A Novel Approach To Modeling And Predicting Crash Frequency At Rural Intersections By Crash Type And Injury Severity Level

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A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level

Author : Jun Deng (Writer on transportation)
Publisher :
ISBN 13 :
Total Pages : 112 pages
Book Rating : 4.:/5 (874 download)

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Book Synopsis A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level by : Jun Deng (Writer on transportation)

Download or read book A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level written by Jun Deng (Writer on transportation) and published by . This book was released on 2013 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Safety at intersections is of significant interest to transportation professionals due to the large number of possible conflicts that occur at those locations. In particular, rural intersections have been recognized as one of the most hazardous locations on roads. However, most models of crash frequency at rural intersections, and road segments in general, do not differentiate between crash type (such as angle, rear-end or sideswipe) and injury severity (such as fatal injury, non-fatal injury, possible injury or property damage only). Thus, there is a need to be able to identify the differential impacts of intersection-specific and other variables on crash types and severity levels. This thesis builds upon the work of Bhat et al., (2013b) to formulate and apply a novel approach for the joint modeling of crash frequency and combinations of crash type and injury severity. The proposed framework explicitly links a count data model (to model crash frequency) with a discrete choice model (to model combinations of crash type and injury severity), and uses a multinomial probit kernel for the discrete choice model and introduces unobserved heterogeneity in both the crash frequency model and the discrete choice model, while also accommodates excess of zeros. The results show that the type of traffic control and the number of entering roads are the most important determinants of crash counts and crash type/injury severity, and the results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects.

A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level

Author : Jun Deng (Writer on transportation)
Publisher :
ISBN 13 :
Total Pages : 48 pages
Book Rating : 4.:/5 (922 download)

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Book Synopsis A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level by : Jun Deng (Writer on transportation)

Advanced Statistical Modeling of the Frequency and Severity of Traffic Crashes on Rural Highways

Author : Irfan Uddin Ahmed
Publisher :
ISBN 13 :
Total Pages : 222 pages
Book Rating : 4.4/5 (387 download)

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Book Synopsis Advanced Statistical Modeling of the Frequency and Severity of Traffic Crashes on Rural Highways by : Irfan Uddin Ahmed

Download or read book Advanced Statistical Modeling of the Frequency and Severity of Traffic Crashes on Rural Highways written by Irfan Uddin Ahmed and published by . This book was released on 2022 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary objective of practitioners working on traffic safety is to reduce the number and severity of crashes. The Highway Safety Manual (HSM) provides practitioners with analytical tools and techniques to estimate the expected crash frequency and severity with the aim to identify and evaluate safety countermeasures. Expected crash frequency can be estimated using Safety Performance Functions (SPFs) provided in Part C of the HSM. The HSM provides simple SPFs which are developed using the most frequently used crash counts model, the negative binomial regression model. The rural nature of Wyoming highways coupled with the mountainous terrain (i.e., challenging roadway geometry) make the HSM basic SPFs unsuitable to determine crash contributing factors for Wyoming conditions. In this regard, the objective of this study is to implement advanced statistical methods such as the different functional forms of Negative Binomial, and Bayesian approach, to develop crash prediction models, investigate crash contributing factors, and determine the impact of safety countermeasures. Bayesian statistics in combination with the power of Markov Chain Monte Carlo (MCMC) sampling techniques provide frameworks to model small sample datasets and complex models at the same time, where the traditional Maximum Likelihood Estimation (MLE) based methods tend to fail. As such, a novel No-U-Turn Sampler for Hamiltonian Monte Carlo (NUTS HMC) sampling technique in a Bayesian framework was utilized to investigate the crash frequency, injury severity of crashes on the interstate freeways and some rural highways in Wyoming. The Poisson and the Negative Binomial (NB) models are the most commonly used regression models in traffic safety analysis. The advantage of the NB model can be further enhanced by providing different functional forms of the variance and the dispersion structure. The NB-2 is the most common form of the NB model, typically used in developing safety performance functions (SPFs) largely due to the mean-variance quadratic relationship. However, studies in the literature have shown that the mean-variance relationship could be unrestrained. Another introduced formulation of the NB model is NB-1, which assumes that there is a constant ratio linking the mean and the variance of the crash frequencies. A more general type of the NB model is the NB-P model, which does not constrain the mean-variance relationship. Thus, leveraging the power of this unrestrained mean-variance relationship, more accurate safety models could be developed, and these would lead to more accurate estimation of crash risk and benefits of potential solutions. This study will help practitioners to implement advanced methodologies to solve traffic safety problems of rural highways that have plagued the researchers for a long time now. The methodologies proposed in this study will help practitioners to replace the outdated and inefficient traditional models and obtain more accurate traffic safety models to predict crashes and the resulting crash injury severity. Moreover, this research quantified the safety effectiveness of some unique countermeasures on rural highways.

