Crash Modification Factors Research Articles

Development of crash modification factors for changing lane width on roadway segments using generalized nonlinear models

This study evaluates the effectiveness of changing lane width in reducing crashes on roadway segments. To consider nonlinear relationships between crash rate and lane width, the study develops generalized nonlinear models (GNMs) using 3-years crash records and road geometry data collected for all roadway segments in Florida. The study also estimates various crash modification factors (CMFs) for different ranges of lane width based on the results of the GNMs. It was found that the crash rate was highest for 12-ft lane and lower for the lane width less than or greater than 12ft. GNMs can extrapolate this nonlinear continuous effect of lane width and estimate the CMFs for any lane width, not only selected lane widths, unlike generalized linear models (GLMs) with categorical variables. The CMFs estimated using GNMs reflect that crashes are less likely to occur for narrower lanes if the lane width is less than 12ft whereas crashes are less likely to occur for wider lanes if the lane width is greater than 12ft. However, these effects varied with the posted speed limits as the effect of interaction between lane width and speed limit was significant. The estimated CMFs show that crashes are less likely to occur for lane widths less than 12ft than the lane widths greater than 12ft if the speed limit is higher than or equal to 40mph. It was also found from the CMFs that crashes at higher severity levels (KABC and KAB) are less likely to occur for lane widths greater or less than 12ft compared to 12-ft lane. The study demonstrates that the CMFs estimated using GNMs clearly reflect variations in crashes with lane width, which cannot be captured by the CMFs estimated using GLMs. Thus, it is recommended that if the relationship between crash rate and lane width is nonlinear, the CMFs are estimated using GNMs.

Validation of Crash Modification Factors Derived from Cross-Sectional Studies with Regression Models

Crash modification factors (CMFs) can be used to capture the safety effects of countermeasures and play a significant role in traffic safety management. As an alternative to the before-and-after study, the regression model method has been widely used for estimating CMFs. Although before-and-after studies are considered to be superior, the use of regression models for estimating CMFs has never been fully investigated. Consequently, the conditions in which regression models could be used for such a purpose were examined. CMFs for three variables—lane width, curve density, and pavement friction—were assumed and used for generating random crash counts. Then CMFs were derived from regression models by using the simulated crash data for three different scenarios. The results were then compared with the assumed true values. The study results showed that (a) when all factors affecting traffic safety are identical in all segments except those of interest, CMFs derived from regression models should be unbiased; (b) if some factors having minor safety effects are omitted from the models, the accuracy of estimated CMFs can still be acceptable; and (c) if some factors already known to have significant effects on crash risk are omitted, CMFs derived from the regression models are generally unreliable. Thus, depending on missing variables not included in the model, the transportation safety analyst can decide whether CMFs developed from regression models should be used for highway safety applications.

Is Horizontal Curvature a Significant Factor of Safety in Rural Multilane Highways?

The Highway Safety Manual (HSM) crash prediction models estimate the expected number of crashes for different facility types. Models in Part C of the first edition of the HSM include crash prediction models for divided and undivided rural multilane highway segments. Each of the HSM crash prediction models for highway segments is composed of a safety performance function (SPF) that is a function of annual average daily traffic and segment length plus a series of crash modification factors (CMFs). The SPF estimates the number of crashes for a site if the site features are of base condition. The effects of other features of the site, if their values are different from the base condition, are carried out through use of CMFs. Existing models for rural multilane segments do not have any CMFs for horizontal curvature. The goal of this research was to investigate whether horizontal alignment has any significant effect on crashes on these types of facilities and if so, to develop a CMF for this feature. Washington State cross-sectional data from the Highway Safety Information System Laboratory were used in this research. Data from 2007 to 2009 were used to conduct the investigation and 2010 and 2011 data were used to validate the results. As the results showed, horizontal curvature has a significant safety effect on rural multilane highways, and using a CMF for horizontal curvature improves the prediction of crashes significantly for tangent and curve segments.

