scholarly journals Safety Evaluation of Freeway Speed-Change Lanes Based on Crashes and Simulated Conflicts

2021 ◽  
Author(s):  
Lei Qin
Keyword(s):  
Traffic Control ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Negative Binomial ◽  
Prediction Models ◽  
Control Strategies ◽  
Safety Evaluation ◽  
Safety Performance ◽  
Assessment Model ◽  
Crash Prediction Models

To facilitate the evaluation of the safety performance of freeway merge, diverge, and weave areas, conventional crash-based Safety Performance Functions (SPFs) were developed using generalized linear models (GLM) with a negative binomial (NB) error structure. However, crash-based SPFs may not take into account all factors that contribute to the crashes. The use of simulated conflicts as a surrogate safety measure to predict crashes can address this issue and provide recommendations for the designs and traffic control strategies. This approach was explored by using Surrogate Safety Assessment Model (SSAM) and VISSIM software to generate and analyze conflicts for merge areas on Ontario freeways. Crash-conflict integrated SPFs with different Time to Collision (TTC) thresholds were then developed and compared. Their predictive capabilities were also evaluated. To complement this analysis, the transferability of US crash prediction models to Ontario data was evaluated and the goodness-of-fit of these models was explored.

scholarly journals Safety Evaluation of Freeway Speed-Change Lanes Based on Crashes and Simulated Conflicts

2021 ◽  
Author(s):  
Lei Qin
Keyword(s):  
Traffic Control ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Negative Binomial ◽  
Prediction Models ◽  
Control Strategies ◽  
Safety Evaluation ◽  
Safety Performance ◽  
Assessment Model ◽  
Crash Prediction Models

To facilitate the evaluation of the safety performance of freeway merge, diverge, and weave areas, conventional crash-based Safety Performance Functions (SPFs) were developed using generalized linear models (GLM) with a negative binomial (NB) error structure. However, crash-based SPFs may not take into account all factors that contribute to the crashes. The use of simulated conflicts as a surrogate safety measure to predict crashes can address this issue and provide recommendations for the designs and traffic control strategies. This approach was explored by using Surrogate Safety Assessment Model (SSAM) and VISSIM software to generate and analyze conflicts for merge areas on Ontario freeways. Crash-conflict integrated SPFs with different Time to Collision (TTC) thresholds were then developed and compared. Their predictive capabilities were also evaluated. To complement this analysis, the transferability of US crash prediction models to Ontario data was evaluated and the goodness-of-fit of these models was explored.

Safety Performance of One-Way Arterials

2020 ◽  
Vol 2674 (10) ◽  
pp. 548-559
Author(s):  
Srinivas R. Geedipally ◽  
Dominique Lord ◽  
Michael P. Pratt ◽  
Kay Fitzpatrick ◽  
Eun Sug Park
Keyword(s):  
Predictive Models ◽  
Traffic Control ◽  
Injury Severity ◽  
Negative Binomial ◽  
Prediction Models ◽  
Distribution Functions ◽  
Safety Performance ◽  
Safety Performance Function ◽  
Traffic Characteristics ◽  
Wide Range

Safety analysts are generally interested in understanding the differences in the safety performance when a two-way street is converted to a one-way operation or vice-versa. Literature exists to understand and predict the safety of two-way streets. However, safety prediction procedures are currently not available for assessing the safety performance of one-way arterials. This research was undertaken to develop safety prediction models for one-way arterials. To accomplish this objective, data collected in California, Illinois, Michigan, Oregon, and Texas were assembled that included a wide range of geometric design features, traffic control features, traffic characteristics, and crash records. The data were used to calibrate predictive models, each of which included a safety performance function (SPF) and several crash modification factors (CMFs). Separate SPFs were developed for fatal and injury crashes (i.e., fatal, incapacitating injury, non-incapacitating injury, and possible injury crash) and property-damage-only crashes. The SPFs were estimated using the negative binomial modeling structure. Severity distribution functions (SDFs) were also calibrated using the fatal and injury data. These functions can be used with the predictive models to estimate the expected crash frequency for each of four injury severity levels.

