Potential Effectiveness of Bicycle-Automatic Emergency Braking using the Washtenaw Area Transportation Study Data Set

2021 ◽  
pp. 036119812110013
Author(s):  
Samantha H. Haus ◽  
Ryan M. Anderson ◽  
Rini Sherony ◽  
Hampton C. Gabler
Keyword(s):  
United States ◽  
The United States ◽  
Study Data ◽  
Related Factors ◽  
General Estimate ◽  
Data Set ◽  
Potential Effectiveness ◽  
The Road ◽  
Emergency Braking ◽  
Estimate System

In the United States, fatalities from vehicle–bicycle crashes have been increasing since 2010. A total of 857 cyclists were struck and killed in 2018 which is an increase from 623 fatalities in 2010. One promising countermeasure is Automatic Emergency Braking (AEB), which can help prevent and/or mitigate many vehicle–bicycle crashes. AEB is a vehicle-based system that can detect and mitigate an impending crash. The goal of this study was to elucidate U.S. vehicle–bicycle crashes and examine related factors to estimate AEB effectiveness. This study used a unique in-depth vehicle–bicycle crash study dataset collected under the collaboration of the Washtenaw Area Transportation Study (WATS) and the Toyota Collaborative Research Center conducted in southeast Michigan from 2011 to 2013. The WATS database provides in-depth investigations of vehicle–bicycle crashes in the United States. The characteristics of the WATS vehicle–bicycle crashes were validated against the Fatality Analysis Reporting System and the General Estimate System. The WATS database cases were examined to estimate the potential effectiveness of AEB to prevent or mitigate vehicle–bicycle collisions. In 60% of the WATS cases, cyclists were in the road for more than 1 s before impact. Assuming that a hypothetical AEB system requires a minimum of 1 s for detection and brake activation, these collisions would potentially be avoided or mitigated. However, for the remaining cases with less than 1 s of time to react (40% of cases), that AEB system would be challenged to avoid or mitigate the collision.

Investigating Effect of Driver-, Vehicle-, and Road-Related Factors on Location-Specific Crashes with Naturalistic Driving Data

2019 ◽  
Vol 2673 (6) ◽  
pp. 46-56 ◽  
Author(s):  
Grace Ashley ◽  
Osama A. Osman ◽  
Sherif Ishak ◽  
Julius Codjoe
Keyword(s):  
United States ◽  
Machine Learning ◽  
Traffic Accidents ◽  
The United States ◽  
Crash Risk ◽  
Related Factors ◽  
Data Set ◽  
Intersection Safety ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving

According to NHTSA, traffic accidents cost the United States billions of U.S. dollars each year. Intersection accidents alone accounted for 23% of the 32,675 motor crash deaths in 2014. With the advent of the largest naturalistic driving data set in the United States collected by the SHRP2 Naturalistic Driving Study project, this study performs a crash-only analysis to identify driver-, vehicle-, and roadway-related factors that affect the driving risk at different location types using a machine learning tool. The study then analyzes the most important factors obtained from the machine learning analysis to identify how they affect crash risk. The results, in order of importance of variables, were driver behavior, locality, lane occupied, alignment, and through travel lanes. Also, drivers who violated traffic signals were four times more likely to be involved in a crash than drivers who did not. Those who violated stop signs were two times more likely to be involved in crashes than those who did not. Drivers performing visual-manual (VM) tasks at uncontrolled intersections were 2.7 times more likely to be involved in crashes than those who did not engage in these tasks. At nonintersections, drivers who performed VM tasks were 3.4 times more likely to be involved in crashes than drivers who did not. These findings add to the evidence that the establishment of safety awareness programs geared toward intersection safety is imperative.

scholarly journals Altitude and risk of sudden unexpected infant death in the United States

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Richard Johnston ◽  
Xiaohan Yan ◽  
Tatiana M. Anderson ◽  
Edwin A. Mitchell
Keyword(s):  
United States ◽  
Logistic Regression ◽  
Infant Death ◽  
The United States ◽  
Sudden Infant ◽  
Data Set ◽  
Live Births ◽  
Sudden Unexpected Infant Death ◽  
Increased Risk ◽  
Unexpected Infant Death

AbstractThe effect of altitude on the risk of sudden infant death syndrome (SIDS) has been reported previously, but with conflicting findings. We aimed to examine whether the risk of sudden unexpected infant death (SUID) varies with altitude in the United States. Data from the Centers for Disease Control and Prevention (CDC)’s Cohort Linked Birth/Infant Death Data Set for births between 2005 and 2010 were examined. County of birth was used to estimate altitude. Logistic regression and Generalized Additive Model (GAM) were used, adjusting for year, mother’s race, Hispanic origin, marital status, age, education and smoking, father’s age and race, number of prenatal visits, plurality, live birth order, and infant’s sex, birthweight and gestation. There were 25,305,778 live births over the 6-year study period. The total number of deaths from SUID in this period were 23,673 (rate = 0.94/1000 live births). In the logistic regression model there was a small, but statistically significant, increased risk of SUID associated with birth at > 8000 feet compared with < 6000 feet (aOR = 1.93; 95% CI 1.00–3.71). The GAM showed a similar increased risk over 8000 feet, but this was not statistically significant. Only 9245 (0.037%) of mothers gave birth at > 8000 feet during the study period and 10 deaths (0.042%) were attributed to SUID. The number of SUID deaths at this altitude in the United States is very small (10 deaths in 6 years).