Highway Safety Manual

Author :
Publisher : AASHTO
ISBN 13 : 1560514779
Total Pages : 886 pages
Book Rating : 4.5/5 (65 download)

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Book Synopsis Highway Safety Manual by :

Download or read book Highway Safety Manual written by and published by AASHTO. This book was released on 2010 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Highway Safety Manual (HSM) is a resource that provides safety knowledge and tools in a useful form to facilitate improved decision making based on safety performance. The focus of the HSM is to provide quantitative information for decision making. The HSM assembles currently available information and methodologies on measuring, estimating and evaluating roadways in terms of crash frequency (number of crashes per year) and crash severity (level of injuries due to crashes). The HSM presents tools and methodologies for consideration of 'safety' across the range of highway activities: planning, programming, project development, construction, operations, and maintenance. The purpose of this is to convey present knowledge regarding highway safety information for use by a broad array of transportation professionals"--p. xxiii, vol. 1.

Statistical Methods and Modeling and Safety Data, Analysis, and Evaluation

Author : National Research Council (U.S.). Transportation Research Board
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.:/5 ( download)

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Book Synopsis Statistical Methods and Modeling and Safety Data, Analysis, and Evaluation by : National Research Council (U.S.). Transportation Research Board

Download or read book Statistical Methods and Modeling and Safety Data, Analysis, and Evaluation written by National Research Council (U.S.). Transportation Research Board and published by . This book was released on 2003 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers empirical approaches to outlier detection in intelligent transportation systems data, modeling of traffic crash-flow relationships for intersections, profiling of high-frequency accident locations by use of association rules, analysis of rollovers and injuries with sport utility vehicles, and automated accident detection at intersections via digital audio signal processing.

Modelling Crash Frequency and Severity Using Global Positioning System Travel Data

Author : Joshua Stipancic
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (111 download)

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Book Synopsis Modelling Crash Frequency and Severity Using Global Positioning System Travel Data by : Joshua Stipancic

Download or read book Modelling Crash Frequency and Severity Using Global Positioning System Travel Data written by Joshua Stipancic and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Improving road safety requires accurate network screening methods to identify and prioritize sites to maximize effectiveness of implemented countermeasures. In screening, hotspots are commonly identified using statistical models based on historical crash data. However, collision databases are subject to errors and omissions and crash-based methods are reactive. With the arrival of Global Positioning System (GPS) trajectory data, surrogate safety methods, proactive by nature, have gained popularity. Although GPS-enabled smartphones can collect reliable and spatio-temporally rich driving data from regular drivers using an inexpensive, simple, and user-friendly tool, few studies to date have analyzed large volumes of smartphone GPS data and considered surrogate-safety modelling techniques for network screening. The main objective of this thesis is to propose and validate a GPS-based network screening modeling framework dependent on surrogate safety measures (SSMs). First, methods for collecting and processing GPS and associated data sources are presented. Data, collected in Quebec City and capturing 4000 drivers and 21,000 trips, was processed using map matching and speed filtering algorithms. Spatio-temporal congestion measures were proposed and extracted and techniques for visualizing congestion patterns at aggregate and disaggregate levels were explored. Results showed that each peak period has an onset period and dissipation period lasting one hour. Congestion in the evening is greater and more dispersed than in the morning. Congestion on motorways, arterials, and collectors is most variable during peak periods. Second, various event-based and traffic flow SSMs are proposed and correlated with historical collision frequency and severity using Spearman's correlation coefficient and pairwise Kolmogorov-Smirnov tests, respectively. For example, hard braking (HBEs) and accelerating events (HAEs) were positively correlated with crash frequency, though correlations were much stronger at intersections than at links. Higher numbers of these vehicle manoeuvres were also related to increased collision severity. Considered traffic flow SSMs included congestion index (CI), average speed (V̄), and coefficient of variation of speed (CVS). CI was positively correlated with crash frequency and showed a non-monotonous relationship with severity. V̄ was negatively correlated with crash frequency and had no conclusive statistical relationship with crash severity. CVS was positively related to increased crash frequency and severity. Third, a mixed-multivariate model was developed to predict crash frequency and severity incorporating GPS-derived SSMs as predictive variables. The outcome is estimated using two models; a crash frequency model using a Full Bayes approach and estimated using the Integrated Nested Laplace Approximation (INLA) approach and a crash severity model integrated through a fractional Multinomial Logit model. The results are combined to generate posterior expected crash frequency at each severity level and rank sites based on crash cost. Negative Binomial models outperformed alternative models based on a sample of the network, and including spatial effects showed improvement in model fit. This crash frequency model was shown to be accurate at the network scale, with the majority of proposed SSMs statistically significant at 95 % confidence. In the crash severity model, fewer variables were significant, yet the effect of all significant variables was consistent with previous results. Correlations between rankings predicted by the model and by the crash data were adequate for intersections (0.46) but were poorer for links (0.25). The inclusion of severity, which is an independent dimension of safety, is a substantial improvement over many existing studies, and the ability to prioritize sites based on GPS data and SSMs rather than historical crash data represents a substantial contribution to the field of road safety." --

