Towards a Smart World: Hazard Levels for Monitoring of Autonomous Vehicles’ Swarms

This work explores the creation of quantifiable indices to monitor the safe operations and movement of families of autonomous vehicles (AV) in restricted highway-like environments. Specifically, this work will explore the creation of ad-hoc rules for monitoring lateral and longitudinal movement of multiple AVs based on behavior that mimics swarm and flock movement (or particle swarm motion). This exploratory work is sponsored by the Emerging Leader Seed grant program of the Mineta Transportation Institute and aims at investigating feasibility of adaptation of particle swarm motion to control families of autonomous vehicles. Specifically, it explores how particle swarm approaches can be augmented by setting safety thresholds and fail-safe mechanisms to avoid collisions in off-nominal situations. This concept leverages the integration of the notion of hazard and danger levels (i.e., measures of the “closeness” to a given accident scenario, typically used in robotics) with the concept of safety distance and separation/collision avoidance for ground vehicles. A draft of implementation of four hazard level functions indicates that safety thresholds can be set up to autonomously trigger lateral and longitudinal motion control based on three main rules respectively based on speed, heading, and braking distance to steer the vehicle and maintain separation/avoid collisions in families of autonomous vehicles. The concepts here presented can be used to set up a high-level framework for developing artificial intelligence algorithms that can serve as back-up to standard machine learning approaches for control and steering of autonomous vehicles. Although there are no constraints on the concept’s implementation, it is expected that this work would be most relevant for highly-automated Level 4 and Level 5 vehicles, capable of communicating with each other and in the presence of a monitoring ground control center for the operations of the swarm

Analysis of Disengagements in Semi-Autonomous Vehicles: Drivers’ Takeover Performance and Operational Implications

This report analyzes the reactions of human drivers placed in simulated Autonomous Technology disengagement scenarios. The study was executed in a human-in-the-loop setting, within a high-fidelity integrated car simulator capable of handling both manual and autonomous driving. A population of 40 individuals was tested, with metrics for control takeover quantification given by: i) response times (considering inputs of steering, throttle, and braking); ii) vehicle drift from the lane centerline after takeover as well as overall (integral) drift over an S-turn curve compared to a baseline obtained in manual driving; and iii) accuracy metrics to quantify human factors associated with the simulation experiment. Independent variables considered for the study were the age of the driver, the speed at the time of disengagement, and the time at which the disengagement occurred (i.e., how long automation was engaged for). The study shows that changes in the vehicle speed significantly affect all the variables investigated, pointing to the importance of setting up thresholds for maximum operational speed of vehicles driven in autonomous mode when the human driver serves as back-up. The results shows that the establishment of an operational threshold could reduce the maximum drift and lead to better control during takeover, perhaps warranting a lower speed limit than conventional vehicles. With regards to the age variable, neither the response times analysis nor the drift analysis provide support for any claim to limit the age of drivers of semi-autonomous vehicles

Human capital, technology intensity and growth in a regional context

This paper contributes to the vast literature on the regional application of endogenous growth theory. A well-known feature of capitalist growth and development is the vast and persistent divergence in per capita income growth between regions. These differences have been explained theoretically and empirically using neoclassical approaches emphasising increasing returns at a regional level, with reference, for example, to the development of industrial districts. The new economics of urban and regional growth look at the \u2018local\u2019 dimension focussing on the role of the so-called knowledge economy as an explanation for uneven development across regions. Within this heterogeneity, the operation of human capital and knowledge spillovers play roles in differentiating growth rates. The study of the concentration of a specific mix of economic activities and human capital, with a \u2018fine grain\u2019 focus at the local level, is a useful tool to understand growth and spatial differentials. In this study, we develop an empirical analysis of the pattern of growth in the Veneto region, focusing mainly on the role played by human capital employed in sectors with different technological intensities. To do so, we built up an original dataset by merging data available at a very local level (Local Labour Systems-LLS), which was produced by the National Institute of Statistics, with our elaborations on data from an employee-employer dataset made available by the Local Labour Agency (Veneto Lavoro). The latter dataset included all employment spells in the Veneto region. Our new dataset allows both definition of the human capital content of every worker and classification of firms according to their technological intensity. This dataset is used to estimate growth equations for the cross-section of the Venetian LLSs and to test the validity of different growth models. The results underline how growth in the Veneto region is positively affected by human capital employed not in high to medium-high technology industries, but in medium to medium-low ones

Fast method for the determination of short-chain-length polyhydroxyalkanoates (scl-PHAs) in bacterial samples by In Vial-Thermolysis (IVT)

none8siA new method based on the GC–MS analysis of thermolysis products obtained by treating bacterial samples at a high temperature (above 270 C) has been developed. This method, here named “In-Vial- Thermolysis” (IVT), allowed for the simultaneous determination of short-chain-length polyhydrox- yalkanoates (scl-PHA) content and composition. The method was applied to both single strains and microbial mixed cultures (MMC) fed with different carbon sources. The IVT procedure provided similar analytical performances compared to previous Py-GC–MS and Py- GC-FID methods, suggesting a similar application for PHA quantitation in bacterial cells. Results from the IVT procedure and the traditional methanolysis method were compared; the correlation between the two datasets was fit for the purpose, giving a R2 of 0.975. In search of further simplification, the rationale of IVT was exploited for the development of a “field method” based on the titration of thermolyzed samples with sodium hydrogen carbonate to quantify PHA inside bacterial cells. The accuracy of the IVT method was fit for the purpose. These results lead to the possibility for the on-line measurement of PHA productivity. Moreover, they allow for the fast and inexpensive quantification/characterization of PHA for biotechnological process control, as well as investigation over various bacterial communities and/or feeding strategies.mixedF. Abbondanzi; G. Biscaro; G. Carvalho; L. Favaro; P. Lemos; M. Paglione; C. Samorì; C. TorriF. Abbondanzi; G. Biscaro; G. Carvalho; L. Favaro; P. Lemos; M. Paglione; C. Samorì; C. Torr

Influência da secagem da polpa na composição centesimal de tortas de macaúba do Pantanal de Mato Grosso do Sul.

Objetivou-se, neste trabalho, avaliar os efeitos de diferentes processos de secagem dos frutos na composição centesimal de torta da polpa da macaúba proveniente da região do Pantanal de Corumbá, Mato Grosso do Sul