Modeling Crash Severity And Speed Profile At Roadway Work Zones
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| Author | : Zhenyu Wang |
| Publisher | : |
| Total Pages | : |
| Release | : 2008 |
| Genre | : |
| ISBN | : |
ABSTRACT: Work zone tends to cause hazardous conditions for drivers and construction workers since work zones generate conflicts between construction activities and the traffic, therefore aggravate the existing traffic conditions and result in severe traffic safety and operational problems. To address the influence of various factors on the crash severity is beneficial to understand the characteristics of work zone crashes. The understanding can be used to select proper countermeasures for reducing the crash severity at work zones and improving work zone safety. In this dissertation, crash severity models were developed to explore the factor impacts on crash severity for two work zone crash datasets (overall crashes and rear-end crashes). Partial proportional odds logistic regression, which has less restriction to the parallel regression assumption and provides more reasonable interpretations of the coefficients, was used to estimate the models. The factor impacts were summarized to indicate which factors are more likely to increase work zone crash severity or which factors tends to reduce the severity. Because the speed variety is an important factor causing accidents at work zone area, the work zone speed profile was analyzed and modeled to predict the distribution of speed along the distance to the starting point of lane closures. A new learning machine algorithm, support vector regression (SVR), was utilized to develop the speed profile model for freeway work zone sections under various scenarios since its excellent generalization ability. A simulation-based experiment was designed for producing the speed data (output data) and scenario data (input data). Based on these data, the speed profile model was trained and validated. The speed profile model can be used as a reference for designing appropriate traffic control countermeasures to improve the work zone safety.
| Author | : Qing Wang |
| Publisher | : |
| Total Pages | : |
| Release | : 2009 |
| Genre | : |
| ISBN | : |
ABSTRACT: In USA, despite recent efforts to improve work zone safety, the number of crashes and fatalities at work zones has increased continuously over several past years. For addressing the existing safety problems, a clear understanding of the characteristics of work zone crashes is necessary. This thesis summarized a research study focusing on work zone traffic crash analysis to investigate the characteristics of work zone crashes and to identify the factors contributing to injury severity at work zones. These factors included roadway design, environmental conditions, traffic conditions and vehicle/driver features. Especially, special population groups, which divided into older, middle Age, and young, were inspected. This study was based on history crash data from the Florida State, which were extracted from the Florida CAR (Crash Analysis Reporting) system. Descriptive statistics method was used to find the characteristics of crashes at work zones. After then, an injury severity predict model, using the ordered probit regression technology, was developed to investigate the impacts of various factors on different the injury severity at work zones. From the model, it can be concluded that some factors, including the road section with curve, alcohol/drugs involved, a high speed, angle crash and too young or old drivers are more likely to increase the probability of angle crashes. Based on the magnitudes of the variable coefficients, the factor of maximum posted speed have a great impact to injury severity, which shows restriction to driving speed is principle countermeasure for improving work zone safety.
| Author | : Sunanda Dissanayake |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2015 |
| Genre | : Roads |
| ISBN | : |
"The safe and efficient flow of traffic through work zones must be established by improving work zone conditions. Therefore, identifying the factors associated with the severity and the frequency of work zone crashes is important. According to current statistics from the Federal Highway Administration, 2,372 fatalities were associated with motor vehicle traffic crashes in work zones in the United States during the four years from 2010 to 2013. From 2002 to 2014, an average of 1,612 work zone crashes occurred in Kansas each year, making it a serious concern in Kansas. The objectives of this study were to analyze work zone crash characteristics, identify the factors associated with crash severity and frequency, and to identify recommendations to improve work zone safety. Work zone crashes in Kansas from 2010 to 2013 were used to develop crash severity models. Ordered probit regression was used to model the crash severities for daytime, nighttime, multi-vehicle and single-vehicle work zone crashes and for work zones crashes in general. Based on severity models, drivers from 26 to 65 years of age were associated with high crash severities during daytime work zone crashes and driver age was not found significant in nighttime work zone crashes. The use of safety equipment was related to reduced crash severities regardless of the time of the crash. Negative binomial regression was used to model the work zone crash frequency using work zones functioned in Kansas in 2013 and 2014. According to results, increased average daily traffic (AADT) was related to higher number of work zone crashes and work zones in operation at nighttime were related to a reduced number of work zone crashes. Findings of this study were used to provide general countermeasure ideas for improving safety of work zones" (page ii).