Reliability-Based Assessment of Benefits in Roadway Safety Management

Road agencies set quantitative targets and adopt related road safety strategies in accordance with each agency's priorities and available resources. Benefit–cost analyses are carried out to support the decision-making process, and alternative measures are ranked according to their expected benefits and benefit–cost ratios, calculated with a safety performance function (SPF) and crash modification factors (CMFs) as predictors of future safety performance. Because of the variance in CMFs and crash frequency, it is uncertain what the benefits of some future actions will be. The chance of making a wrong decision depends on the standard deviations of the probability distributions of the CMFs and the SPF. To deal with the inherent uncertainty in the decision-making process, a reliability-based assessment of the benefits must be performed to introduce a stochastic approach. In this paper, the variances in the CMFs and SPFs are taken into account in a reliability-based benefit–cost analysis to address the improvements and issues associated with an accurate probabilistic approach when compared with deterministic results or other approximated procedures. A case study is presented that compares safety countermeasures selected to reduce crash frequency and severity on sharp curves on freeways. These measures include delineation systems, shoulder rumble strips, and retro-fitted safety barriers, individually and in combination. Monte Carlo simulations were applied to calculate the probability of the failure of the benefit–cost analysis statements. The results and comparisons with alternative approaches, such as the approach proposed in the Highway Safety Manual, are presented and show remarkable differences in the evaluation outcomes.

Safety Effectiveness of Flashing Yellow Arrow

The purpose of this project was to develop crash modification factors (CMFs) for the implementation of a flashing yellow arrow (FYA) on the basis of the specific before-and-after period conditions of a signalized intersection. Although this countermeasure has been used for years in North Carolina and other states, no published studies to date have provided CMFs for left-turn crashes specific to the treated approaches, and none has provided CMFs for the three-section FYA for permissive-only left turns. Crash data from 222 intersections in North Carolina with an FYA protected–permissive left turn (FYA-PPLT), three-section FYA permissive-only left-turn installations, or both were used to provide CMFs for five category types: Category 1 (permissive only to FYA-PPLT), Category 2 (protected only to FYA-PPLT), Category 2A (protected only to FYA-PPLT with time of day operation), Category 3 (five-section PPLT to FYA-PPLT), and Category 4 (permissive only to FYA permissive only). A before-and-after crash analysis with consideration given to increases in traffic was used to determine the safety estimates. Safety performance functions were used to account for the effect of traffic volume trends. In Categories 3 and 4, the change was exclusive to the left-turn display and not to a change in phasing. All CMF results were statistically significant for Category 3, and target and injury CMF results were statistically significant for Category 4. On the basis of the results from the study sites, a statistically significant decrease was found in target left-turn crashes and injury crashes after a site signal underwent a change from a solid green ball to an FYA for permissive left turns when phasing remained unchanged. This finding applied whether the left phasing was protected–permissive or fully permissive.

Crash Modification Factors for Dynamic Speed Feedback Signs on Rural Curves

A large number of crashes occur on curves even though they account for only a small percentage of a system’s mileage. Excessive speed has been identified as a primary factor in both lane departure and curve-related crashes. A number of countermeasures have been proposed to reduce driver speeds on curves, which ideally result in successful curve negotiation and fewer crashes. Dynamic speed feedback sign (DSFS) systems are traffic control devices that have been used to reduce vehicle speeds successfully and, subsequently, crashes in applications such as traffic calming on urban roads. DSFS systems show promise, but they have not been fully evaluated for rural curves. To better understand the effectiveness of DSFS systems in reducing crashes on curves, a national field evaluation of DSFS systems on curves on rural two lane roadways was conducted. Two different DSFS systems were selected and placed at 22 sites in seven states. Control sites were also identified. A full Bayes modeling methodology was utilized to develop crash modification factors (CMFs) for several scenarios including total crashes for both directions, total crashes in the direction of the sign, total single-vehicle crashes, and single-vehicle crashes in the direction of the sign. Using quarterly crash frequency as the response variable, crash modification factors were developed and results showed that crashes were 5% to 7% lower after installation of the signs depending on the model.

