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Author: Uditha Nandun Galgamuwa
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Lane-departure crashes are the most predominant crash type in Kansas which causes very high number of motor vehicle fatalities. Therefore, the Kansas Department of Transportation (KDOT) has implemented several different types of countermeasures to reduce the number of motor vehicle fatalities associated with lane-departure crashes. This research was conducted to estimate the safety effectiveness of commonly used lane-departure countermeasures in Kansas on all crashes and lane-departure crashes using Crash Modification Factors (CMFs). Paved shoulders, rumble strips, safety edge treatments and median cable barriers were identified as the commonly used lane-departure countermeasures on both tangent and curved road segments while chevrons and post-mounted delineators were identified as the most commonly used lane-departure countermeasures on curved road segments. This research proposes a state-of-art method of estimating CMFs using cross-sectional data for chevrons and post-mounted delineators. Furthermore, another state-of-art method is proposed in this research to estimate CMFs for safety edge treatments using before-and-after data. Considering the difficulties of finding the exact date of implementation of each countermeasure, both cross-sectional and before-and-after studies were employed to estimate the CMFs. Cross-sectional and case-control methods, which are the two major methods in cross-sectional studies were employed to estimate CMFs for paved shoulders, rumble strips, and median cable barriers. The conventional cross-sectional and case-control methods were modified when estimating CMFs for chevrons and post-mounted delineators by incorporating environmental and human behaviors in addition to geometric and traffic-related explanatory variables. The proposed method is novel and has not been used in the previous cross-sectional models available in the literature. Generalized linear regression models assuming negative binomial error structure were used to develop models for cross-sectional method to estimate CMFs while logistic regression models were used to estimate CMFs using case-control method. Results showed that incorporating environmental and human-related variables into cross-sectional models provide better model fit than in conventional cross-sectional models. To validate the developed models for cross-sectional method, mean of the residuals and the Root Mean Square Error (RMSE) were used. For the case-control method, Receiver Operational Characteristic (ROC) was used to evaluate the predictive power of models for a binary outcome using classification tables. However, it was seen that the case-control method is not suitable for estimating CMFs for all crashes since the range of the crash frequency is wide in each road segment. A regression-based method of estimating CMFs using before-and-after data was proposed to estimate CMFs for safety edge treatments. This method allows researchers to identify the safety effectiveness of an individual CMFs on road segments where multiple treatments have been applied at the same time. Since this method uses road geometric and traffic-related characteristics in addition to countermeasure information as the explanatory variables, the model itself would be the Safety Performance Function (SPF). Therefore, developing new SPF is not necessary. Finally, the CMFs were estimated using before-and-after Empirical Bayes method to validate the results from the regression-based method. The results of this study can be used as a decision-making tool when implementing lane-departure countermeasures on similar roadways in Kansas. Even though there are readily available CMFs from the national level studies, having more localized CMFs will be beneficial due to differences in traffic-related and geometric characteristics on different roadways.