| Author | : Mohamed Osman |
| Publisher | : |
| Total Pages | : |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
Work zones are critical parts of the transportation infrastructure renewal process consisting of rehabilitation of roadways, maintenance, and utility work. Given the specific nature of a work zone (complex arrangements of traffic control devices and signs, narrow lanes, duration) a number of crashes occur with varying severities involving different vehicle sizes. This dissertation proposes a comprehensive discrete choice analysis of injury severity of crashes in work zones on both the crash and occupant levels, in roadway work zones through a comprehensive set of discrete choice econometric frameworks. Robust discrete choice modeling structures are introduced and applied in the field of work zone safety. This dissertation contains three (3) studies representing the empirical analysis conducted to address the following research questions:1. What factors may contribute to the injury severity levels of large-truck crashes in work zones? And what are the robust analytical methods to recognize such factors?2. How do specific work zone configurations affect factors contributing to the levels of injury severity of work zone crashes?3. How does the specific work zone-component-area where a crash has occurred affect factors contributing to the injury severity levels of work zone crashes?The first study investigates the causal factors contributing to injury severity of large truck crashes in work zones. The second study investigates the causal factors contributing to the injury severity of passenger-car occupants for crashes occurring in different work zone configurations (lane closure, lane shift/crossover, shoulder/median, intermittent, and other). The third study investigates the causal factors contributing to driver & rsquo;s injury severity in the different work zone component-areas (advance-warning, transition, activity, and termination areas). The first study compares a comprehensive set of discrete choice modeling structures; Multinomial Logit (MNL) model, Nested Logit (NL) model, Ordered Logit (ORL) model and Generalized Ordered Response Logit (GORL) model. The second and third studies developed the Mixed Generalized Ordered Response Probit (MGORP) modeling framework to conduct the proposed analysis to answer the second and third research questions. The empirical analysis was conducted using work zone crash database in 10 years of the Highway Safety Information System (HSIS).
| Author | : Ibrahim Alfallaj |
| Publisher | : |
| Total Pages | : 73 |
| Release | : 2014 |
| Genre | : Road work zones |
| ISBN | : |
Due to growth of vehicle travel using streets and highway systems in the United States, pavement repair and rehabilitation projects have increased. As a result, the presence of work zones has created traffic congestion and has increased the crash risk. The main object of this study was to identify significant factors that contribute to an increase in crash severity in the state of Ohio and recognize the most risk segment within the work zone locations. The work zone segment area is made of : (a) termination area (TA), (b) before the first work zone warning sign area (BWS), (c) advance warning area (AWA), (d) transition area (TSA), (e) activity area (AA). This study used a 5-year crash data from Ohio Department of Public Safety (ODPS) database from 2008 to 2012. In this study, classification tree modeling was used to investigate significant predictor variables of crash severity of work zone related crashes and recognize the most significant crash location within work zone areas in the state of Ohio. Classification tree modeling identified ten important variables (factors) that explain a large amount of the variation in the response variable, crash severity. These predictor variables of work zone crash severity identified include collision type, motorcycle related, work zone crashes type, posted speed limit, vehicle type, speed related, alcohol related, semi-truck related, youth related and road condition. In case of work zone location analysis results, this study identified six significant factors, which include collision type, work zone crash type, posted speed limit, vehicle type, workers present, and age of driver. Collision type is the most significant factor that affects crash severity in a work zone. Likewise, for work zone location, the work-zone crash type was the most significant factor that contributed in increasing the probability of work zone location crashes.
| Author | : Ozgur Ozturk |
| Publisher | : |
| Total Pages | : 231 |
| Release | : 2014 |
| Genre | : Road work zones |
| ISBN | : |
Work zone presence is an important concern for drivers in terms of safety and congestion. In recent years, work zone safety has received much attention due to numerous highway renovation projects that have resulted in many work zone crashes. To minimize the effect of work zones on roadway safety risks and traffic conditions, potential factors need to be addressed and countermeasures need to be implemented to ensure that the motorist can drive in a safe manner. The impact of the work zones can be estimated by using descriptive analysis and different statistical modeling methods. To this end, this study focused on three major areas: the crash frequency at work zones, the crash severity at work zones and the change in traffic conditions at work zones. Statistically robust models were developed by incorporating integrated datasets that could identify significant factors affecting each of these study areas. To better understand this, different from the previous studies, model results were compared against reference conditions, such as work zone crash frequency and modeling parameters were compared with non-work zone parameters. In addition, different statistical modeling techniques were applied to examine the best model or set of variables to connect crash severity and possible causative factors for binary level and multiple level outcomes. Two crash severity indexes were proposed and used to estimate multilevel crash severity by using both maximum severity and the monetary cost weighted severity. Besides safety issues, different types of lane closures and crashes observed within lane closures were studied to examine if there would be a change in traffic conditions compared with normal time traffic. Comparisons of each concept provides an idea for agencies about the differences of work zone and non-work zone conditions which is important if indeed there is a specific impact for the work zone cases. Work zone presence was found to have an increasing effect on crash occurrence. Nighttime shifts were found to be safer when compared to daytime work zone periods. Injury crashes for two-lane closure cases were found to have a more marked impact on traffic volume compared with other cases studied in this dissertation. In the conclusions chapter, all of these findings are summarized along with specific recommendations.