Transferability and Calibration of Highway Safety Manual Performance Functions and Development of New Models for Urban Four-Lane Divided Roads in Riyadh, Saudi Arabia

The first edition of the Highway Safety Manual (HSM) provides a number of safety performance functions (SPFs) that can be used to predict severe collisions on a roadway network. This paper examines the calibration of the HSM SPFs for urban four-lane divided roadway segments with angle parking in Riyadh, Saudi Arabia, and the development of new SPFs. This study first calibrated the HSM SPFs by using HSM default crash modification factors (CMFs) and then proposed new local CMFs, which adjust the estimation of calibration factors by using fatal and injury crash data. In addition, new forms for specific SPFs were further evaluated to identify the best model by using the Poisson–gamma regression technique. It was found that the jurisdiction-specific SPFs provided the best fit of the data used in this study and would be the best SPFs for predicting severe collisions in the city of Riyadh. The best fatal and injury model describes the mean crash frequency as a function of the natural logarithm of the annual average daily traffic, segment length, speed limit, and driveway density. The study found that the HSM calibration using Riyadh local CMFs outperformed the calibration method using HSM default values. Based on these results, potential countermeasures were proposed to reduce the number of severe crashes on Riyadh urban roads, and the potential for HSM application in Saudi Arabia is addressed.

Development of adjustment functions to assess combined safety effects of multiple treatments on rural two-lane roadways

Numerous studies have attempted to evaluate the safety effectiveness of specific single treatment on roadways by estimating crash modification factors (CMFs). However, there is a need to also assess safety effects of multiple treatments since multiple treatments are usually simultaneously applied to roadways. Due to the lack of sufficient CMFs of multiple treatments, the Highway Safety Manual (HSM) provides combining method for multiple CMFs. However, it is cautioned in the HSM and related sources that combined safety effect of multiple CMFs may be over or under estimated. Moreover, the literature did not evaluate the accuracy of the combining method using CMFs obtained from the same study area. Thus, the main objectives of this research are: (1) to estimate CMFs and crash modification functions (CM Functions) for two single treatments (shoulder rumble strips, widening (1–9ft) shoulder width) and combination (installing shoulder rumble strips+widening shoulder width) using the observational before–after with empirical Bayes (EB) method and (2) to develop adjustment factors and functions to assess combined safety effects of multiple treatments based on the accuracy of the combined CMFs for multiple treatments estimated by the existing combining method. Data was collected for rural two-lane roadways in Florida and Florida-specific safety performance functions (SPFs) were estimated for different crash types and severities. The CM Functions and adjustment functions were developed using linear and nonlinear regression models. The results of before–after with EB method show that the two single treatments and combination are effective in reducing total and SVROR (single vehicle run-off roadway) crashes. The results indicate that the treatments were more safety effective for the roadway segments with narrower original shoulder width in the before period. It was found that although the CMFs for multiple treatments (i.e., combination of two single treatments) were generally lower than CMFs for single treatments, they were getting similar to the roadway segments with wider shoulder width. The findings indicate that the combined safety effects of multiple treatments using HSM combining method are mostly over-estimated and the accuracy of HSM combining method vary based on crash types and severity levels. Therefore, it is recommended to develop and apply the adjustment factors and functions to predict the safety effects of multiple treatments when the HSM combining method is used.

Effects on speed and safety of point-to-point speed enforcement systems: Evaluation on the urban motorway A56 Tangenziale di Napoli

In this paper, we evaluated the effects on speed and safety of the point-to-point (P2P) speed enforcement system activated on the urban motorway A56 in Italy. The P2P speed enforcement is a relatively new approach to traffic law enforcement that involves the calculation of the average speed over a section. To evaluate the speed effects, we performed a before–after analysis of speed data investigating also effects on non-compliance to speed limits. To evaluate the safety effects, we carried out an empirical Bayes observational before-and-after study.The P2P system led to very positive effects on both speed and safety. As far as the effects on the section average travel speeds, the system yielded to a reduction in the mean speed, the 85th percentile speed, the standard deviation of speed, and the proportion of drivers exceeding the speed limits, exceeding the speed limits more than 10km/h, and exceeding the speed limits more than 20km/h. The best results were the decrease of the speed variability and the reduction of the excessive speeding behaviour. The decrease in the standard deviation of speed was 26% while the proportion of light and heavy vehicles exceeding the speed limits more than 20km/h was reduced respectively by 84 and 77%.As far as the safety effects, the P2P system yielded to a 32% reduction in the total crashes, with a lower 95% confidence limit of the estimate equal to 22%. The greatest crash reductions were in rainy weather (57%), on wet pavement (51%), on curves (49%), for single vehicle crashes (44%), and for injury crashes (37%). It is noteworthy that the system produced a statistically significant reduction of 21% in total crashes also in the part of the motorway where it was not activated, thus generating a significant spillover effect.The investigation of the effects of the P2P system on speed and safety over time allowed to develop crash modification functions where the relationship between crash modification factors and speed parameters (mean speed, 85th percentile speed, and standard deviation of speed) was expressed by a power function. Crash modification functions show that the effect of speed on safety is greater on curves and for injury crashes.Even though the study results show excellent outcomes, we must point out that the crash reduction effects decreased over time and speed, speed variability, and non-compliance to speed limits significantly increased over time. To maintain its effectiveness over time, P2P speed enforcement must be actively managed, i.e. constantly monitored and supported by appropriate sanctions.

