scholarly journals Safety evaluation of roundabouts at freeway ramp terminals and HSM calibration

2017 ◽  
Author(s):  
◽  
Jacob A. Berry
Keyword(s):  
Empirical Bayes ◽  
Safety Evaluation ◽  
Crash Severity ◽  
Site Specific ◽  
Crash Data ◽  
Highway Safety Manual ◽  
Time Period ◽  
Using Data ◽  
Crash Types ◽  
Project Level

Although the conventional understanding is that roundabouts have the potential to improve safety at intersections, particularly by reducing more severe crash types, there is limited knowledge on their safety impacts when utilized as part of an interchange system. This research utilizes multiple years of crash, traffic, and geometric data across a variety of roundabout interchange sites in Missouri to develop a two-level Empirical Bayes (EB) safety analysis at the project (entire interchange) and site-specific (ramp terminal only) levels. The results were then aggregated for both single-lane and dual-lane roundabout terminals. The project-level results for single-lane sites showed a decrease in fatal/injury crashes (FI) by 20.3 percent, property damage only (PDO) crashes by 26.0 percent and total crashes by 24.5 percent. The site-specific results for single-lane roundabout terminals indicated a reduction of FI crashes by 32.8 percent, PDO crashes by 23.1 percent, and total crashes by 24.4 percent. At the project-level, dual-lane roundabouts were shown to reduce FI crashes by 2.3 percent while increasing PDO and total crashes by 16.9 percent and 12.2 percent, respectively. The dual-lane site-specific results indicated an increase in FI crashes by 34.7 percent, PDO crashes by 53.9 percent, and total crashes by 50.0 percent at the ramp terminal specifically. This analysis directly compares observed crash data after roundabout implementation to the expected number of crashes over that time period if the roundabout were never constructed. Therefore, this indicates that single-lane roundabouts performed significantly better than their original configurations, while the dual-lane roundabout terminals were shown to be less-suitable for certain applications. Additionally, it was found that a high proportion of the roundabout crashes occurred at the exit ramp approach legs; this was illustrated in the collision diagrams and crash type distributions that were produced for the common observed crashes at both single and dual-lane roundabout terminals. As a separate part of this thesis research, an improved calibration of the Highway Safety Manual safety performance functions of four facility types was performed using data from 2012-2014 to calibrate for local Missouri conditions. Crash severity and crash type distributions were also developed for each facility type.

Safety Evaluation of Horizontal Alignment Design Consistency on Rural Two-Lane Highways

2019 ◽  
Vol 2673 (2) ◽  
pp. 628-636 ◽  
Author(s):  
Ian Hamilton ◽  
Scott Himes ◽  
R. J. Porter ◽  
Eric Donnell
Keyword(s):  
Negative Binomial ◽  
Safety Evaluation ◽  
Negative Binomial Regression ◽  
Expected Number ◽  
Horizontal Alignment ◽  
Highway Safety Manual ◽  
Horizontal Curves ◽  
Alternative Measures ◽  
Using Data ◽  
Design Consistency

Design consistency in the context of highway and street design refers to the conformance of highway geometry to driver expectancy. Existing design policies provide guidance related to horizontal alignment design consistency. While design consistency has safety implications and is intuitively linked to roadway departure crashes, the authors are only aware of a few studies that sought to link measures of design consistency to safety performance. This study explores relationships between alternative measures of horizontal alignment design consistency and the expected number of roadway departure crashes along horizontal curves on rural, two-lane, two-way roads. The authors analyzed 854 horizontal curves on rural two-lane highways in Indiana and Pennsylvania using data obtained from the SHRP 2 Roadway Information Database (RID) 2.0. Relationships between measures of design consistency and the expected number of roadway departure crashes were explored using a negative binomial regression modeling approach. The results indicate a relationship between the frequency of roadway departure crashes on a study curve and the radii of upstream and downstream curves. The ratio of the length of upstream and downstream tangents relative to a study curve radius was also statistically significant in Pennsylvania. Such findings are intuitive given the concept of design consistency and represent an advancement to existing predictive methods in the AASHTO Highway Safety Manual, which estimate the expected number of crashes on a segment as a function of the characteristics of only that segment.

