Mobility and Energy Impacts of Shared Automated Vehicles: a Review of Recent Literature

The purpose of this review is to present findings from recent research on Shared automated vehicles (SAV) impacts on mobility and energy.While the literature on potential SAV impacts on travel behavior and the environment is still developing, researchers have suggested that SAVs could reduce transportation costs and incur minimal increases in total trip time due to efficient routing to support pooling. Researchers also speculate that SAVs would result in a 55% reduction in energy use and ~ 90% reduction in greenhouse gas (GHG) emissions.SAV impacts on mobility and energy are uncertain. Researchers should carefully track SAV technology developments and adjust previous model assumptions based on real-world data to produce better impact estimates. SAVs could prove to be a next technological advancement that reshapes the transportation system by providing a safer, efficient, and less costly travel alternative

SLR - Análisis del Aprendizaje Basado en Juegos Serios en las Prácticas de los Estudios de Ingeniería

Este trabajo se trata de un Análisis Sistemático de la Literatura del uso de los juegos serios en los estudios de ingeniería.15 página

Mobility on Demand in the United States

The growth of shared mobility services and enabling technologies, such as smartphone apps, is contributing to the commodification and aggregation of transportation services. This chapter reviews terms and definitions related to Mobility on Demand (MOD) and Mobility as a Service (MaaS), the mobility marketplace, stakeholders, and enablers. This chapter also reviews the U.S. Department of Transportation’s MOD Sandbox Program, including common opportunities and challenges, partnerships, and case studies for employing on-demand mobility pilots and programs. The chapter concludes with a discussion of vehicle automation and on-demand mobility including pilot projects and the potential transformative impacts of shared automated vehicles on parking, land use, and the built environment

A multi-decade record of high quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID

Empowering production workers with digitally facilitated knowledge processes--a conceptual framework

Recent digital advancements, including social software, mobile technologies and augmented reality, offer promising opportunities to empower knowledge workers in their production environment by leveraging their knowledge processes, decision-making skills and social interaction practices. This paper proposes a conceptual framework for empowering workers in industrial production environments with digitally facilitated knowledge management processes. The framework explores four concrete facets of digital advancements that apply to a wide range of knowledge processes and production strategies in manufacturing companies. Each of these advancements are capable of supporting one specific facet of the individual knowledge management processes of workers; knowledge transfer, discovery, acquisition and sharing.The study contributes to the production research community by aligning emerging digital technologies and current trends in advanced manufacturing environments to benefit workers and improve job satisfaction, efficiency and productivity.The paper also contains suggestions about developing innovative solutions for production environments that support workers with digital technologies for flexible production

A Value-Sensitive Design Approach to Intelligent Agents

This chapter proposed a novel design methodology called Value-Sensitive Design and its potential application to the field of artificial intelligence research and design. It discusses the imperatives in adopting a design philosophy that embeds values into the design of artificial agents at the early stages of AI development. Because of the high risk stakes in the unmitigated design of artificial agents, this chapter proposes that even though VSD may turn out to be a less-than-optimal design methodology, it currently provides a framework that has the potential to embed stakeholder values and incorporate current design methods. The reader should begin to take away the importance of a proactive design approach to intelligent agents

Exploration using an information-based reaction-diffusion process

In this paper, a novel solution for autonomous robotic exploration is proposed. We model the distribution of information in an unknown environment as an unsteady diffiusion process, which can be an appropriate mathematical for- mulation and analogy for expanding, time- varying, and dynamic environments. This in- formation distribution map is the solution of the diffusion process partial diffierential equa- tion, and is regressed from sensor data as a Gaussian Process. Optimization of the pro- cess parameters leads to an optimal frontier map which describes regions of interest for fur- ther exploration. Since the presented approach considers a continuous model of the environ- ment, it can be used to plan smooth exploration paths exploiting the structural dependencies of the environment whilst handling sparse sensor measurements. The performance of the ap- proach is evaluated through simulation results in the well-known Freiburg and Cave maps