Comparison of safety effect estimates obtained from empirical Bayes before–after study, propensity scores-potential outcomes framework, and regression model with cross-sectional data

A variety of different study designs and analysis methods have been used to evaluate the performance of traffic safety countermeasures. The most common study designs and methods include observational before–after studies using the empirical Bayes method and cross-sectional studies using regression models. The propensity scores-potential outcomes framework has recently been proposed as an alternative traffic safety countermeasure evaluation method to address the challenges associated with selection biases that can be part of cross-sectional studies. Crash modification factors derived from the application of all three methods have not yet been compared. This paper compares the results of retrospective, observational evaluations of a traffic safety countermeasure using both before–after and cross-sectional study designs.The paper describes the strengths and limitations of each method, focusing primarily on how each addresses site selection bias, which is a common issue in observational safety studies. The Safety Edge paving technique, which seeks to mitigate crashes related to roadway departure events, is the countermeasure used in the present study to compare the alternative evaluation methods. The results indicated that all three methods yielded results that were consistent with each other and with previous research. The empirical Bayes results had the smallest standard errors. It is concluded that the propensity scores with potential outcomes framework is a viable alternative analysis method to the empirical Bayes before–after study. It should be considered whenever a before–after study is not possible or practical.

Developing crash modification functions to assess safety effects of adding bike lanes for urban arterials with different roadway and socio-economic characteristics

Although many researchers have estimated crash modification factors (CMFs) for specific treatments (or countermeasures), there is a lack of studies that explored the heterogeneous effects of roadway characteristics on crash frequency among treated sites. Generally, the CMF estimated by before–after studies represents overall safety effects of the treatment in a fixed value. However, as each treated site has different roadway characteristics, there is a need to assess the variation of CMFs among the treated sites with different roadway characteristics through crash modification functions (CMFunctions). The main objective of this research is to determine relationships between the safety effects of adding a bike lane and the roadway characteristics through (1) evaluation of CMFs for adding a bike lane using observational before–after with empirical Bayes (EB) and cross-sectional methods, and (2) development of simple and full CMFunctions which are describe the CMF in a function of roadway characteristics of the sites. Data was collected for urban arterials in Florida, and the Florida-specific full SPFs were developed. Moreover, socio-economic parameters were collected and included in CMFunctions and SPFs (1) to capture the effects of the variables that represent volume of bicyclists and (2) to identify general relationship between the CMFs and these characteristics. In order to achieve better performance of CMFunctions, data mining techniques were used.The results of both before–after and cross-sectional methods show that adding a bike lane on urban arterials has positive safety effects (i.e., CMF<1) for all crashes and bike crashes. It was found that adding a bike lane is more effective in reducing bike crashes than all crashes. It was also found that the CMFs vary across the sites with different roadway characteristics. In particular, annual average daily traffic (AADT), number of lanes, AADT per lane, median width, bike lane width, and lane width are significant characteristics that affect the variation in safety effects of adding a bike lane. Some socio-economic characteristics such as bike commuter rate and population density also have significant effect on the variation in CMFs. The findings suggest that full CMFunctions showed better model fit than simple CMFuncttions since they account for the heterogeneous effects of multiple roadway and socio-economic characteristics. The proposed CMFunctions provide insights into bike lane design and selection of sites for bike lane installation for reducing crashes.

