An Agent-based Modelling Framework for Driving Policy Learning in Connected and Autonomous Vehicles

Due to the complexity of the natural world, a programmer cannot foresee all possible situations, a connected and autonomous vehicle (CAV) will face during its operation, and hence, CAVs will need to learn to make decisions autonomously. Due to the sensing of its surroundings and information exchanged with other vehicles and road infrastructure, a CAV will have access to large amounts of useful data. While different control algorithms have been proposed for CAVs, the benefits brought about by connectedness of autonomous vehicles to other vehicles and to the infrastructure, and its implications on policy learning has not been investigated in literature. This paper investigates a data driven driving policy learning framework through an agent-based modelling approaches. The contributions of the paper are two-fold. A dynamic programming framework is proposed for in-vehicle policy learning with and without connectivity to neighboring vehicles. The simulation results indicate that while a CAV can learn to make autonomous decisions, vehicle-to-vehicle (V2V) communication of information improves this capability. Furthermore, to overcome the limitations of sensing in a CAV, the paper proposes a novel concept for infrastructure-led policy learning and communication with autonomous vehicles. In infrastructure-led policy learning, road-side infrastructure senses and captures successful vehicle maneuvers and learns an optimal policy from those temporal sequences, and when a vehicle approaches the road-side unit, the policy is communicated to the CAV. Deep-imitation learning methodology is proposed to develop such an infrastructure-led policy learning framework

Testing a gravity-based accessibility instrument to engage stakeholders into integrated LUT planning

The paper starts from the concern that while there is a large body of literature focusing on the theoretical definitions and measurements of accessibility, the extent to which such measures are used in planning practice is less clear. Previous reviews of accessibility instruments have in fact identified a gap between the clear theoretical assumptions and the infrequent applications of accessibility instruments in spatial and transport planning. In this paper we present the results of a structured-workshop involving private and public stakeholders to test usability of gravity-based accessibility measures (GraBaM) to assess integrated land-use and transport policies. The research is part of the COST Action TU1002 “Accessibility Instruments for Planning Practice” during which different accessibility instruments where tested for different case studies. Here we report on the empirical case study of Rome

The learning process of accessibility instrument developers: Testing the tools in planning practice

Many planning support tools have recently been developed aimed at measuring and mod- elling accessibility (Accessibility Instrument or AI). The main difficulty for tool developers is designing an AI that is at the same time technically rigorous and usable in practice. Measuring accessibility is indeed a complex task, and AI outputs are difficult to communi- cate to target end-users, in particular, because these users are professionals from several disciplines with different languages and areas of expertise, such as urban geographers, spa- tial planners, transport planners, and budgeting professionals. In addition to this, AI devel- opers seem to have little awareness of the needs of AI end-users, which in turn tend to have limited ability for using these tools. Against this complex background, our research focuses on the viewpoint of AI developers, with two aims: (1) to provide insights into how AI devel- opers perceive their tools and (2) to understand how their perceptions might change after testing their AI with end-users. With this in mind, an analysis of 15 case studies was per- formed: groups of end-users tested different AI in structured workshops. Before and after the workshops, two questionnaires explored the AI developers’ perceptions on the tools and their usability. The paper demonstrates that the workshops with end-users were crit- ical for developers to appreciate the importance of specific characteristics the tool should have, namely practical relevance, flexibility, and ease of use. The study provides evidence that AI developers were prone to change their perceptions about AI after interacting directly with end-users

Board Walk – January 2020

[No abstract available

DNA Methylation Analysis Validates Organoids as a Viable Model for Studying Human Intestinal Aging.

Background & aimsThe epithelia of the intestine and colon turn over rapidly and are maintained by adult stem cells at the base of crypts. Although the small intestine and colon have distinct, well-characterized physiological functions, it remains unclear if there are fundamental regional differences in stem cell behavior or region-dependent degenerative changes during aging. Mesenchyme-free organoids provide useful tools for investigating intestinal stem cell biology in vitro and have started to be used for investigating age-related changes in stem cell function. However, it is unknown whether organoids maintain hallmarks of age in the absence of an aging niche. We tested whether stem cell-enriched organoids preserved the DNA methylation-based aging profiles associated with the tissues and crypts from which they were derived.MethodsTo address this, we used standard human methylation arrays and the human epigenetic clock as a biomarker of age to analyze in vitro-derived, 3-dimensional, stem cell-enriched intestinal organoids.ResultsWe found that human stem cell-enriched organoids maintained segmental differences in methylation patterns and that age, as measured by the epigenetic clock, also was maintained in vitro. Surprisingly, we found that stem cell-enriched organoids derived from the small intestine showed striking epigenetic age reduction relative to organoids derived from colon.ConclusionsOur data validate the use of organoids as a model for studying human intestinal aging and introduce methods that can be used when modeling aging or age-onset diseases in vitro

Urban Form and Sustainability: the Case Study of Rome

This paper investigates the relation between sustainability and urban form. To this aim a system of Land-Use and Transport Interactions (LUTI) models has been designed and applied to the metropolitan area of Rome, to understand the interdependence of key variables such as travel behavior, transport supply, property values, jobs and residential location. The models represent the behavior of both dwellers and transport users and how they react to changing conditions. A system of assessment indicators has been defined to systematically test and compare alternative scenarios of urban form and to evaluate to what extent different locations and density distributions of activities achieve sustainability in terms of transport performances, social and environmental impacts

Point-free Ultrametric Spaces and the Category of Fuzzy Subsets

Some attempts to establish a link between point-free geometry and the categorical approach to fuzzy set theory is exposed. In fact, it is possible to find functors between the category of fuzzy sets as defined by Höhle in [4] and a category whose objects are the pointless ultrametric spaces

Global and local conservation of mass, momentum and kinetic energy in the simulation of compressible flow

The spatial discretization of convective terms in compressible flow equations is studied from an abstract viewpoint, for finite-difference methods and finite-volume type formulations with cell-centered numerical fluxes. General conditions are sought for the local and global conservation of primary (mass and momentum) and secondary (kinetic energy) invariants on Cartesian meshes. The analysis, based on a matrix approach, shows that sharp criteria for global and local conservation can be obtained and that in many cases these two concepts are equivalent. Explicit numerical fluxes are derived in all finite-difference formulations for which global conservation is guaranteed, even for non-uniform Cartesian meshes. The treatment reveals also an intimate relation between conservative finite-difference formulations and cell-centered finite-volume type approaches. This analogy suggests the design of wider classes of finite-difference discretizations locally preserving primary and secondary invariants