Author: Uditha Nandun Galgamuwa
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Lane-departure crashes are the most predominant crash type in Kansas which causes very high number of motor vehicle fatalities. Therefore, the Kansas Department of Transportation (KDOT) has implemented several different types of countermeasures to reduce the number of motor vehicle fatalities associated with lane-departure crashes. This research was conducted to estimate the safety effectiveness of commonly used lane-departure countermeasures in Kansas on all crashes and lane-departure crashes using Crash Modification Factors (CMFs). Paved shoulders, rumble strips, safety edge treatments and median cable barriers were identified as the commonly used lane-departure countermeasures on both tangent and curved road segments while chevrons and post-mounted delineators were identified as the most commonly used lane-departure countermeasures on curved road segments. This research proposes a state-of-art method of estimating CMFs using cross-sectional data for chevrons and post-mounted delineators. Furthermore, another state-of-art method is proposed in this research to estimate CMFs for safety edge treatments using before-and-after data. Considering the difficulties of finding the exact date of implementation of each countermeasure, both cross-sectional and before-and-after studies were employed to estimate the CMFs. Cross-sectional and case-control methods, which are the two major methods in cross-sectional studies were employed to estimate CMFs for paved shoulders, rumble strips, and median cable barriers. The conventional cross-sectional and case-control methods were modified when estimating CMFs for chevrons and post-mounted delineators by incorporating environmental and human behaviors in addition to geometric and traffic-related explanatory variables. The proposed method is novel and has not been used in the previous cross-sectional models available in the literature. Generalized linear regression models assuming negative binomial error structure were used to develop models for cross-sectional method to estimate CMFs while logistic regression models were used to estimate CMFs using case-control method. Results showed that incorporating environmental and human-related variables into cross-sectional models provide better model fit than in conventional cross-sectional models. To validate the developed models for cross-sectional method, mean of the residuals and the Root Mean Square Error (RMSE) were used. For the case-control method, Receiver Operational Characteristic (ROC) was used to evaluate the predictive power of models for a binary outcome using classification tables. However, it was seen that the case-control method is not suitable for estimating CMFs for all crashes since the range of the crash frequency is wide in each road segment. A regression-based method of estimating CMFs using before-and-after data was proposed to estimate CMFs for safety edge treatments. This method allows researchers to identify the safety effectiveness of an individual CMFs on road segments where multiple treatments have been applied at the same time. Since this method uses road geometric and traffic-related characteristics in addition to countermeasure information as the explanatory variables, the model itself would be the Safety Performance Function (SPF). Therefore, developing new SPF is not necessary. Finally, the CMFs were estimated using before-and-after Empirical Bayes method to validate the results from the regression-based method. The results of this study can be used as a decision-making tool when implementing lane-departure countermeasures on similar roadways in Kansas. Even though there are readily available CMFs from the national level studies, having more localized CMFs will be beneficial due to differences in traffic-related and geometric characteristics on different roadways.
Author: Irfan Uddin Ahmed
Publisher:
ISBN: 9780438384477
Category : Roads
Languages : en
Pages : 103
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Book Description
The World Health Organization (WHO) reports road traffic injuries are one of the leading causes of death worldwide with 1.2 million people dying in traffic crashes annually. Total losses in monetary value amounted to $836 billion in the US in 2010. According to the Federal Highway Administration (FHWA), the comprehensive cost of a single fatal crash is estimated to be $9.6 million (2016 dollars). There have been 37,461 fatalities in 2016 in the US, which was an increase of 5.5% from 2015. According to the Fatality Analysis of Reporting System (FARS), the traffic fatality rate for the US was 1.18 per 100 million vehicle miles traveled (MVMT) while Wyoming experienced 1.20 fatalities per 100 MVMT in 2016. The trend in recent crash rates reveals that Wyoming has always been facing higher fatality rates than the national average. Challenging roadway geometry, long driving distances, and adverse weather conditions could contribute to higher average crash rates in Wyoming. Research shows that a significant number of fatal and serious injury crashes result from lane departure crashes. Lane departure crashes include angle, head-on, sideswipe, and run-off-road crashes. Factors such as driver fatigue and drowsiness, distracted driving, poor road surface condition, adverse weather, challenging roadway geometry preventing easy passing maneuvers may result in increased lane departure crashes. Some of these contributing factors could be mitigated by providing countermeasures, such as centerline rumble strips, by adding passing lanes on a two-lane roadway, and by dividing the roadway into four-lane highways. This study analyzes and compares the safety effectiveness of these three countermeasures on a two-lane two-way highway in Wyoming. The roadway selected for this study is US 287 between Laramie and the Wyoming-Colorado Stateline. Statistical analyses and benefit-cost analyses were carried out to evaluate the safety effectiveness of the aforementioned countermeasures. Six years of crash data (2003-2008) were used to develop the Safety Performance Functions (SPFs) utilizing negative binomial and zero-inflated negative binomial (ZINB) regression models. A segmented dataset consisting of variable segment lengths was prepared using homogeneous roadway geometry and traffic volume data. SPFs were developed for total crashes, property damage only (PDO) crashes, fatal and injury (F+I) crashes as