LOSS Evaluation for Continuous Downgrades Segments Based on Accident Frequency Prediction

2014 ◽  
Vol 505-506 ◽  
pp. 1061-1066
Author(s):  
Yi Xuan Sun ◽  
Chun Fu Shao ◽  
Meng Meng ◽  
Song Shou Ouyang
Keyword(s):  
Traffic Safety ◽  
Evaluation Method ◽  
Negative Binomial ◽  
Prediction Models ◽  
Safety Evaluation ◽  
Safety Performance ◽  
Accident Frequency ◽  
Sample Segment ◽  
Level 3 ◽  
Geometrical Factors

In order to evaluate traffic safety performance of continuous downgrades segment more accurately and quantitatively, a new safety evaluation method namely level of safety service (LOSS) is introduced. Based on the current traffic safety situation in China, the LOSS definition and classification method are studied systematically. In this paper, LOSS is built as a 5 levels framework and the graded threshold values are derived from accident frequency prediction models. The empirical research dataset includes 322 accidents data on a 15.27km continuous downgrades segment. The dataset is grouped into 16 fixed longitudinal grade sections to highlight the geometrical characteristics. Negative binomial model is best fitted among four candidate models, while the parameter estimation result indicates that geometrical factors, oversize vehicles mixed rate and average speed have significant positive effect on accident frequency. The overall LOSS of sample segment locates into the Level 3 interval, which means less safety performance than expected. As an extended application, LOSS specific to each fixed longitudinal grade section is analyzed.

scholarly journals The variability of urban safety performance functions for different road elements: an Italian case study

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Paolo Intini ◽  
Nicola Berloco ◽  
Gabriele Cavalluzzi ◽  
Dominique Lord ◽  
Vittorio Ranieri ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Prediction Models ◽  
Safety Performance ◽  
Common Trends ◽  
Main Research ◽  
Pavement Markings ◽  
Italian Case ◽  
Sight Distance ◽  
Safety Performance Functions ◽  
Urban Safety

Abstract Background Urban safety performance functions are used to predict crash frequencies, mostly based on Negative Binomial (NB) count models. They could be differentiated for considering homogeneous subsets of segments/intersections and different predictors. Materials and methods The main research questions concerned: a) finding the best possible subsets for segments and intersections for safety modelling, by discussing the related problems and inquiring into the variability of predictors within the subsets; b) comparing the modelling results with the existing literature to highlight common trends and/or main differences; c) assessing the importance of additional crash predictors, besides traditional variables. In the context of a National research project, traffic volumes, geometric, control and additional variables were collected for road segments and intersections in the City of Bari, Italy, with 1500 fatal+injury related crashes (2012–2016). Six NB models were developed for: one/two-way homogeneous segments, three/four-legged, signalized/unsignalized intersections. Results Crash predictors greatly vary within the different subsets considered. The effect of vertical signs on minor roads/driveways, critical sight distance, cycle crossings, pavement/markings maintenance was specifically discussed. Some common trends but also differences in both types and effect of crash predictors were found by comparing results with literature. Conclusion The disaggregation of urban crash prediction models by considering different subsets of segments and intersections helps in revealing the specific influence of some predictors. Local characteristics may influence the relationships between well-established crash predictors and crash frequencies. A significant part of the urban crash frequency variability remains unexplained, thus encouraging research on this topic.

New Intersection Crash Prediction Models for the Second Edition of the Highway Safety Manual

2021 ◽  
pp. 036119812110398
Author(s):  
Darren J. Torbic ◽  
Daniel Cook ◽  
Joseph Grotheer ◽  
Richard Porter ◽  
Jeffrey Gooch ◽  
...  
Keyword(s):  
Traffic Control ◽  
Prediction Models ◽  
Highway Safety ◽  
Crash Severity ◽  
Crash Prediction ◽  
Part C ◽  
Highway Safety Manual ◽  
Rural And Urban ◽  
Diamond Interchanges ◽  
Crash Prediction Models

The objective of this research was to develop new intersection crash prediction models for consideration in the second edition of the Highway Safety Manual (HSM), consistent with existing methods in HSM Part C and comprehensive in their ability to address a wide range of intersection configurations and traffic control types in rural and urban areas. The focus of the research was on developing safety performance functions (SPFs) for intersection configurations and traffic control types not currently addressed in HSM Part C. SPFs were developed for the following general intersection configurations and traffic control types: rural and urban all-way stop-controlled intersections; rural three-leg intersections with signal control; intersections on high-speed urban and suburban arterials (i.e., arterials with speed limits greater than or equal to 50 mph); urban five-leg intersections with signal control; three-leg intersections where the through movements make turning maneuvers at the intersections; crossroad ramp terminals at single-point diamond interchanges; and crossroad ramp terminals at tight diamond interchanges. Development of severity distribution functions (SDFs) for use in combination with SPFs to estimate crash severity as a function of geometric design elements and traffic control features was explored; but owing to challenges and inconsistencies in developing and interpreting the SDFs, it was recommended for the second edition of the HSM that crash severity for the new intersection configurations and traffic control types be addressed in a manner consistent with existing methods in Chapters 10, 11, and 12 of the first edition, without use of SDFs.

