Safety Evaluation of the SafetyEdge Treatment for Pavement Edge Drop-Offs on Two-Lane Rural Roads

2018 ◽  
Vol 2672 (30) ◽  
pp. 1-8
Author(s):  
Craig Lyon ◽  
Bhagwant Persaud ◽  
Eric Donnell
Keyword(s):  
Empirical Bayes ◽  
Safety Evaluation ◽  
Cost Effective ◽  
Rural Highways ◽  
The Road ◽  
Run Off ◽  
Lane Width ◽  
Traffic Volumes ◽  
Pre Treatment ◽  
Edge Drop

This study estimated crash modification factors (CMFs) for the SafetyEdge paving technique that is applied for the treatment of pavement edge drop-offs on two-lane rural highways. An empirical Bayes observational before-after evaluation based on installation data in Iowa, North Carolina, Ohio, Pennsylvania, and Florida found that the SafetyEdge treatment was associated with statistically significant reductions in fatal and injury (FI), run-off-the-road (ROR), opposite-direction (head-on and sideswipe), and drop-off-related crashes. The ROR CMF was also statistically significant for both horizontal curved and tangent sections. A disaggregate analysis examined the variation of the CMF for ROR with factors such as the travel lane width, traffic volume, presence of a horizontal curve, posted speed limit, and the pre-treatment ROR crash frequency. The results of that analysis indicated, for example, that the SafetyEdge paving technique appears to have a greater ROR safety benefit on two-lane rural roadway segments with average annual daily traffic volumes greater than 3,000 vehicles per day, relative to roadway segments with lower traffic volumes. A crash modification function (CMFunction) was calibrated with expected pre-treatment ROR crashes as the independent variable to simultaneously capture the relationship of the CMF for ROR crashes to multiple factors. An economic analysis found that the treatment is highly cost-effective.

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.

scholarly journals Use of single vehicle collisions to model fatigue-related crashes on rural two-lane highways

2021 ◽  
Author(s):  
Xu Lin
Keyword(s):  
Circadian Rhythm ◽  
Traffic Safety ◽  
Safety Information ◽  
Rural Highways ◽  
Formidable Challenge ◽  
Average Curvature ◽  
Run Off ◽  
Traffic Volumes ◽  
Single Vehicle ◽  
Design Factors

Fatigue-related crashes are believed to be more common on rural highways than on urban roads and on two-lane roads rather than on other rural road types. Thus an understanding of how design factors affect fatigue-related crashes on rural to-lane roads is vital. The problem is that fatigue is rarely reported as a cause of crashes, since is is rarely suspected by the police as a possible cause and since potential liability may motive the drivers not to reveal the real causes of the crash. Thus, getting a handle on these crashes thorough modeling is a formidable challenge. Fortunately, there is research to suggest that single-vehicle run-off-road crashes, particularly those during periods of low circadian rhythm, can be used as a reasonable surrogate in modeling fatigue--related crashes. The paper is based on research to examine how fatigue-related crashes rural on two-lane roads, as represented by single vehicle crashes, are affected by various engineering design factors. This study's goal is to explore the effects of fatigue on driving on rural two-lane roads in North America, and to consider how we can work towards mitigating the effects of fatigue on traffic safety. For this investigation, generalized linear and logistic regression modelling were used on US Highway Safety Information System (HSIS) data from Ohio. Models were developed separately and combined for periods of high and low circadian rhythm and for single-vehicle run-off-road and other crashes. The results show, for example, the after controlling for traffic volumes, increases in speed limit, average curvature and average gradient and decreases in surface width and average shoulder width were found to be associated with increased fatigue related crashes. Important differences were found in the effects of factors for period of low and high circadian rhythm.

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.

scholarly journals Use of single vehicle collisions to model fatigue-related crashes on rural two-lane highways

2021 ◽  
Author(s):  
Xu Lin
Keyword(s):  
Circadian Rhythm ◽  
Traffic Safety ◽  
Safety Information ◽  
Rural Highways ◽  
Formidable Challenge ◽  
Average Curvature ◽  
Run Off ◽  
Traffic Volumes ◽  
Single Vehicle ◽  
Design Factors

Fatigue-related crashes are believed to be more common on rural highways than on urban roads and on two-lane roads rather than on other rural road types. Thus an understanding of how design factors affect fatigue-related crashes on rural to-lane roads is vital. The problem is that fatigue is rarely reported as a cause of crashes, since is is rarely suspected by the police as a possible cause and since potential liability may motive the drivers not to reveal the real causes of the crash. Thus, getting a handle on these crashes thorough modeling is a formidable challenge. Fortunately, there is research to suggest that single-vehicle run-off-road crashes, particularly those during periods of low circadian rhythm, can be used as a reasonable surrogate in modeling fatigue--related crashes. The paper is based on research to examine how fatigue-related crashes rural on two-lane roads, as represented by single vehicle crashes, are affected by various engineering design factors. This study's goal is to explore the effects of fatigue on driving on rural two-lane roads in North America, and to consider how we can work towards mitigating the effects of fatigue on traffic safety. For this investigation, generalized linear and logistic regression modelling were used on US Highway Safety Information System (HSIS) data from Ohio. Models were developed separately and combined for periods of high and low circadian rhythm and for single-vehicle run-off-road and other crashes. The results show, for example, the after controlling for traffic volumes, increases in speed limit, average curvature and average gradient and decreases in surface width and average shoulder width were found to be associated with increased fatigue related crashes. Important differences were found in the effects of factors for period of low and high circadian rhythm.