Development of Safety Performance Measures for Urban Roundabouts in India

Roundabouts, although considered as safe among the various intersection types, have seen an increasing crash rate over the years in India. Geometric design of a roundabout directly influences the driver’s speed adoption and maneuvering behavior, and hence plays a vital role in its safety performance. Application of treatments at roundabouts by altering the geometric design requires careful safety evaluation before actual implementation. The present study identified the crash causes and devised safety performance measures for urban roundabouts located in the state of Kerala, India. Crash prediction models and crash modification factors (CMFs) are developed in this study for the safety assessment of geometric design features of roundabouts. Of the many models tried, the zero-inflated negative binomial regression model is the best model to predict the crash frequency of roundabout approaches. Geometric features of the central island, circulatory roadway, and approach roads are associated with the crash occurrence on roundabout approaches. CMFs are developed by a cross-sectional method and are useful for investigating the relationship between safety and geometric design features of roundabouts.

A Study of Safety Impacts of Different Types of Driveways and their Density

The recently published Highway Safety Manual (HSM) has defined seven different driveway types based on land use and parking lot size, including major commercial, minor commercial, major industrial-institutional, minor industrial-institutional, major residential, minor residential, and other. Major driveways are defined as having more than 50 parking spaces, while minor driveways are defined as those having fewer than 50 parking spaces. The HSM crash prediction models require the inputs of driveway type and density. However, the actual impacts of different types of driveways on the number of crashes are not clear. The crash modification factors provided were based on few past studies, with high standards of error. The purpose of this research is to develop a method to quantify the impact of driveway types and density on traffic crash frequencies, types, and severities. The different driveway types were collected in the state of Illinois and crashes occurring in the impact area of each driveway were identified from the IDOT crash database (from 2005 to 2009). A cross section comparison was conducted to compare the mean crash frequency and crash rates among different driveways. A further statistical analysis was used to develop a relationship between each driveway type and crash rates.

Integrated traffic conflict model for estimating crash modification factors

Crash modification factors (CMFs) for road safety treatments are usually obtained through observational models based on reported crashes. Observational Bayesian before-and-after methods have been applied to obtain more precise estimates of CMFs by accounting for the regression-to-the-mean bias inherent in naive methods. However, sufficient crash data reported over an extended period of time are needed to provide reliable estimates of treatment effects, a requirement that can be a challenge for certain types of treatment. In addition, these studies require that sites analyzed actually receive the treatment to which the CMF pertains. Another key issue with observational approaches is that they are not causal in nature, and as such, cannot provide a sound “behavioral” rationale for the treatment effect. Surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been proposed to address this issue by providing a more “causal perspective” on lack of safety for different road and traffic conditions. The traffic conflict approach has been criticized, however, for lacking a formal link to observed and verified crashes, a difficulty that this paper attempts to resolve by presenting and investigating an alternative approach for estimating CMFs using simulated conflicts that are linked formally to observed crashes. The integrated CMF estimates are compared to estimates from an empirical Bayes (EB) crash-based before-and-after analysis for the same sample of treatment sites. The treatment considered involves changing left turn signal priority at Toronto signalized intersections from permissive to protected-permissive. The results are promising in that the proposed integrated method yields CMFs that closely match those obtained from the crash-based EB before-and-after analysis.

Propensity scores-potential outcomes framework to incorporate severity probabilities in the Highway Safety Manual crash prediction algorithm

Accurate estimation of the expected number of crashes at different severity levels for entities with and without countermeasures plays a vital role in selecting countermeasures in the framework of the safety management process. The current practice is to use the American Association of State Highway and Transportation Officials’ Highway Safety Manual crash prediction algorithms, which combine safety performance functions and crash modification factors, to estimate the effects of safety countermeasures on different highway and street facility types. Many of these crash prediction algorithms are based solely on crash frequency, or assume that severity outcomes are unchanged when planning for, or implementing, safety countermeasures. Failing to account for the uncertainty associated with crash severity outcomes, and assuming crash severity distributions remain unchanged in safety performance evaluations, limits the utility of the Highway Safety Manual crash prediction algorithms in assessing the effect of safety countermeasures on crash severity. This study demonstrates the application of a propensity scores-potential outcomes framework to estimate the probability distribution for the occurrence of different crash severity levels by accounting for the uncertainties associated with them. The probability of fatal and severe injury crash occurrence at lighted and unlighted intersections is estimated in this paper using data from Minnesota. The results show that the expected probability of occurrence of fatal and severe injury crashes at a lighted intersection was 1 in 35 crashes and the estimated risk ratio indicates that the respective probabilities at an unlighted intersection was 1.14 times higher compared to lighted intersections. The results from the potential outcomes-propensity scores framework are compared to results obtained from traditional binary logit models, without application of propensity scores matching. Traditional binary logit analysis suggests that the probability of occurrence of severe injury crashes is higher at lighted intersections compared to unlighted intersections, which contradicts the findings obtained from the propensity scores-potential outcomes framework. This finding underscores the importance of having comparable treated and untreated entities in traffic safety countermeasure evaluations.