scholarly journals Collective Risk Ranking of Highway Segments on the Basis of Severity-Weighted Crash Rates

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Dawei Li ◽  
Mustafa F. M. Al-Mahamda
Keyword(s):  
Empirical Bayes ◽  
Safety Information ◽  
Crash Severity ◽  
Regression To The Mean ◽  
Factors Affecting ◽  
Crash Data ◽  
Crash Rates ◽  
Risk Ranking ◽  
Collective Risk ◽  
Major Factors

This study is intended to focus on the major factors affecting traffic crash rates and severity levels, in addition to identifying crash-prone locations (i.e., black spots) based on the two indicators. The available crash data for different road segments used for the analysis were obtained from the Washington state database provided by the Highway Safety Information System (HSIS) for the years 2006 to 2011. A Random Forest (RF) classifier was used to predict the outcome level of crash severity, while crash rates were predicted by applying RF regressor. Certain features were selected for each model besides the abstraction of new features to check if there are unobserved correlations affecting the independent variables, such as accounting for the number and weight of crashes within 1 km2 area by implementing the Getis-Ord Gi∗ index. Moreover, to calculate the collective risk (CR) score, crash rates were adjusted to incorporate crash severity weights (cost per severity type) and regression-to-the-mean (RTM) bias via Empirical Bayes (EB) method. Finally, segments were ranked according to their CR score.

Safety Evaluation of Alternative Audible Lane Departure Warning Treatments in Reducing Traffic Crashes: An Empirical Bayes Observational Before–After Study

2018 ◽  
Vol 2672 (21) ◽  
pp. 30-40 ◽  
Author(s):  
Lingtao Wu ◽  
Srinivas R. Geedipally ◽  
Adam M. Pike
Keyword(s):  
Empirical Bayes ◽  
Safety Evaluation ◽  
Highway Safety ◽  
Warning Systems ◽  
Lane Departure Warning ◽  
Crash Data ◽  
Pavement Markings ◽  
Lane Departure ◽  
Run Off ◽  
Single Vehicle

Roadway departure crashes are a major contributor to traffic fatalities and injury. Rumble strips have been shown to be an effective countermeasure in reducing roadway departure crashes. However, some roadway situations, for instance, inadequate shoulder width or roadway surface depth, have limited the application of conventional milled or rolled in rumble strips. Alternative audible lane departure warning systems, including profile (audible) pavement markings and preformed rumble bars, are increasingly used to overcome the limitations that exist with the milled rumble strips. So far, the safety effectiveness of these alternative audible lane departure warning systems has not been extensively assessed. The main purpose of this paper is to examine the safety effect of installing profile pavement markings and preformed rumble bars. Specifically, this study developed crash modification factors for these treatments that quantify the effectiveness in reducing single-vehicle-run-off-road (SVROR) and opposite-direction (OD) crashes. Traffic, roadway, and crash data at the treated sites on 189 miles of rural two-lane highways in Texas were analyzed using an empirical Bayes (EB) before–after analysis method. Safety performance functions from the Highway Safety Manual and Texas Highway Safety Design Workbook were used in the EB analysis. The results revealed a 21.3% reduction in all SVROR and OD crashes, and 32.5% to 39.9% reduction in fatal and injury SVROR and OD crashes after installing profile pavement marking and preformed rumble bars.