Highway and Traffic Safety

Author : National Research Council (U.S.). Transportation Research Board
Publisher :
ISBN 13 :
Total Pages : 148 pages
Book Rating : 4.X/5 (4 download)

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Book Synopsis Highway and Traffic Safety by : National Research Council (U.S.). Transportation Research Board

Download or read book Highway and Traffic Safety written by National Research Council (U.S.). Transportation Research Board and published by . This book was released on 2000 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation Research Record contains the following papers: Method for identifying factors contributing to driver-injury severity in traffic crashes (Chen, WH and Jovanis, PP); Crash- and injury-outcome multipliers (Kim, K); Guidelines for identification of hazardous highway curves (Persaud, B, Retting, RA and Lyon, C); Tools to identify safety issues for a corridor safety-improvement program (Breyer, JP); Prediction of risk of wet-pavement accidents : fuzzy logic model (Xiao, J, Kulakowski, BT and El-Gindy, M); Analysis of accident-reduction factors on California state highways (Hanley, KE, Gibby, AR and Ferrara, T); Injury effects of rollovers and events sequence in single-vehicle crashes (Krull, KA, Khattack, AJ and Council, FM); Analytical modeling of driver-guidance schemes with flow variability considerations (Kaysi, I and Ail, NH); Evaluating the effectiveness of Norway's speak out! road safety campaign : The logic of causal inference in road safety evaluation studies (Elvik, R); Effect of speed, flow, and geometric characteristics on crash frequency for two-lane highways (Garber, NJ and Ehrhart, AA); Development of a relational accident database management system for Mexican federal roads (Mendoza, A, Uribe, A, Gil, GZ and Mayoral, E); Estimating traffic accident rates while accounting for traffic-volume estimation error : a Gibbs sampling approach (Davis, GA); Accident prediction models with and without trend : application of the generalized estimating equations procedure (Lord, D and Persaud, BN); Examination of methods that adjust observed traffic volumes on a network (Kikuchi, S, Miljkovic, D and van Zuylen, HJ); Day-to-day travel-time trends and travel-time prediction form loop-detector data (Kwon, JK, Coifman, B and Bickel, P); Heuristic vehicle classification using inductive signatures on freeways (Sun, C and Ritchie, SG).