C. Sharon Advisor Dov Weisglass, Remarks on Relations with the United States, Disengagement, the Road Map, and the Possibilities of a Palestinian State, Tel Aviv, October 2004 (excerpts)

2005 ◽  
Vol 34 (2) ◽  
pp. 203-207
Keyword(s):  
United States ◽  
National Security ◽  
Full Text ◽  
Prime Minister ◽  
The United States ◽  
Sharp Contrast ◽  
Tel Aviv ◽  
The Road ◽  
Road Map ◽  
The Relationship

Ha'Aretz's lengthy interview with Dov Weisglass, Prime Minister Ariel Sharon's ““point man”” with Washington and probably his closest advisor, was conducted by Ari Shavit and published first in excerpts and two days later in its entirety. In addition to bringing into sharp contrast the contradiction between Israel's declaratory policies and assurances and its actual policies and intentions——and in so doing eliciting a swift ““clarification”” from the Prime Minister's Office——the interview also conveys a sense of the intimacy and easy camaraderie that characterizes U.S.-Israeli interactions. The full text is available at www.haaretz.com. Tell me about the dynamics of the relationship between you [and U.S. national security advisor Condoleezza Rice], and whether it's an unusual relationship.

scholarly journals Development of a semi-parametric PAR (Photosynthetically Active Radiation) partitioning model for the United States, version 1.0

2014 ◽  
Vol 7 (5) ◽  
pp. 2477-2484 ◽  
Author(s):  
J. C. Kathilankal ◽  
T. L. O'Halloran ◽  
A. Schmidt ◽  
C. V. Hanson ◽  
B. E. Law
Keyword(s):  
United States ◽  
Elevation Angle ◽  
Model Performance ◽  
Diffuse Radiation ◽  
The United States ◽  
Polynomial Model ◽  
Coefficient Of Determination ◽  
Data Set ◽  
Cubic Polynomial ◽  
Solar Elevation Angle

Abstract. A semi-parametric PAR diffuse radiation model was developed using commonly measured climatic variables from 108 site-years of data from 17 AmeriFlux sites. The model has a logistic form and improves upon previous efforts using a larger data set and physically viable climate variables as predictors, including relative humidity, clearness index, surface albedo and solar elevation angle. Model performance was evaluated by comparison with a simple cubic polynomial model developed for the PAR spectral range. The logistic model outperformed the polynomial model with an improved coefficient of determination and slope relative to measured data (logistic: R2 = 0.76; slope = 0.76; cubic: R2 = 0.73; slope = 0.72), making this the most robust PAR-partitioning model for the United States currently available.

The Telephone Problem and the Road to Telephone Regulation in the United States, 1876–1917

1991 ◽  
Vol 3 (1) ◽  
pp. 42-69 ◽  
Author(s):  
Jeffrey E. Cohen
Keyword(s):  
United States ◽  
Interest Group ◽  
The United States ◽  
Policy Outcomes ◽  
Policy Outcome ◽  
The Public ◽  
The Road ◽  
Telephone Companies ◽  
Private Interests ◽  
Multiple Interest

Between 1876 and 1917, government philosophy toward telephone regulation began moving away from laissez-faire and toward some kind of involvement in economic affairs. However, while some early studies of regulation suggest business hostility to that policy, AT&T actively sought regulation, jogging government and the public in that direction. But this study is not just a restatement of the interest-group-capture theory, as offered by such economists as Stigler or historians as Kolko. Regulation resulted from the convergence of interests of many affected players, including residential and business telephone subscribers, the independent telephone companies that competed with AT&T, and the state and federal governments, as well as AT&T. I employ a multiple interest theory to account for telephone regulation, but unlike other studies using such a framework, I suggest that government is an independent actor with impact on the final policy outcome, and not merely an arena where private interests battle for control over policy outcomes, as is so common among other multiple interest studies of regulation.

Racial Sentiment and Public Support for Arming Teachers with Guns in the United States

2021 ◽  
pp. 215336872110389
Author(s):  
Andrew J. Baranauskas
Keyword(s):  
United States ◽  
African Americans ◽  
Minority Groups ◽  
Public Support ◽  
The United States ◽  
Data Set ◽  
Racial Issue ◽  
Racial Resentment ◽  
Nationally Representative ◽  
Negative Feelings

In the effort to prevent school shootings in the United States, policies that aim to arm teachers with guns have received considerable attention. Recent research on public support for these policies finds that African Americans are substantially less likely to support them, indicating that support for arming teachers is a racial issue. Given the racialized nature of support for punitive crime policies in the United States, it is possible that racial sentiment shapes support for arming teachers as well. This study aims to determine the association between two types of racial sentiment—explicit negative feelings toward racial/ethnic minority groups and racial resentment—and support for arming teachers using a nationally representative data set. While explicit negative feelings toward African Americans and Hispanics are not associated with support for arming teachers, those with racial resentments are significantly more likely to support arming teachers. Racial resentment also weakens the effect of other variables found to be associated with support for arming teachers, including conservative ideology and economic pessimism. Implications for policy and research are discussed.

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