Safety Performance of Flashing Yellow Arrow for Protected–Permissive Left-Turn Signal Control in Central Illinois

2017 ◽  
Vol 2636 (1) ◽  
pp. 32-42 ◽  
Author(s):  
Kerrie L. Schattler ◽  
Eric P. Anderson ◽  
Trevor Hanson
Keyword(s):  
Empirical Bayes ◽  
Safety Evaluation ◽  
Left Turn ◽  
Turn Signal ◽  
Crash Data ◽  
Flashing Yellow Arrow ◽  
Before And After ◽  
Control Research ◽  
Central Illinois ◽  
Yellow Arrow

In 2010, the Illinois Department of Transportation began implementing the flashing yellow arrow (FYA) at intersections operating with protected–permissive left-turn (PPLT) control. Research was conducted to evaluate the safety-effectiveness of FYAs at 86 intersections and 164 approaches in central Illinois. The effectiveness evaluation was performed with 3 years of before-and-after FYA installation crash data and the empirical Bayes method. In the before condition, the left-turn signals operated with a circular green display indicating the permissive interval of PPLT control using a five-section signal head. In the after condition, the FYA replaced the circular green display for the permissive interval of PPLT with a four-section signal head. Supplemental traffic signs were mounted on the mast arm adjacent to the left-turn signal at over half of the FYA installations. The results of the comprehensive safety evaluation of the FYA for PPLT control are presented. Analyses were also performed to assess the effects of the FYA supplemental signs and the effects of the FYA overall on two subsets of at-fault drivers: older drivers (age 65+) and younger drivers (age 16 to 21). The resulting mean crash modification factors for the targeted crash types ranged from 0.589 to 0.714. The findings of this research support the continued use of FYAs for PPLT control to improve safety at signalized intersections in central Illinois.

Evaluating the Safety Effects of Span Wire to Mast Arm Signal Conversion

2018 ◽  
Vol 2672 (30) ◽  
pp. 21-31 ◽  
Author(s):  
Zulqarnain H. Khattak ◽  
Michael D. Fontaine
Keyword(s):  
Road Safety ◽  
Empirical Bayes ◽  
Comprehensive Evaluation ◽  
Department Of Transportation ◽  
Crash Data ◽  
Signal Conversion ◽  
Modification Factor ◽  
Virginia Department ◽  
Crash Types ◽  
Safety Benefit

The mast arm signal mounting configuration has often been assumed to provide greater conspicuity and visibility than span wire installations, but the impacts of this countermeasure on road safety have not been well established quantitatively. This paper’s intent is to provide a comprehensive evaluation of safety effects of converting span wire installations to mast arm installations. An Empirical Bayes before–after safety analysis was conducted using crash data for 30 intersections collected from the Virginia Department of Transportation (VDOT). A crash type analysis was also conducted to observe changes in crash types. Based on the data available, no statistically significant improvement in safety was found. Average crash modification factor (CMF) values of 0.97 and 0.98 were observed for total and fatal and injury crashes, but these CMFs were not statistically significant. A reduction in the proportion of angle crashes was observed, but the change was not statistically significant and the overall distribution of crashes did not change significantly after converting signal configurations from span wire to mast arm. Although mast arm deployments may offer advantages in maintenance costs and aesthetics, there does not appear to be a substantial safety benefit to these conversions.

scholarly journals Safety evaluation for roadside crashes by vehicle–object collision simulation

2018 ◽  
Vol 10 (10) ◽  
pp. 168781401880558 ◽  
Author(s):  
Kejun Long ◽  
Zhibo Gao ◽  
Quan Yuan ◽  
Wang Xiang ◽  
Wei Hao
Keyword(s):  
Evaluation Method ◽  
Center Of Mass ◽  
Safety Evaluation ◽  
Severity Index ◽  
Field Investigation ◽  
Crash Test ◽  
Crash Severity ◽  
Roadside Safety ◽  
Crash Data ◽  
Test Standards