Exploration of Advances in Statistical Methodologies for Crash Count and Severity Prediction Models

Author : Kai Wang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)

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Book Synopsis Exploration of Advances in Statistical Methodologies for Crash Count and Severity Prediction Models by : Kai Wang

Download or read book Exploration of Advances in Statistical Methodologies for Crash Count and Severity Prediction Models written by Kai Wang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This report first describes the use of different copula based models to simultaneously estimate the two crash indicators: injury severity and vehicle damage. The Gaussian copula model outperforms the other copula based model specifications (i.e. Gaussian, Farlie-Gumbel-Morgenstern (FGM), Frank, Clayton, Joe and Gumbel copula models), and the results indicate that injury severity and vehicle damage are highly correlated, and the correlations between injury severity and vehicle damage varied with different crash characteristics including manners of collision and collision types. This study indicates that the copula-based model can be considered to get a more accurate model structure when simultaneously estimating injury severity and vehicle damage in crash severity analyses. The second part of this report describes estimation of cluster based SPFs for local road intersections and segments in Connecticut using socio-economic and network topological data instead of traffic counts as exposure. The number of intersections and the total local roadway length were appropriate to be used as exposure in the intersection and segment SPFs, respectively. Models including total population, retail and non-retail employment and average household income are found to be the best both on the basis of model fit and out of sample prediction. The third part of this report describes estimation of crashes by both crash type and crash severity on rural two-lane highways, using the Multivariate Poisson Lognormal (MVPLN) model. The crash type and crash severity counts are significantly correlated; the standard errors of covariates in the MVPLN model are slightly lower than the other two univariate crash prediction models (i.e. Negative Binomial model and Univariate Poisson Lognormal model) when the covariates are statistically significant; and the MVPLN model outperforms the UPLN and NB models in crash count prediction accuracy. This study indicates that when simultaneously predicting crash counts by crash type and crash severity for rural two-lane highways, the MVPLN model should be considered to avoid estimation error and to account for the potential correlations among crash type counts and crash severity counts.

Estimation of Crash Type Frequency Accounting for Misclassification in Crash Data

Author : Asif Mahmud
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (138 download)

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Book Synopsis Estimation of Crash Type Frequency Accounting for Misclassification in Crash Data by : Asif Mahmud

Download or read book Estimation of Crash Type Frequency Accounting for Misclassification in Crash Data written by Asif Mahmud and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Individual crash types have different underlying causes and thus the relationships between roadway/traffic characteristics and crash frequency are likely to differ across unique crash types. Two statistical methods -- univariate and multivariate formulations -- have been widely used so far by researchers in estimating the impact of contributing factors on different crash types. Addressing the limitations of these methods, recently a two-stage approach has been proposed in which one model is estimated to predict the total crash frequency and its prediction is combined with another model which predicts the proportions of different crash types. More efficient one-stage joint models, in which both the frequency and proportion models are estimated simultaneously and predictions are provided more directly, have also been proposed for macro-level analysis. This study investigates the performance of this joint modeling paradigm in analyzing unique crash type frequencies on individual road segments. Moreover, this study also proposes the use of a multinomial logit (MNL) model to estimate the proportion of different collision types, which has never been done in safety literature. This study compares the performance of all these methods in predicting crash frequency by crash type on two-way two-lane urban-suburban collector roadway segments in Pennsylvania. While the methodologies of crash type frequency estimation are well-established, less focus has been given on the quality of the crash dataset they are applied on. Crash misclassification (MC) -- e.g., a crash of one type or severity being mistakenly miscategorized as another -- is a relatively common problem in transportation safety. Crash frequency models for individual crash categories estimated using datasets with MC errors could result in biased parameter estimates and thus lead to ineffective countermeasure planning. This study proposes a novel methodological formulation to directly account for this MC error and incorporates it into the two most common count data models used for crash frequency prediction: Poisson and Negative Binomial (NB) regression. The proposed framework introduces probabilistic MC rates among different crash types and modifies the likelihood function of the count models accordingly. The study also demonstrates how this approach can be integrated into reformulated models that express each count model as a discrete choice model. The capability of the proposed models to estimate true parameters, given the existence of MC error, is examined via simulation analysis. Then, the proposed models are applied to empirical data to examine the presence of MC in crash data and further examine the robustness of the proposed models. Lastly, the ability of the proposed models in accounting for underreporting, another acute problem in crash data, is examined through comparing its performance with that from established frameworks.