well as lane departure crashes. Numerous explanatory variables related to roadway geometry and traffic volume were considered in the modeling process. It was found that LOG(VMT), vertical grade, and presence of rumble strips were the significant variables in predicting crash frequency. AIC was used as the model selection criterion to find the best fit model. Observational before-after with Empirical Bayes (EB) method was utilized to develop Crash Modification Factors (CMF) to analyze the safety effectiveness of lane departure crash countermeasure. The results show that with the implementation of conversion to four-lane divided highway, there is an expected crash reduction of 52%, 55%, 86%, and 77% associated with total crashes, F+I crashes, PDO crashes, and lane departure crashes, respectively. Furthermore, the CMFs for centerline rumble strips indicate expected crash reduction of 69%, 52%, 89%, and 80% for total crashes, F+I crashes, PDO crashes, and lane departure crashes, respectively. The CMFs obtained for passing lanes show that an expected total crash reduction of 32%, F+I crash reduction of 20% and 25% crash reduction in lane departure crashes. The overall results from this analysis show that the highest percentage of crash reduction can be expected from the implementation of centerline rumble strips. All the CMFs indicated that all countermeasures are effective in reducing the frequency and severity of crashes. Finally, a benefit-cost analysis (BCA) was carried out using comprehensive crash costs calculated by following the Highway Safety Manual and the Wyoming Department of Transportation methods. The BCA provided the opportunity to determine which countermeasure provided the best return (benefits) on investment (project costs). It was found that the return on investment is the highest for the implementation of centerline rumble strips followed by addition of passing lanes. Conversion to four-lane divided highway resulted in the lowest benefit to cost ratio. One of the reasons for this could be the higher project costs of adding lanes and dividing the roadway than the other countermeasures investigated in this study. The safety analyses and the benefit-cost analyses carried out in this study show that the implementation of centerline rumble strips provides very high CMFs and benefit to cost ratio which may seem impractical. There could be a number of reasons for the overestimation of the CMFs and the benefits of centerline rumble strips.
Author: Sunanda Dissanayake
Publisher:
ISBN:
Category :
Languages : en
Pages : 113
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Book Description
Kansas experienced about 60,000 crashes annually from 2013 to 2016, 25% of which occurred at urban intersections. Hence, urban intersections in Kansas are one of the critical locations in terms of frequency of crashes. Therefore, an accurate prediction of crashes at these locations would help identify critical intersections with a higher probability of an occurrence of crash, which would help in selecting appropriate countermeasures to reduce those crashes. The crash prediction models provided in the Highway Safety Manual (HSM) predict crashes using traffic and geometric data for various roadway facilities, which are incorporated through Safety Performance Functions (SPFs) and Crash Modification Factors. The primary objective of this study was to estimate calibration factors for different types of urban intersections in Kansas. This study followed the crash prediction method and calibration procedure provided in the HSM to estimate calibration factors for four different urban intersection types in Kansas: 3-leg unsignalized intersections with stop control on the minor approach (3ST), 3-leg signalized intersections (3SG), 4-leg unsignalized intersections with stop control on the minor approach (4ST), and 4-leg signalized intersections (4SG). Following the HSM methodology, the required data elements were collected from various sources. The Annual Average Daily Traffic (AADT) data were extracted from the Kansas Crash Analysis & Reporting System (KCARS) database and GIS Shapefiles were downloaded from the Federal Highway Administration website. For some of the 3ST and 3SG intersections, minor-street AADT was not available. Hence, multiple linear regression models were developed for the estimation of minor-street AADT. Crash data were extracted from the KCARS database, and other geometric data were extracted using Google Earth. The HSM requirement for sample size is 30 to 50 sites, with at least 100 crashes per year for the study period for the combined set of sites. In this study, 2013 to 2015 was chosen as the study period for 3ST, 3SG, and 4SG intersections, and 2014 to 2016 was chosen for 4ST intersections, based on the availability of recent crash data at the beginning of the calibration procedure for each facility type. The sample size considered for calibration was 234 for 3ST, 89 for 3SG, 167 for 4ST, and 198 for 4SG intersections. Out of the 234 3ST intersections, minor-street AADT was estimated using multiple linear regression models for 106 intersections. For 3SG intersections, minor-street AADT was estimated for 21 out of the 89 intersections. The calibration factors for these facility types were estimated to be 0.64 for 3SG, 0.51 for 3ST, 1.17 for 4SG, and 0.61 for 4ST when considering crashes of all severities. Considering only the fatal and injury crashes, the calibration factors were estimated as 0.52 for 3SG, 0.40 for 3ST, 2.00 for 4SG, and 0.73 for 4ST. The calibration factors show that the HSM methodology underpredicted crashes for 4SG intersections, and overpredicted crashes for the other three intersection types. The reliability of the calibration factors was assessed with the help of Cumulative Residual plots and coefficient of variation. The results from the goodness-of-fit tests showed that the calibration factors were not reliable and showed bias in the prediction of crashes. Hence, calibration functions were developed, and their reliability was examined. The results showed that calibration functions had better reliability as compared to calibration factors, with more accuracy in crash prediction. The findings from this study can be used to identify intersections with a higher probability of having crashes in the future. Suitable countermeasures can be applied at critical locations which would help reduce the number of crashes at urban intersections in Kansas, thus increasing the safety.