In order to evaluate roadside crash severity and help making decision on roadside safety improvement alternatives, this article proposes a roadside crash severity evaluation method based on vehicle kinematics metric during the crash: Acceleration Severity Index. Based on the field investigation on 1917 km of representative roads, roadside crash test standards and parameters were determined. A total of 59 crash scenarios, involving 5 typical roadside obstacles, 2 types of guardrails, 15 embankment slopes, and 3 types of vehicles (car, bus, and truck), were designed for simulated crash testing with VPG3.2 and LS-DYNA971 software. The x-, y-, and z-direction acceleration (or deceleration) curves of a test vehicle’s center of mass during each crash test were collected for the calculation of the Acceleration Severity Index values. The Fisher optimal partition algorithm was used to cluster the Acceleration Severity Index values to identify an appropriate number of roadside crash severity levels and the corresponding threshold values that demarcate these levels. The results showed that the roadside crash severity classification produced by Acceleration Severity Index–based method is consistent with handbook Guideline for Implementation of Highway Safety Enhancement Project. Therefore, when crash data are missing, crash test could be a feasible surrogate method for roadside crash severity evaluation.

Empirical Bayes Before-After Study to Develop Crash Modification Factors and Functions for High Friction Surface Treatments on Curves and Ramps

2020 ◽  
Vol 2674 (12) ◽  
pp. 505-514 ◽  
Author(s):  
Craig Lyon ◽  
Bhagwant Persaud ◽  
David Merritt ◽  
Joseph Cheung
Keyword(s):  
Friction Surface ◽  
Empirical Bayes ◽  
Crash Frequency ◽  
Run Off ◽  
Innovative Methodology ◽  
Crash Modification Factors ◽  
Using Data ◽  
Benefit Cost ◽  
Crash Types ◽  
Disaggregate Analysis

The intent of the study was to fill a knowledge void by developing high quality crash modification factors (CMFs) and benefit/cost (B/C) ratios for high friction surface treatment (HFST). The state-of-the-art empirical Bayes (EB) before-after methodology was applied to evaluate the effects of this treatment on crashes of various types using data from West Virginia (curve sites), Pennsylvania (curve sites), Kentucky (curve and ramp sites), and Arkansas (ramp sites). The results for curve sites generally indicate substantial and highly significant safety benefits. This is especially so for the primary crash types targeted by HFST programs: run-off-road, wet road, and head-on side-swipe opposite direction crashes (HOSSOD). The results for ramp sites were inconsistent, with substantial benefits for all crashes and injury crashes for Kentucky, negligible effects for these crashes in Arkansas, and substantial and highly significant reductions in wet weather crashes in both states. A disaggregate analysis of the CMF results for curve sites indicated a logical and consistent relationship between CMFs and three variables: friction improvement, traffic volume, and expected crash frequency before treatment. These variables, and an innovative methodology, were used in developing crash modification functions (CMFunctions) that can be applied to determine where, and under what conditions, the treatment can be used most effectively. Such functions are typically not provided for the vast majority of treatments for which CMFs are available, so, in itself, developing them is a significant contribution of this research.

Safety Evaluation of Change in Posted Speed Limit from 65 to 70 mph on Rural Virginia Interstate System

2018 ◽  
Vol 2672 (38) ◽  
pp. 35-45
Author(s):  
Scott Himes ◽  
Frank Gross ◽  
Michael Nichols ◽  
Mena Lockwood
Keyword(s):  
Empirical Bayes ◽  
Safety Evaluation ◽  
Speed Limit ◽  
Department Of Transportation ◽  
Run Off ◽  
Adjustment Factors ◽  
Interstate System ◽  
Virginia Department ◽  
Crash Types ◽  
Disaggregate Analysis