Analyzing Crash Frequency and Severity Data Using Novel Techniques

Author : Gaurav Satish Mehta
Publisher :
ISBN 13 :
Total Pages : 158 pages
Book Rating : 4.:/5 (94 download)

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Book Synopsis Analyzing Crash Frequency and Severity Data Using Novel Techniques by : Gaurav Satish Mehta

Download or read book Analyzing Crash Frequency and Severity Data Using Novel Techniques written by Gaurav Satish Mehta and published by . This book was released on 2014 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing safe travel from one point to another is the main objective of any public transportation agency. The recent publication of the Highway Safety Manual (HSM) has resulted in an increasing emphasis on the safety performance of specific roadway facilities. The HSM provides tools such as crash prediction models that can be used to make informed decisions. The manual is a good starting point for transportation agencies interested in improving roadway safety in their states. However, the models published in the manual need calibration to account for the local driver behavior and jurisdictional changes. The method provided in the HSM for calibrating crash prediction models is not scientific and has been proved inefficient by several studies. To overcome this limitation this study proposes two alternatives. Firstly, a new method is proposed for calibrating the crash prediction models using negative binomial regression. Secondly, this study investigates new forms of state-specific Safety Performance Function SPFs using negative binomial techniques. The HSM's 1st edition provides a multiplier applied to the univariate crash prediction models to estimate the expected number of crashes for different crash severities. It does not consider the distinct effect unobserved heterogeneity might have on crash severities. To address this limitation, this study developed a multivariate extension of the Conway Maxwell Poisson distribution for predicting crashes. This study gives the statistical properties and the parameter estimation algorithm for the distribution. The last part of this dissertation extends the use of Highway Safety Manual by developing a multivariate crash prediction model for the bridge section of the roads. The study then compares the performance of the newly proposed multivariate Conway Maxwell Poisson (MVCMP) model with the multivariate Poisson Lognormal, univariate Conway Maxwell Poisson (UCMP) and univariate Poisson Lognormal model for different crash severities. This example will help transportation researchers in applying the model correctly.

Highway Safety Analytics and Modeling

Author : Dominique Lord
Publisher : Elsevier
ISBN 13 : 0128168196
Total Pages : 504 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Highway Safety Analytics and Modeling by : Dominique Lord

Download or read book Highway Safety Analytics and Modeling written by Dominique Lord and published by Elsevier. This book was released on 2021-02-27 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highway Safety Analytics and Modeling comprehensively covers the key elements needed to make effective transportation engineering and policy decisions based on highway safety data analysis in a single. reference. The book includes all aspects of the decision-making process, from collecting and assembling data to developing models and evaluating analysis results. It discusses the challenges of working with crash and naturalistic data, identifies problems and proposes well-researched methods to solve them. Finally, the book examines the nuances associated with safety data analysis and shows how to best use the information to develop countermeasures, policies, and programs to reduce the frequency and severity of traffic crashes. Complements the Highway Safety Manual by the American Association of State Highway and Transportation Officials Provides examples and case studies for most models and methods Includes learning aids such as online data, examples and solutions to problems

Modeling Multilevel Data in Traffic Safety

Author : Hoong Chor Chin
Publisher : Nova Science Publishers
ISBN 13 : 9781606922705
Total Pages : 0 pages
Book Rating : 4.9/5 (227 download)

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Book Synopsis Modeling Multilevel Data in Traffic Safety by : Hoong Chor Chin

Download or read book Modeling Multilevel Data in Traffic Safety written by Hoong Chor Chin and published by Nova Science Publishers. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Background: In the study of traffic system safety, statistical models have been broadly applied to establish the relationships between the traffic crash occurrence and various risk factors. Most of the existing methods, such as the generalised linear regression models, assume that each observation (e.g. a crash or a vehicle involvement) in the estimation procedure corresponds to an individual situation. Hence, the residuals from the models exhibit independence. Problem: However, this "independence" assumption may often not hold true since multilevel data structures exist extensively because of the data collection and clustering process. Disregarding the possible within-group correlations may lead to production of models with unreliable parameter estimates and statistical inferences. Method: Following a literature review of crash prediction models, this book proposes a 5 T-level hierarchy, viz. (Geographic region level -- Traffic site level -- Traffic crash level -- Driver-vehicle unit level -- Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To model properly the potential between-group heterogeneity due to the multilevel data structure, a framework of hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is employed. Bayesian inference using Markov chain Monte Carlo algorithm is developed to calibrate the proposed hierarchical models. Two Bayesian measures, viz. the Deviance Information Criterion and Cross-Validation Predictive Densities, are adapted to establish the model suitability. Illustrations: The proposed method is illustrated using two case studies in Singapore: 1) a crash-frequency prediction model which takes into account Traffic site level and Time level; 2) a crash-severity prediction model which takes into account Traffic crash level and Driver-vehicle unit level. Conclusion: Comparing the predictive abilities of the proposed models against those of traditional methods, the study demonstrates the importance of accounting for the within-group correlations and illustrates the flexibilities and effectiveness of the Bayesian hierarchical approach in modelling multilevel structure of traffic safety data.