Author: Amin Akhnoukh
Publisher: Springer Nature
ISBN: 3030798011
Category : Technology & Engineering
Languages : en
Pages : 1211
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Book Description
This volume focuses on recent advances in the planning, design, construction and management of new and existing roads with a particular focus on safety, sustainability and resilience. It discusses field experience through case studies and pilots presented by leading international subject-matter specialists. Chapters were selected from the 18th International Road Federation World Meeting & Exhibition, Dubai 2021.
Author: Rijesh Karmacharya
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Kansas experienced about 60,000 crashes annually from 2013 to 2016, 25% of which occurred at urban intersections. Hence, urban intersections in Kansas are one of the most critical locations in terms of frequency of crashes. Therefore, an accurate prediction of crashes at these locations would help identify critical intersections with a higher probability of an occurrence of crash, which would help in selecting appropriate countermeasures to reduce those crashes. The crash prediction models provided in the Highway Safety Manual (HSM) predict crashes using traffic and geometric data for various roadway facilities, which are incorporated through Safety Performance Functions (SPFs) and Crash Modification Factors. The primary objective of this study was to estimate calibration factors for different types of urban intersection in Kansas. This study followed the crash prediction method and calibration procedure provided in the HSM to estimate calibration factors for four different urban intersection types in Kansas: 3-leg unsignalized intersections with stop control on the minor approach (3ST), 3-leg signalized intersections (3SG), 4-leg unsignalized intersections with stop control on the minor approach (4ST), and 4-leg signalized intersections (4SG). Following the HSM methodology, the required data elements were collected from various sources. The Annual Average Daily Traffic (AADT) data were extracted from Kansas Crash Analysis & Reporting System (KCARS) database and GIS Shapefiles downloaded from Federal Highway Administration website. For some of 3ST and 3SG intersections, minor-street AADT was not available. Hence, multiple linear regression models were developed for the estimation of minor-street AADT. Crash data were extracted from the Kansas Crash Analysis and Reporting System database, and other geometric data were extracted using Google Earth. The HSM requirement for sample size is 30 to 50 sites, with at least 100 crashes per year for the study period for the combined set of sites. In this study, the study period for 3ST, 3SG, and 4SG intersections were taken as 2013 to 2015, and 2014 to 2016 for 4ST, based on the availability of recent crash data at the beginning of the calibration procedure for each facility type. The sample size considered for calibration was 234 for 3ST, 89 for 3SG, 167 for 4ST, and 198 for 4SG intersections. Out of the 234 3ST intersections, minor-street AADT was estimated using multiple linear regression models for 106 intersections. For 3SG intersections, minor-street AADT was estimated for 21 out of the 89 intersections. The calibration factors for these facility types were estimated to be 0.64 for 3SG, 0.51 for 3ST, 1.17 for 4SG, and 0.61 for 4ST when considering crashes of all severities. Considering only the fatal and injury crashes, the calibration factors were estimated as 0.52 for 3SG, 0.40 for 3ST, 2.00 for 4SG, and 0.73 for 4ST. The calibration factors show that the HSM methodology underpredicted crashes for 4SG, and overpredicted crashes for other three intersection types. The reliability of the calibration factors was assessed with the help of Cumulative Residual plots and coefficient of variation. The results from the goodness-of-fit tests showed that the calibration factors were not reliable and showed bias in the prediction of crashes. Hence, calibration functions were developed, and their reliability were examined. The results showed that calibration functions had better reliability as compared to calibration factors, with more accuracy in crash prediction. The findings from this study can be used to identify intersections with a higher probability of having crashes in the future. Suitable countermeasures can be applied at critical locations which would help reduce the number of crashes at urban intersections in Kansas; thus increasing the safety.