scholarly journals Evaluation of the Use of a Road Diet Design: An Urban Corridor Case Study in Washington, DC

2021 ◽  
Vol 13 (16) ◽  
pp. 8964
Author(s):  
Mohammad A. Aljamal ◽  
Derek Voight ◽  
Jacob Green ◽  
Jianwei Wang ◽  
Huthaifa I. Ashqar
Keyword(s):  
Empirical Bayes ◽  
Annual Number ◽  
Full Time ◽  
Left Turn ◽  
The Road ◽  
Traffic Calming ◽  
Before And After ◽  
Traffic Volumes ◽  
Bayes Analysis ◽  
Urban Corridor

A traditional road diet design converts a four-lane two-way road to a three-lane road consisting of two through lanes and a center two-way left turn lane. This paper introduces a new application of the road diet design in an urban corridor. Specifically, the new application converts a four-lane two-way road into a two-lane two-way road with full-time parking lanes in both directions. The paper analyzed the traffic impacts of the road diet application on the corridor of New Jersey Avenue, northwest, in the city of Washington, District of Columbia. The corridor included five signalized and one unsignalized intersections. Before-and-after analyses using Synchro 11 simulation and Site-Specific Empirical Bayes analysis were used to evaluate and compare existing and proposed scenarios. The proposed scenario provided various benefits including offering accessibility to the businesses in the area and acting as a traffic calming strategy. For signalized intersections, the overall performance remained the same for most intersections except for one intersection (on P Street), as it is significantly impacted by the road diet design due to the dramatic increase of traffic volumes in its minor streets as a result of diverting traffic volumes from the unsignalized intersection for left and through movements. Results showed that the use of a road diet design enhanced the unsignalized intersection performance due to the traffic volume divergence from its minor streets and enhanced the safety of the study area by decreasing the annual number of predicted crashes. To achieve better operational benefits and reflect traffic demands, the paper recommends to re-optimize signal timings when a road diet design is adopted.

The cost-effectiveness of curve flattening in Alberta

1994 ◽  
Vol 21 (2) ◽  
pp. 285-296 ◽  
Author(s):  
R. J. Talarico ◽  
J. F. Morrall
Keyword(s):  
Cost Effectiveness ◽  
Key Words ◽  
Cost Effective ◽  
Traffic Operations ◽  
Rural Highways ◽  
Horizontal Curves ◽  
Traffic Volumes ◽  
Margin Of Safety ◽  
The Cost ◽  
Side Friction

Rehabilitation and restoration improvements on highways typically involve widening lane and shoulder widths, as well as revisions to the superelevation rate. This upgrading approach may sometimes neglect the possibility of flattening horizontal curves, which may result in safer, more cost-effective designs. Aside from the obvious safety benefits for highway travellers, additional benefits may occur in terms of improved traffic operations of intersections on curves. This paper describes the findings of a research project which was conducted to determine the maximum side friction available for a range of roadway curvatures, vehicle speeds, and vehicle types.A three-axis accelerometer and a ball bank indicator were installed in seven test vehicles. Lateral accelerations and ball bank readings were recorded as test vehicles traversed test curves at constant speeds. These data were used to determine the margin of safety provided on dry, wet, and icy pavements.It was found that motorists demand high levels of side friction on sharp curves. In fact, curvatures sharper than 500 m provide very low margins of safety against skidding. Since improved superelevation rates are unlikely to increase the margin of safety to a sufficient level, the cost-effectiveness of curve flattening for rural highways in Alberta was estimated for a range of traffic volumes and central angles. Key words: side friction, margins of safety, horizontal curves, 3-R projects, cost-effectiveness of curve flattening.

scholarly journals Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method

2019 ◽  
Vol 16 (7) ◽  
pp. 1166 ◽  
Author(s):  
Tianpei Tang ◽  
Senlai Zhu ◽  
Yuntao Guo ◽  
Xizhao Zhou ◽  
Yang Cao
Keyword(s):  
Bayesian Network ◽  
Low Cost ◽  
Road Networks ◽  
Access Point ◽  
Safety Risk ◽  
Crash Data ◽  
Risk Levels ◽  
The Road ◽  
Run Off ◽  
Point Density

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts’ judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015–2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

scholarly journals Recent Advances in Conventional Methods and Electrochemical Aptasensors for Mycotoxin Detection