scholarly journals Safety Analysis of Interchange Functional Areas

2018 ◽  
Vol 2672 (30) ◽  
pp. 120-130
Author(s):  
Akinfolarin Abatan ◽  
Peter T. Savolainen
Keyword(s):  
Random Effects ◽  
Traffic Control ◽  
Negative Binomial ◽  
Research Literature ◽  
Safety Performance ◽  
Random Effects Models ◽  
Traffic Crash ◽  
Design Alternatives ◽  
Traffic Conflicts ◽  
Functional Areas

Limited access facilities, such as freeways and expressways, are generally designed to the highest standards among public roads. Consequently, these facilities demonstrate crash, injury, and fatality rates that are significantly lower than other road facility types. However, these rates are generally elevated in the immediate vicinity of interchanges because of increases in traffic conflicts precipitated by weaving, merging, and diverging traffic. Given the extensive costs involved in interchange construction, it is important to discern the expected operational and safety impacts of various design alternatives. To this end, the objective of this study was to analyze safety performance within the functional areas of interchanges. The study involves the integration of traffic crash, volume, and roadway geometric data from 2010 to 2014 in the state of Iowa. Separate analyses were conducted for the freeway mainline and ramp connections. A series of safety performance functions (SPFs) were estimated for both the mainline and ramps. Random effects negative binomial models were estimated, which account for correlation in crash counts at the same location over time. The results show the frequency of crashes to vary based on traffic volume, interchange configuration, speed limit, and traffic control at the ramp terminal. The random effects models are shown to significantly outperform pooled models, which suggest there are several important location-specific factors that are not included in the analysis dataset. The SPFs from this study are also compared with several reference models from the extant research literature.

scholarly journals Crash Prediction Models for Horizontal Curve Segments on Two-Lane Rural Roads in Thailand

2021 ◽  
Vol 13 (16) ◽  
pp. 9011
Author(s):  
Nopadon Kronprasert ◽  
Katesirint Boontan ◽  
Patipat Kanha
Keyword(s):  
Prediction Models ◽  
Safety Performance ◽  
Horizontal Curve ◽  
Crash Frequency ◽  
Rural Roads ◽  
Crash Prediction ◽  
Road Crashes ◽  
Highway Safety Manual ◽  
Safety Performance Functions ◽  
Crash Prediction Models

The number of road crashes continues to rise significantly in Thailand. Curve segments on two-lane rural roads are among the most hazardous locations which lead to road crashes and tremendous economic losses; therefore, a detailed examination of its risk is required. This study aims to develop crash prediction models using Safety Performance Functions (SPFs) as a tool to identify the relationship among road alignment, road geometric and traffic conditions, and crash frequency for two-lane rural horizontal curve segments. Relevant data associated with 86,599 curve segments on two-lane rural road networks in Thailand were collected including road alignment data from a GPS vehicle tracking technology, road attribute data from rural road asset databases, and historical crash data from crash reports. Safety Performance Functions (SPFs) for horizontal curve segments were developed, using Poisson regression, negative binomial regression, and calibrated Highway Safety Manual models. The results showed that the most significant parameter affecting crash frequency is lane width, followed by curve length, traffic volume, curve radius, and types of curves (i.e., circular curves, compound curves, reverse curves, and broken-back curves). Comparing among crash prediction models developed, the calibrated Highway Safety Manual SPF outperforms the others in prediction accuracy.

scholarly journals Modeling Traffic Accident Occurrence at Hazardous Road Locations: A Case Study in Tunisia

2018 ◽  
Author(s):  
Fedy Ouni ◽  
Mounir Belloumi
Keyword(s):  
Goodness Of Fit ◽  
Negative Binomial ◽  
Prediction Models ◽  
Pearson Correlation ◽  
Surface Condition ◽  
Random Effect ◽  
Negative Binomial Model ◽  
Empirical Modeling ◽  
Binomial Model ◽  
Model Average