Author: David L. Harkey
Publisher:
ISBN:
Category : Transportation
Languages : en
Pages : 92
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Book Description
TRB¿s National Cooperative Highway Research Program (NCHRP) Report 617: Accident Modification Factors for Traffic Engineering and ITS Improvements explores the development of accident modification factors (AMFs) for traffic engineering and intelligent transportation system improvements. AMFs, also known as crash reduction factors, are designed to provide a simple and quick way of estimating the safety impacts of various types of engineering improvements, encompassing the areas of signing, alignment, channelization, and other traffic engineering solutions.
Author:
Publisher:
ISBN: 9780309702546
Category : Traffic accidents
Languages : en
Pages : 0
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Book Description
Highway safety practitioners were given a significant new tool in 2010 with the publication of the AASHTO Highway Safety Manual. In the HSM, crash modification factors (CMFs) were provided to estimate the safety effects for a variety of treatments or countermeasures. The TRB National Cooperative Highway Research Program's NCHRP Web-Only Document 352: Crash Modification Factors in the Highway Safety Manual: Resources for Evaluation provides the appendices to NCHRP Research Report 1029: Crash Modification Factors in the Highway Safety Manual: A Review.
Author: James A. Bonneson
Publisher:
ISBN:
Category : Roads
Languages : en
Pages : 46
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Book Description
Highway safety is an ongoing concern to the Texas Department of Transportation (TxDOT). As part of its proactive commitment to improving highway safety, TxDOT is moving toward including quantitative safety analyses earlier in the project development process. The objectives of this research project are: (1) the development of safety design guidelines and evaluation tools to be used by TxDOT designers, and (2) the production of a plan for the incorporation of these guidelines and tools in the planning and design stages of the project development process. This document describes a procedure for using accident modification factors in the highway design process. Application of the procedure entails the use of several factors, where each factor addresses one specific design element (such as lane width, shoulder width, curve radius, etc.). Collectively, the factors can be used to estimate the effect of a change in one or more design elements. The procedure can be used to evaluate the safety benefits associated with alternative geometric designs.
Author: Eric Donnell
Publisher:
ISBN:
Category : Roads
Languages : en
Pages : 114
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Book Description
The transportation-engineering community is transforming by integrating quantitative methods into the task development process. This report identifies opportunities to better understand the relationships between road safety and factors that affect traffic-crash occurrence and severity. In this report, current statistical-analysis methods and data sources used in road-safety research are compared with alternative methods and data sources. Causal inference methods are compared to observational before–after methods to develop safety-effect estimates of centerline and edgeline rumble strips. Regression trees and Random ForestsTM are compared to count regression methods to predict crash frequencies on freeways. Road-safety performance estimates using the Crash Outcomes Data Evaluation System are also discussed, with a focus on opportunities to link hospital and crash data to understand the relationship between crashes and site-specific contributing factors. Methods to account for underreporting in crash-frequency models are also described.
Author: United States. Federal Highway Administration
Publisher:
ISBN:
Category : Highway engineering
Languages : en
Pages : 28
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Book Description
Documents estimates of the crash reduction that might be expected if a specific countermeasure or group of countermeasures is implemented with respect to roadway departure crashes and other non-intersection crashes. The crash reduction estimates are presented as Crash Reduction Factors (CRFs).