Exploration and comparison of crash modification factors for multiple treatments on rural multilane roadways

As multiple treatments (or countermeasures) are simultaneously applied to roadways, there is a need to assess their combined safety effects. Due to a lack of empirical crash modification factors (CMFs) for multiple treatments, the Highway Safety Manual (HSM) and other related studies developed various methods of combining multiple CMFs for single treatments. However, the literature did not evaluate the accuracy of these methods using CMFs obtained from the same study area. Thus, the main objectives of this research are: (1) develop CMFs for two single treatments (shoulder rumble strips, widening shoulder width) and one combined treatment (shoulder rumble strips+widening shoulder width) using before–after and cross-sectional methods and (2) evaluate the accuracy of the combined CMFs for multiple treatments estimated by the existing methods based on actual evaluated combined CMFs. Data was collected for rural multi-lane highways in Florida and four safety performance functions (SPFs) were estimated using 360 reference sites for two crash types (All crashes and Single Vehicle Run-off Roadway (SVROR) crashes) and two severity levels (all severity (KABCO) and injury (KABC)).The results of both before–after and cross-sectional methods show that the two single treatments and the combined treatment produced safety improvement. It was found that safety effects were higher for the roadway segments with shoulder rumble strips and wider shoulder width. It was also found that the treatments were more safety effective (i.e. lower CMF) for the roadway segments with narrower original shoulder width in the before period. However, although CMFs for multiple treatments were generally lower than CMFs for single treatments, they were similar for the roadway segments with shoulder width of 8–12 feet. More specifically, CMFs for single treatments were lower than CMFs for multiple treatments for the roadway segments with shoulder width of 9 feet or higher. Among different methods of combining CMFs, the HSM, Systematic Reduction of Subsequent CMFs, Applying only the most effective CMF, and Weighted average of multiple CMFs (Meta-Analysis) showed good estimates of the combined CMFs for multiple treatments with 2.2% difference between actual and estimated CMFs. The findings suggest that the existing methods of combining multiple CMFs are generally valid but they need to be applied for different crash types and injury levels separately.Lastly, an average of the combined CMFs from the best two methods was closer to the actual CMF than the combined CMF from only one best method. This indicates that it is better not to rely on only one specific existing method of combining CMFs for predicting CMF for multiple treatments.

Methodology to develop crash modification functions for road safety treatments with fully specified and hierarchical models

Crash modification factors (CMFs) for road safety treatments are developed as multiplicative factors that are used to reflect the expected changes in safety performance associated with changes in highway design and/or the traffic control features. However, current CMFs have methodological drawbacks. For example, variability with application circumstance is not well understood, and, as important, correlation is not addressed when several CMFs are applied multiplicatively. These issues can be addressed by developing safety performance functions (SPFs) with components of crash modification functions (CM-Functions), an approach that includes all CMF related variables, along with others, while capturing quantitative and other effects of factors and accounting for cross-factor correlations. CM-Functions can capture the safety impact of factors through a continuous and quantitative approach, avoiding the problematic categorical analysis that is often used to capture CMF variability. There are two formulations to develop such SPFs with CM-Function components – fully specified models and hierarchical models. Based on sample datasets from two Canadian cities, both approaches are investigated in this paper. While both model formulations yielded promising results and reasonable CM-Functions, the hierarchical model was found to be more suitable in retaining homogeneity of first-level SPFs, while addressing CM-Functions in sub-level modeling. In addition, hierarchical models better capture the correlations between different impact factors.