| Author | : Simon Washington |
| Publisher | : CRC Press |
| Total Pages | : 496 |
| Release | : 2020-01-30 |
| Genre | : Technology & Engineering |
| ISBN | : 0429520751 |
The book's website (with databases and other support materials) can be accessed here. Praise for the Second Edition: The second edition introduces an especially broad set of statistical methods ... As a lecturer in both transportation and marketing research, I find this book an excellent textbook for advanced undergraduate, Master’s and Ph.D. students, covering topics from simple descriptive statistics to complex Bayesian models. ... It is one of the few books that cover an extensive set of statistical methods needed for data analysis in transportation. The book offers a wealth of examples from the transportation field. —The American Statistician Statistical and Econometric Methods for Transportation Data Analysis, Third Edition offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics and to provide an increasing range of examples and corresponding data sets. It describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. It provides a wide breadth of examples and case studies, covering applications in various aspects of transportation planning, engineering, safety, and economics. Ample analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications. New to the Third Edition Updated references and improved examples throughout. New sections on random parameters linear regression and ordered probability models including the hierarchical ordered probit model. A new section on random parameters models with heterogeneity in the means and variances of parameter estimates. Multiple new sections on correlated random parameters and correlated grouped random parameters in probit, logit and hazard-based models. A new section discussing the practical aspects of random parameters model estimation. A new chapter on Latent Class Models. A new chapter on Bivariate and Multivariate Dependent Variable Models. Statistical and Econometric Methods for Transportation Data Analysis, Third Edition can serve as a textbook for advanced undergraduate, Masters, and Ph.D. students in transportation-related disciplines including engineering, economics, urban and regional planning, and sociology. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems.
| Author | : Kristin Kersavage |
| Publisher | : |
| Total Pages | : |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
Reducing the number and severity of crashes on highways and streets is of high importance for government officials and transportation professionals in the United States. Substantial research has focused on various speed metrics, such as operating speeds and the posted speed limit, and their relationship to safety, such as crash frequency and crash severity. Crash severity is the safety measure most often linked to measures of speed and is based on dissipation of kinetic energy. However, many aspects of the relationships between speed metrics and crash frequency and risk have yet to be studied in depth, so a complete understanding of speeding-related crashes is unknown. Design speeds are used to establish geometric design criteria, and operating speed results from the geometric design process. Posted speed limits may be established based on operating speeds or by statute. When posted speed limits are inconsistent with design or operating speeds, road safety performance may be affected. A more complete understanding of the relationship between safety performance and operating speeds, posted speed limits, and design speeds may produce rational speed limits and lead to improved safety performance on roadways.This research combined real-time vehicle probe speed data, roadway inventory data, and crash data to assess crash risk and crash frequency.This thesis first determined the risk of a crash on two-lane rural highways based on operating speed metrics, differences between speed metrics, and traffic volume data. Results from the crash risk analysis indicate that operating speeds in 1-minute and 5-minute averages improve the statistical fit and prediction of binary logistic regression models. Higher traffic volumes and operating speeds higher than either the road average speed or road reference speed were associated with increased crash risk. Whereas, variations in travel speeds between vehicles were associated with decreased crash risk. This thesis also analyzed the frequency of crashes on horizontal curve segments of two-lane rural roadways using operating speed data, differences among speed metrics, traffic volume data, roadway inventory data, and crash data. Negative binomial regression models improve the statistical fit and prediction of crash frequency models compared to random-effects negative binomial regression. Generally, increases in the differences between operating speed and road average speed and the differences between operating speed and inferred design were associated with an increase in crash frequency. Increases in the differences between inferred design speed and posted speed limit were also associated with an expected increase in crash frequency; however, increases in the operating speed variance and in the difference between operating speeds and posted speed limit were associated with an expected decrease in crash frequency.