Effective July 1, 2010, the Virginia Department of Transportation (VDOT) increased the maximum posted speed limit on interstates and similar facilities from 65 to 70 mph, if recommended following an engineering study. As a result, VDOT performed engineering studies on selected rural interstates posted at 65 mph. By November 2010, VDOT had increased the speed limit from 65 to 70 mph for approximately 670 centerline miles of select rural interstates. This paper presents the results of an empirical Bayes before–after study into the safety and operational effects of the speed limit increase. The analysis focused on total, injury, run-off-road, and truck-related crashes. Comparison segments were used to develop annual adjustment factors, account for regional differences, and identify underlying crash trends in the period before the speed limit increase. At the aggregate level, the results indicated no increase in any of the focus crash types after the increase. Focusing on sites without other changes, the increased speed limit did not increase or decrease any of the crash types. The disaggregate analysis provided further insight into the circumstances in which the change in posted speed limit had more and less pronounced impacts; specifically, that segment type (base or interchange) influenced safety: interchange segments observed statistically significant increases in total, run-off-road, and truck-related crashes. The disaggregate analysis also showed that roadway improvements may help to offset the safety impact of increasing the posted speed limit.

Safety Evaluation of Pedestrian Countdown Signals: Definitive Results from Two Cities in the United States

2021 ◽  
pp. 036119812110634
Author(s):  
Raghavan Srinivasan ◽  
Bo Lan ◽  
Daniel Carter ◽  
Sarah Smith ◽  
Bhagwant Persaud ◽  
...  
Keyword(s):  
Confidence Level ◽  
Empirical Bayes ◽  
Safety Evaluation ◽  
The United States ◽  
Cost Ratio ◽  
Regression To The Mean ◽  
Benefit Cost Ratio ◽  
Inadequate Sample Size ◽  
Pedestrian Crashes ◽  
Using Data

The pedestrian countdown signals (PCS) treatment involves the display of a numerical countdown that shows how many seconds are left in the flashing DON’T WALK interval. Although many studies have attempted to evaluate the safety of PCS, the results have been inconsistent for many reasons, including inadequate sample size and the inability to control for possible bias from regression to the mean and from exposure. This study performed a before-after empirical Bayes analysis using data from 115 treated intersections in Charlotte, North Carolina and 218 treated intersections in Philadelphia, Pennsylvania to evaluate the safety effects of PCS. The evaluation also included 136 reference intersections in Charlotte, and 597 reference intersections in Philadelphia. Following the implementation of PCS, total crashes decreased by approximately 8% and rear-end crashes decreased by approximately 12%, and these reductions were statistically significant at the 95% confidence level. Pedestrian crashes decreased by about 9% and this reduction was statistically significant at the 90% confidence level. Economic analysis revealed a benefit-cost ratio of 23 with a low of 13 and a high of 32.

scholarly journals Longitudinal stability of urinary extracellular vesicle protein patterns within and between individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Leyla A. Erozenci ◽  
Sander R. Piersma ◽  
Thang V. Pham ◽  
Irene V. Bijnsdorp ◽  
Connie R. Jimenez
Keyword(s):  
Expression Patterns ◽  
Interaction Network ◽  
Extracellular Vesicle ◽  
Protein Signaling ◽  
Protein Patterns ◽  
Specific Expression ◽  
Non Invasive ◽  
Data Independent Acquisition ◽  
Time Period ◽  
Using Data

AbstractThe protein content of urinary extracellular vesicles (EVs) is considered to be an attractive non-invasive biomarker source. However, little is known about the consistency and variability of urinary EV proteins within and between individuals over a longer time-period. Here, we evaluated the stability of the urinary EV proteomes of 8 healthy individuals at 9 timepoints over 6 months using data-independent-acquisition mass spectrometry. The 1802 identified proteins had a high correlation amongst all samples, with 40% of the proteome detected in every sample and 90% detected in more than 1 individual at all timepoints. Unsupervised analysis of top 10% most variable proteins yielded person-specific profiles. The core EV-protein-interaction network of 516 proteins detected in all measured samples revealed sub-clusters involved in the biological processes of G-protein signaling, cytoskeletal transport, cellular energy metabolism and immunity. Furthermore, gender-specific expression patterns were detected in the urinary EV proteome. Our findings indicate that the urinary EV proteome is stable in longitudinal samples of healthy subjects over a prolonged time-period, further underscoring its potential for reliable non-invasive diagnostic/prognostic biomarkers.

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