Relating crash frequency and severity: Evaluating the effectiveness of shoulder rumble strips on reducing fatal and major injury crashes

To approach the goal of “Toward Zero Deaths,” there is a need to develop an analysis paradigm to better understand the effects of a countermeasure on reducing the number of severe crashes. One of the goals in traffic safety research is to search for an effective treatment to reduce fatal and major injury crashes, referred to as severe crashes. To achieve this goal, the selection of promising countermeasures is of utmost importance, and relies on the effectiveness of candidate countermeasures in reducing severe crashes. Although it is important to precisely evaluate the effectiveness of candidate countermeasures in reducing the number of severe crashes at a site, the current state-of-the-practice often leads to biased estimates. While there have been a few advanced statistical models developed to mitigate the problem in practice, these models are computationally difficult to estimate because severe crashes are dispersed spatially and temporally, and cannot be integrated into the Highway Safety Manual framework, which develops a series of safety performance functions and crash modification factors to predict the number of crashes. Crash severity outcomes are generally integrated into the Highway Safety Manual using deterministic distributions rather than statistical models. Accounting for the variability in crash severity as a function geometric design, traffic flow, and other roadway and roadside features is afforded by estimating statistical models. Therefore, there is a need to develop a new analysis paradigm to resolve the limitations in the current Highway Safety Manual methods. We propose an approach which decomposes the severe crash frequency into a function of the change in the total number of crashes and the probability of a crash becoming a severe crash before and after a countermeasure is implemented. We tested this approach by evaluating the effectiveness of shoulder rumble strips on reducing the number of severe crashes. A total of 310 segments that have had shoulder rumble strips installed during 2002–2009 are included in the analysis. It was found that shoulder rumble strips reduce the total number of crashes, but have no statistically significant effect on reducing the probability of a severe crash outcome.

Development of a Korea highway safety evaluation proto type model on the concept of IHSDM crash prediction module

This study tries to develop a Korea highway safety evaluation proto type model for quantified safety evaluation. We develop a base model and crash modification factors (CMFs) through reviewing the procedures and methodologies in Highway Safety Manual. At the same time, we try to carefully consider collectable data and roadway environment of Korea that are different from the USA. CMFs are developed through models and expert's judgement. Developed CMFs are for driveway density, pedestrian crosswalk, existence of median, terrain types, and land-use types. Also, verification of the developed base model and CMFs were performed using two routes of Korea's rural two-lane highways while comparing with roadway safety design synthesis and Crash Prediction Module (CPM) of Interactive Highway Safety Design Model (IHSDM). Applicability analysis was then performed in two aspects of predictability and adaptability of the proto type model. As a result, CMFs and predicted accident estimates of CPM are similar with the developed Korea proto type model. However, the base model and CMFs of the developed proto type for Korea are more precise than the others when evaluating sections where the number of actual accidents is higher. It is found that considering CMF for land-use type is justifiable when developing a Korea highway safety evaluation proto type model. This study validates the possibility of developing a full scale of Korea highway safety evaluation model.

Evaluating the Safety Effects of Signal Improvements

Many fatal and injury crashes on roadways occur at intersections. Traffic signals are often installed or modified to reduce these severe crashes. Whether the traffic signal improvements help reduce severe crashes can be evaluated with crash modification factors (CMFs). Recent research showed that traditional safety evaluation methods were inadequate for developing CMFs. Bayesian statistical methods have been used in traffic safety studies to analyze the effectiveness of safety improvements more accurately. The hierarchical Bayesian method is an advanced statistical technique that can account for the shortcomings of traditional methods and more fully reflect the effectiveness of safety improvements. This study used a hierarchical Bayesian model to analyze the effectiveness of new traffic signal installations and modifications to existing traffic signals from permissive-only phasing to protected–permissive left-turn phasing through the development of CMFs for multiple scenarios. A benefit-to-cost (B-C) analysis was performed for each improvement to determine how long it would take to recover the cost of installation. The results showed a slight increase in overall and nonsevere crashes and a decrease in severe crashes for both new signal installations and modifications to existing signals. The B-C analysis indicated that a benefit came from both improvements and that new signal installation costs could be recovered in approximately 5 years and the cost of the installation of a left-turn signal modification could be recovered in approximately 9 weeks.