The purpose of the present study is to explore the linkage between Hazardous Road Locations-based crash counts and a variety of geometric characteristics, roadway characteristics, traffic flow characteristics and spatial features in the region of Sousse, Tunisia. For this purpose, collision data was collected from at 52 hazardous road sections including 1397 crash records for a 11-year monitoring period from January 1, 2004 to December 31, 2014 obtained from National Observatory for Information, Training, Documentation and Studies on Road Safety in Tunisia (NOITDRS). The matrix of Pearson correlation was used in order to avoid inclusion of both variables, which were highly correlated. Both the Random Effects Negative Binomial model and the Negative Binomial model were estimated. To evaluate the models, the Random Effect Negative Binomial model improves the goodness-of-fit compared to the Negative Binomial model. Average Daily Traffic volume, Curved alignment, Presence of public lighting, Visibility, Number of lane, Presence of vertical/horizontal sign, Presence of rural segment, Presence of drainage system, Roadway surface condition, Presence of paved shoulder and presence of major road were found as significant variables influencing accident occurrences. Overall, the current research contributes to the literature from empirical, modeling methodological standpoints since it was the first study conducted in Tunisia to use crash prediction models for hazardous road locations, and that portrays Tunisian reality. The research findings present advantageous insights on hazardous road locations in the region of Sousse, Tunisia and present useful planning tools for public authorities in Tunisia.

scholarly journals Prediction of Medical Costs in a Health Insurance Carrier according to Risk Profiles and Uses by its Affiliates

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Rodolfo Herrera Medina ◽  
Jaime Lee ◽  
Ferney Herrera Cruz
Keyword(s):  
Goodness Of Fit ◽  
Linear Models ◽  
Prediction Models ◽  
Age Groups ◽  
Simple Random Sampling ◽  
Medical Costs ◽  
Sampling Frame ◽  
Cross Sectional ◽  
Insurance Carrier ◽  
Statistical Criteria

Objective: To find a model of prediction of the medical cost of a Health Benefits Management Company (EAPB) with adequate statistical criteria. Methods: A Cross-sectional study with retrospective follow-up of the use of health services in an EAPB during a one-year period. The sampling frame consisted of a population of 1,529,188 affiliates who were assigned to a primary care IPS group. By simple random sampling size was estimated at 190,917 users. The dependent variable was the cost of the services used deflated to the year 2013. As independent variables besides the traditional sociodemographic variables chosen in this type of prediction models, variables of the insurance were added; Variables of risk management (inclusion or not in promotion and prevention program) and of comorbidities. Results: Simple Linear Regression modeling showed errors of inappropriate statistical criteria such as violating the principle of normality in cost errors. The Generalized Linear Models, proposed to estimate POS average costs, have an appropriate goodness of fit and evaluated with small Deviations and minimum Akaike criterion (AIC) compared to other models of the exponential family Conclusions: The appropriate statistical model to predict medical costs was the Generalized Linear Model with two parts segmented by age groups and gender. This research suggests that to estimate the benefit premium of any EAPB, besides socio-demographic variables, insurance variables, membership or not in promotion programs and risk prevention and/or management and the burden of disease of that population should be used.

scholarly journals Investigation of surrogate measures for safety assessment of two-way stop controlled intersections.

2021 ◽  
Author(s):  
Adrian Lorion
Keyword(s):  
Goodness Of Fit ◽  
Prediction Models ◽  
Traffic Volume ◽  
Left Turn ◽  
Crash Prediction ◽  
Greater Toronto Area ◽  
Crash Prediction Models ◽  
Surrogate Measures ◽  
Surrogate Safety Measures ◽  
Volume Intersection

Crash prediction models used to estimate safety at intersections, road, and highway segments are traditionally developed using various traffic volume measures. There are issues with this approach and surrogate safety measures such as conflicts and delays can overcome them. This study investigates the relationships between crash frequencies and traffic volume, intersection delay, and conflicts to explore the viability of these models for estimating safety at two-way stop controlled intersections. The database used includes 78 three leg and 55 four leg intersections within the Greater Toronto Area. Crash prediction models were developed and evaluated based on goodness-of-fit measures and CURE plots. Two conflict estimation techniques are compared in order to determine which is best suited for two-way stop controlled intersection simulations. This study also investigates the use of the models for estimating the safety impact of implementing a left turn lane on a major approach of a three leg intersection.

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