Cross-section Fatal Crash Type Prediction Models

Author : Hong Zhu
Publisher :
ISBN 13 :
Total Pages : 656 pages
Book Rating : 4.:/5 (635 download)

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Book Synopsis Cross-section Fatal Crash Type Prediction Models by : Hong Zhu

Download or read book Cross-section Fatal Crash Type Prediction Models written by Hong Zhu and published by . This book was released on 2010 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rural two-lane highway in the southeastern United States is frequently associated with a disproportionate number of serious and fatal crashes. The major research objectives are to investigate the relations between probabilities of fatal crash type occurrence and potential contributing factors from road geometric design characteristics and roadside, environmental features. This dissertation analyzes the regional fatal crash database and successfully develops statistical models to examine the relations and provided meaningful research findings. This dissertation contributes to current traffic safety analysis by directly examining the connection between major fatal crash type occurrence and roadway geometrics, roadside characteristics, and environmental conditions through a regional case study. This study effort addresses the less understood relationship between fatal crash types and road features compared to other crash measures, such as crash frequency, crash rate, and injury severity. The developed fatal crash type prediction models not only demonstrate strong connections between crash types and road characteristics, but also provide a quantitative assessment tool for countermeasures in terms of reduction of fatal crash type occurrence. Since most countermeasures are more effective at mitigating certain type of crashes, the information revealed from the crash type prediction models help clarify the relationship between candidate countermeasures and expected crash reductions.

Safety Data, Analysis, and Evaluation

Author :
Publisher :
ISBN 13 : 9780309369367
Total Pages : 0 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Safety Data, Analysis, and Evaluation by :

Download or read book Safety Data, Analysis, and Evaluation written by and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "TRB?s Transportation Research Record: Journal of the Transportation Research Board, No. 2514, explores 19 papers related to safety data, analysis, and evaluation in the transportation sector, including: Exploring Driver Error at Intersections: Key Contributors and Solutions; Level of Service of Safety Revisited; Longitudinal Analysis of Rural Interstate Fatalities in Relation to Speed Limit Policies; Predicting Crashes on Expressway Ramps with Real-Time Traffic and Weather Data; Multilevel Logistic Regression Modeling for Crash Mapping in Metropolitan Areas; Simulated Traffic Conflicts: Do They Accurately Represent Field-Measured Conflicts?; Assessing Safety Improvements to Pedestrian Crossings Using Automated Conflict Analysis; Understanding Factors Affecting Frequency of Traffic Conflicts Between Electric Bicycles and Motorized Vehicles at Signalized Intersections; Comparative Analysis of Injury Severity Resulting from Pedestrian?Motor Vehicle and Bicycle?Motor Vehicle Crashes on Roadways in Alabama; Validation of Crash Modification Factors Derived from Cross-Sectional Studies with Regression Models; Fault Determination for Crashes in Vermont: Implications of Distance from Home; Crash Patterns at Signalized Intersections; Analyses of Multiyear Statewide Secondary Crash Data and Automatic Crash Report Reviewing; Assessment of Pedestrian Risk at Crossings with Kinematic?Probabilistic Model; Predicting Driver Injury Severity in Single-Vehicle and Two-Vehicle Crashes with Boosted Regression Trees; Effects of Geodemographic Profiles of Drivers on Their Injury Severity from Traffic Crashes Using Multilevel Mixed-Effects Ordered Logit Model; Copula-Based Joint Model of Injury Severity and Vehicle Damage in Two-Vehicle Crashes; Identifying Optimal High-Risk Driver Segments for Safety Messaging: Geodemographic Modeling Approach; Evaluation of Signalized-Intersection Crash Screening Methods Based on Distance from Intersection."--Publisher's description.

