITS) challenges with the new types of mobility, but also brought a huge opportunity to accelerate the connectivity and informatization of transportation systems, particularly when we consider all the new forms of data that is becoming available. The primary challenge is how to take advantage of the enormous amount of data to discover knowledge, build effective models, and develop impactful applications. With the theoretical and experimental progress being made over the last two decades, data mining and machine learning technologies have become key approaches for parsing data, understanding information, and making informed decisions, especially as the rise of deep learning algorithms bringing new levels of performance to the analysis of large datasets. The combination of data mining and ITS can greatly benefit research and advances in shared mobility and CAVs.This dissertation focuses on knowledge discovery and data mining for shared mobility and CAV applications. When considering big data associated with shared mobility operations and CAV research, data mining techniques can be customized with transportation knowledge to initially parse the data. Then machine learning methods can be used to model the parsed data to elicit hidden knowledge. Finally, the discovered knowledge and extracted information can help in the development of effective shared mobility and CAV applications to achieve the goals of a safer, faster, and more eco-friendly transportation systems.In this dissertation, there are four main sections that are addressed. First, new methodologies are introduced for extracting lane-level road features from rough crowdsourced GPS trajectories via data mining, which is subsequently used as the fundamental information for CAV applications. The proposed method results in decimeter level accuracy, which satisfies the positioning needs for many macroscopic and microscopic shared mobility and CAV applications. Second, macroscopic ride-hailing service big data has been analyzed for demand prediction, vehicle operation, and system efficiency monitoring. The proposed deep learning algorithms increase the ride-hailing demand prediction accuracy to 80% and can help the fleet dispatching system reduce 30% of vacant travel distance. Third, microscopic automated vehicle perception data has been analyzed for a real-time computer vision system that can be used for lane change behavior detection. The proposed deep learning design combines the residual neural network image input with time serious control data and reaches 95% of lane change behavior prediction accuracy. Last but not least, new ride sharing and CAV applications have been simulated in a behavior modeling framework to analyze the impact of mobility and energy consumption, which addresses key barriers by quantifying the transportation system-wide mobility, energy and behavior impacts from new mobility technologies using real-world data

Computational Transformation of the Public Sphere : Theories and Case Studies

This book is an edited collection of MA research paper on the digital revolution of the public and governance. It covers cyber governance in Finland, and the securitization of cyber security in Finland. It investigates the cases of Brexit, the 2016 US presidental election of Donald Trump, the 2017 presidential election of Volodymyr Zelensky, and Brexit. It examines the environmental concerns of climate change and greenwashing, and the impact of digital communication giving rise to the #MeToo and Incel movements. It considers how digitilization can serve to emancipate women through ride-sharing, and how it leads to the question of robot rights. It considers fake news and algorithmic governance with respect to case studies of the Chinese social credit system, the US FICO credit score, along with Facebook, Twitter, Cambridge Analytica and the European effort to regulate and protect data usage.Non peer reviewe

Computational Transformation of the Public Sphere: Theories and Cases

This book is an edited collection of original research papers on the digital revolution of the public and governance. It covers cyber governance in Finland, and the securitization of cyber security in Finland. It investigates the cases of Brexit, the 2016 US presidential election of Donald Trump, the 2017 presidential election of Volodymyr Zelensky, and Brexit. It examines the environmental concerns of climate change and greenwashing, and the impact of digital communication giving rise to the #MeToo and Incel movements. It considers how digitilization can serve to emancipate women through ride-sharing, and how it leads to the question of robot rights. It considers fake news and algorithmic governance with respect to case studies of the Chinese social credit system, the US FICO credit score, along with Facebook, Twitter, Cambridge Analytica and the European effort to regulate and protect data usage