| Author | : Nicholas J. Garber |
| Publisher | : |
| Total Pages | : 44 |
| Release | : 2002 |
| Genre | : Road work zones |
| ISBN | : |
Work zones tend to cause hazardous conditions for drivers and construction workers since they generate conflicts between construction activities and traffic. A clear understanding of the characteristics of work zone crashes will enhance the selection of the appropriate measures that can minimize the negative impacts of work zones. This study investigated the characteristics of work zone crashes that occurred in Virginia between 1996 and 1999. The information on each crash was obtained from the police crash record. The location of each crash was categorized as being in one of the five areas of a typical work zone: advance warning area, transition area, longitudinal buffer area, activity area, and termination area. An analysis of the percentage distributions was then carried out with respect to area in work zone, severity, type of collision, and type of highway. The proportionality test was used to determine significant differences at the 5 percent significance level. Selected crash characteristics, such as the proportions of single- and multi-vehicle crashes, were compared for work zone and non-work zone crashes. The results indicated that the activity area was the predominant location for work zone crashes regardless of highway type and that rear-end crashes were the predominant type of crash. The results also indicated that the proportion of sideswipe same direction crashes in the transition area was significantly higher than in the advance warning area and that work zone crashes involved a higher proportion of multi-vehicle crashes and fatal crashes than did non-work zone crashes.
| Author | : Azad Salim Abdulhafedh |
| Publisher | : |
| Total Pages | : 243 |
| Release | : 2016 |
| Genre | : |
| ISBN | : |
Modeling crash severity is an important component of reasoning about the issues that may affect highway safety. A better understanding of the factors underlying crash severity can be used to reduce the degree of crash severity injury, locate road hazardous sites, and adopt suitable countermeasures. In order to provide insights on the mechanism and behavior of the crash severity injury, a variety of statistical approaches have been utilized to model the relationship between crash severity and potential risk factors. Many of the traditional approaches for analyzing crash severity are limited in that they are based on the assumption that all observations are independent of each other. However, given the reality of vehicle movement in networked systems, the assumption of independence of crash incidence is not likely valid. For instance, spatial and temporal autocorrelations are important sources of dependency among observations that may bias estimates if not considered in the modeling process. Moreover, there are other aspects of vehicular travel that may influence crash severity that have not been explored in traditional analysis approaches. One such aspect is the roadway visibility that is available to a driver at a given time that can impact their ability to react to changing traffic conditions, a characteristics known as sight distance. Accounting for characteristics such as sight distance in crash severity modeling involve moving beyond statistical analysis and modeling the complex geospatial relationships between the driver and the surrounding landscape. To address these limitations of traditional approaches to crash severity modeling, this dissertation first details a framework for detecting temporal and spatial autocorrelation in crash data. An approach for evaluating the sight distance available to drivers along roadways is then proposed. Finally, a crash severity model is developed based upon a multinomial logistic regression approach that incorporates the available sight distance and spatial autocorrelation as potential risk factors, in addition to a wide range of other factors related to road geometry, traffic volume, driver's behavior, environment, and vehicles. To demonstrate the characteristics of the proposed model, an analysis of vehicular crashes (years 2013-2015) along the I-70 corridor in the state of Missouri (MO) and on roadways in Boone County MO is conducted. To assess existing stopping sight distance and decision sight distance on multilane highways, a geographic information system (GIS)-based viewshed analysis is developed to identify the locations that do not conform to AASHTO (2011) criteria regarding stopping and decision sight distances, which could then be used as potential risk factors in crash prediction. Moreover, this method provides a new technique for estimating passing sight distance along two-lane highways, and locating the passing zones and no-passing zones. In order to detect the existence of temporal autocorrelation and whether it's significant in crash data, this dissertation employs the Durbin-Watson (DW) test, the Breusch-Godfrey (LM) test, and the Ljung-Box Q (LBQ) test, and then describes the removal of any significant amount of temporal autocorrelation from crash data using the differencing procedure, and the Cochrane-Orcutt method. To assess whether vehicle crashes are spatially clustered, dispersed, or random, the Moran's I and Getis-Ord Gi* statistics are used as measures of spatial autocorrelation among vehicle incidents. To incorporate spatial autocorrelation in crash severity modeling, the use of the Gi* statistic as a potential risk factor is also explored. The results provide firm evidence on the importance of accounting for spatial and temporal autocorrelation, and sight distance in modeling traffic crash data.