Foods ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1437
Author(s):  
Jing Yi Ong ◽  
Andrew Pike ◽  
Ling Ling Tan
Keyword(s):  
Quantitative Analysis ◽  
Animal Feed ◽  
Cost Effective ◽  
Preventive Action ◽  
High Affinity ◽  
Recent Advances ◽  
Recognition Elements ◽  
Key Features ◽  
Pre Treatment ◽  
And Performance

The presence of mycotoxins in foodstuffs and feedstuffs is a serious concern for human health. The detection of mycotoxins is therefore necessary as a preventive action to avoid the harmful contamination of foodstuffs and animal feed. In comparison with the considerable expense of treating contaminated foodstuffs, early detection is a cost-effective way to ensure food safety. The high affinity of bio-recognition molecules to mycotoxins has led to the development of affinity columns for sample pre-treatment and the development of biosensors for the quantitative analysis of mycotoxins. Aptamers are a very attractive class of biological receptors that are currently in great demand for the development of new biosensors. In this review, the improvement in the materials and methodology, and the working principles and performance of both conventional and recently developed methods are discussed. The key features and applications of the fundamental recognition elements, such as antibodies and aptamers are addressed. Recent advances in aptasensors that are based on different electrochemical (EC) transducers are reviewed in detail, especially from the perspective of the diagnostic mechanism; in addition, a brief introduction of some commercially available mycotoxin detection kits is provided.

scholarly journals Utilising Commercially Fabricated Printed Circuit Boards as an Electrochemical Biosensing Platform

Micromachines ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 793
Author(s):  
Uroš Zupančič ◽  
Joshua Rainbow ◽  
Pedro Estrela ◽  
Despina Moschou
Keyword(s):  
Printed Circuit Boards ◽  
Electrochemical Sensors ◽  
Cost Effective ◽  
Electrochemical Sensing ◽  
Label Free ◽  
Circuit Boards ◽  
Printed Circuit ◽  
Sensing Applications ◽  
Electrochemical Biosensing ◽  
Pre Treatment

Printed circuit boards (PCBs) offer a promising platform for the development of electronics-assisted biomedical diagnostic sensors and microsystems. The long-standing industrial basis offers distinctive advantages for cost-effective, reproducible, and easily integrated sample-in-answer-out diagnostic microsystems. Nonetheless, the commercial techniques used in the fabrication of PCBs produce various contaminants potentially degrading severely their stability and repeatability in electrochemical sensing applications. Herein, we analyse for the first time such critical technological considerations, allowing the exploitation of commercial PCB platforms as reliable electrochemical sensing platforms. The presented electrochemical and physical characterisation data reveal clear evidence of both organic and inorganic sensing electrode surface contaminants, which can be removed using various pre-cleaning techniques. We demonstrate that, following such pre-treatment rules, PCB-based electrodes can be reliably fabricated for sensitive electrochemical biosensors. Herein, we demonstrate the applicability of the methodology both for labelled protein (procalcitonin) and label-free nucleic acid (E. coli-specific DNA) biomarker quantification, with observed limits of detection (LoD) of 2 pM and 110 pM, respectively. The proposed optimisation of surface pre-treatment is critical in the development of robust and sensitive PCB-based electrochemical sensors for both clinical and environmental diagnostics and monitoring applications.

scholarly journals Automatic Roadway Features Detection with Oriented Object Detection

2021 ◽  
Vol 11 (8) ◽  
pp. 3531
Author(s):  
Hesham M. Eraqi ◽  
Karim Soliman ◽  
Dalia Said ◽  
Omar R. Elezaby ◽  
Mohamed N. Moustafa ◽  
...  
Keyword(s):  
Object Detection ◽  
Safety Evaluation ◽  
Autonomous Driving ◽  
Detection Accuracy ◽  
The Road ◽  
Detection Model ◽  
Detection Approach ◽  
Roadway Safety ◽  
Safety Features ◽  
Oriented Object

Extensive research efforts have been devoted to identify and improve roadway features that impact safety. Maintaining roadway safety features relies on costly manual operations of regular road surveying and data analysis. This paper introduces an automatic roadway safety features detection approach, which harnesses the potential of artificial intelligence (AI) computer vision to make the process more efficient and less costly. Given a front-facing camera and a global positioning system (GPS) sensor, the proposed system automatically evaluates ten roadway safety features. The system is composed of an oriented (or rotated) object detection model, which solves an orientation encoding discontinuity problem to improve detection accuracy, and a rule-based roadway safety evaluation module. To train and validate the proposed model, a fully-annotated dataset for roadway safety features extraction was collected covering 473 km of roads. The proposed method baseline results are found encouraging when compared to the state-of-the-art models. Different oriented object detection strategies are presented and discussed, and the developed model resulted in improving the mean average precision (mAP) by 16.9% when compared with the literature. The roadway safety feature average prediction accuracy is 84.39% and ranges between 91.11% and 63.12%. The introduced model can pervasively enable/disable autonomous driving (AD) based on safety features of the road; and empower connected vehicles (CV) to send and receive estimated safety features, alerting drivers about black spots or relatively less-safe segments or roads.

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