Pedestrian Crash Prediction and Analyzing Contributing Factors Across Texas

Author : Mostaq Ahmed (M.S. in Community and Regional Planning)
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Book Synopsis Pedestrian Crash Prediction and Analyzing Contributing Factors Across Texas by : Mostaq Ahmed (M.S. in Community and Regional Planning)

Download or read book Pedestrian Crash Prediction and Analyzing Contributing Factors Across Texas written by Mostaq Ahmed (M.S. in Community and Regional Planning) and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study applied tree-based machine learning methods to investigate the contributing factors to both crash frequency and injury severity in vehicle-pedestrian crash events. Vehicle and roadway characteristics, driver and pedestrian attributes, traffic controls and land use conditions, transit provision and weather conditions are used as covariates to predict pedestrian crash frequencies (by roadway segment) and injury severity levels (for pedestrians struck by vehicles on public roadways). In both cases, tree-based models offered significantly more prediction accuracy than traditional statistical models (using negative binomial and ordered probit specifications, with the same covariates). The tree-based models also offer valuable interpretability through the regression tree graph itself (with clear branching based on variable cut-points), variable importance plots (for each covariate), and partial dependence plots to help analysts understand the relationship between contributing factors and the target variable (count or severity). Average daily vehicle-miles travelled (DVMT) on each road segment, population density, segment length, census tract-level job density, distance from nearest K-12 school, transit stop density, and segment speed limits were estimated to be the top contributing factors for increasing pedestrian crash counts. DVMT has been found as the single most responsible factor for vehicle-pedestrian crashes and in a way representing pedestrian exposure to such situations. In terms of predicting injury outcomes, intoxication of the pedestrian and/or driver, higher speed limits at the site, crash location not being in the traffic way, older pedestrian, interstate highway locations, and dark and unlit conditions were predictors for more severe outcomes. Importantly, if the surrounding urban area’s population is reasonably high (over 25,000 persons), the probability of the pedestrian dying falls significantly, which supports the ‘safety in numbers’ idea, for more people available to help save the crash victims, or drivers going more slowly due to crowded conditions, closer hospitals, and so on. While few crash studies have included land use variables and local demographics, including proximity to schools, hospitals, and transit stops, population and jobs density variables appeared to add to crash counts and severity for pedestrians, though this is moderated by the 25,000-population threshold and distance variables

Validation of Accident Models for Intersections

Author : Simon Washington
Publisher :
ISBN 13 :
Total Pages : 316 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Validation of Accident Models for Intersections by : Simon Washington

Download or read book Validation of Accident Models for Intersections written by Simon Washington and published by . This book was released on 2005 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report describes the results of validation and calibration of motor vehicle crash models for rural intersections. Both the validation and recalibration activities were conducted in pursuit of one overriding research objective, which was to make marginal improvements to an existing set of statistical models for predicting crashes at two and four lane intersections, with the primary intent to be used in the Interactive Highway Safety Design Module (IHSDM). The five types of intersection models for which conclusions are drawn and recommendations are made are: Three-legged stop controlled intersections of two-lane roads; four-legged stop controlled intersections of two-lane roads; three-legged stop controlled intersections with two lanes on minor and four lanes on major road; and four-legged stop controlled intersections with two lanes on minor and four lanes on major road, and signalized intersections of two-lane roads.

Estimating Calibration Factors and Developing Calibration Functions for the Prediction of Crashes at Urban Intersections in Kansas

Download Estimating Calibration Factors and Developing Calibration Functions for the Prediction of Crashes at Urban Intersections in Kansas PDF Online Free

Author : Rijesh Karmacharya
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (111 download)

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Book Synopsis Estimating Calibration Factors and Developing Calibration Functions for the Prediction of Crashes at Urban Intersections in Kansas by : Rijesh Karmacharya

Download or read book Estimating Calibration Factors and Developing Calibration Functions for the Prediction of Crashes at Urban Intersections in Kansas written by Rijesh Karmacharya and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.