Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.

Incorporating weather into regionwide safety planning prediction models

Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.

Thermal studies of D.C. traction motors

This paper describes a thorough thermal study on a fleet of DC traction motors which were found to suffer from overheating after 3 years of full operation. Overheating of these traction motors is attributed partly because of the higher than expected number of starts and stops between train terminals. Another probable cause of overheating is the design of the traction motor and/or its control strategy. According to the motor manufacturer, a current shunt is permanently connected across the motor field winding. Hence, some of the armature current is bypassed into the current shunt. The motor then runs above its rated speed in the field weakening mode. In this study, a finite difference model has been developed to simulate the temperature profile at different parts inside the traction motor. In order to validate the simulation result, an empty vehicle loaded with drums of water was also used to simulate the full pay-load of a light rail vehicle experimentally. The authors report that the simulation results agree reasonably well with experimental data, and it is likely that the armature of the traction motor will run cooler if its field shunt is disconnected at low speeds

Ownership structure and business evaluation practices in family SMEs : evidence from empirical research in Italy

This paper presents early results from a pilot project which aims to investigate the relationship between proprietary structure of small and medium- sized Italian family firms and their owners’ orientation towards a “business evaluation process”. Evidence from many studies point out the importance of family business in a worldwide economic environment: in Italy 93% of the businesses are represented by family firms; 98% of them have less than 50 employees (Italian Association of Family Firms, 2004) so we judged family SMEs as a relevant field of investigation. In this study we assume a broad definition of family business as “a firm whose control (50% of shares or voting rights) is closely held by the members of the same family” (Corbetta,1995). “Business evaluation process” is intended here both as “continuous evaluation process” (which is the expression of a well developed managerial attitude) or as an “immediate valuation” (i.e. in the case of new shareholder’s entrance, share exchange among siblings, etc). We set two hypotheses to be tested in this paper: the first is “quantitative” and aims to verify whether the number of owners (independent variable) in a family firm is positively correlated to the business evaluation process. If a family firm is led by only one subject, it is more likely that personal values, culture and feelings may affect his choices more than “purely economic opportunities”; so there is less concern about monitoring economic performance or about the economic value of the firm. As the shareholders’ number increases, economic aspects in managing the firm grow in importance over the personal values and "value orientation" acquires a central role. The second hypothesis investigates if and to what extent the presence of “non- family members” among the owners affects their orientation to the business evaluation process. The “Cramer’s V” test has been used to test the hypotheses; both were not confirmed from these early results; next steps will lead to make an inferential analysis on a representative sample of the population.

Senator Elizabeth Warren fights the White House over the secret Trans-Pacific Partnership #TPP #TPPA

In his visit to the G20 in Brisbane, President Barack Obama sought to promote his ambitious Pacific Rim trade agreement — the Trans-Pacific Partnership (TPP). He told an audience at the University of Queensland: We’ll keep leading the effort to realize the Trans-Pacific Partnership to lower barriers, open markets, export goods, and create good jobs for our people. But with the 12 countries of the TPP making up nearly 40 percent of the global economy, this is also about something bigger. It is our chance to put in place new, high standards for trade in the 21st century that uphold our values. So, for example, we are pushing new standards in this trade agreement, requiring countries that participate to protect their workers better and to protect the environment better, and protect intellectual property that unleashes innovation, and baseline standards to ensure transparency and rule of law.