Crash Modification Factors Research Articles

A proactive decision support tool for road safety audit of new highway projects based on crash modification factors and analytical analysis: Algeria as a case study

The most cost-effective way to improve the performance of a new road is to integrate road safety into the early phase of the project design. Therefore, the information obtained from the design phase is simply used to get an overview of the project in place. This article proposes a simplified analytical tool to target road safety problems proactively, even before inspection visits. The study area contains 110 segments of 100 m long (inspection intervals) of a highway under construction, sited in Algeria in the locality of Ghazaouet, Wilaya of Tlemcen. The methodology adopted consists of combining the International Road Assessment Program (iRAP) and the multiple linear regression method to obtain a simplified analytical model, which allows the prediction of road risk for each section of 100 m. The results obtained showed a 98% correlation between the model values and the real values obtained by the iRAP approach. As a complement to the iRAP method, this approach facilitates the anticipatory assessment of road risks by road safety auditors. Eventually, this tool will support and guide auditors to be acquainted with the recent trends in the domain of road safety.

Examining the performance of engineering treatment evaluation methodologies using the hypothetical treatment and actual treatment settings

The selection of treatment evaluation methodology is paramount in determining reliable crash modification factors (CMFs) for engineering treatments. A lack of ground truth makes it cumbersome to examine the performance of treatment evaluation methodologies. In addition, a sound methodological framework is critical for evaluating the performances of treatment evaluation methodologies. In addressing these challenges, this study proposed a framework for assessing treatment evaluation methodologies by hypothetical treatments with known ground truth and actual real-world treatments. In particular, this study examined three before-after treatment evaluation approaches: 1) Empirical Bayes, 2) Simulation-based Empirical Bayes, and 3) Full Bayes methods. In addition, this study examined the Cross-Sectional treatment evaluation methodology. The methodological framework utilized five datasets of hypothetical treatment with known ground truth based on the hotspot identification method and a real-world dataset of wide centerline treatment on two-lane, two-way rural highways in Queensland, Australia. Results showed that all the methods could identify the ground truth of hypothetical treatments, but the Full Bayes approach better predicts the known ground truth compared to Empirical Bayes, Simulation-based Empirical Bayes, and Cross-Sectional methods. The Full Bayes approach was also found to provide the most precise estimate for real-world wide centerline treatment along rural highways compared to other methods. Moreover, the current study highlighted that the Cross-Sectional method offers a viable estimate of treatment effectiveness in case the before-period data is limited.

Performance and safety effectiveness evaluation of mini-roundabouts in Michigan

This study evaluates the performance and safety effectiveness of mini-roundabouts. Crash, operational, and geometric data for 14 mini-roundabouts located in the state of Michigan were collected for both before and after installation time periods between 2007 and 2016. Three years of complete before and after installation crash data were analyzed utilizing the Before-and-After study with Comparison Group methodology. A total 28 untreated sites with similar characteristics to the 14 mini-roundabouts sites were used to account for changes in crashes unrelated to the treatment (mini-roundabout installation), evaluate the impacts of the treatment on the intersection, and develop the crash modification factors (CMFs). The results for overall safety effectiveness indicate a decrease in total crashes at signalized intersections when converted into mini-roundabouts, and an increase in total crashes at two-way stop-controlled (TWSC) and all-way stop-controlled (AWSC) intersections when converted into mini-roundabouts. The recommended CMFs for converting a TWSC, AWSC, and signalized intersection into a mini-roundabout are 1.039, 1.051, and 0.755 for total crashes, respectively.

A survival analysis with random parameter approach for assessing temporal instability in treatment effect

Before-after analysis methods in traffic safety often aggregate traffic crashes into crash frequencies using relatively long aggregation time periods, such as a year. The implicit assumption is that the treatment effect is temporally stable over the aggregation period. However, certain “treatments”, such as the COVID-19 pandemic, may result in fast-evolving changes to road safety. By aggregating individual crashes, it is difficult to investigate the temporal characteristics of crashes and capture the potential temporal instability in treatment effect at detailed temporal levels, such as within a year. Therefore, this study exploits the disaggregated nature of crashes and proposes a survival analysis with random parameter (SARP) before-after analysis approach that can flexibly accommodate the temporal instability in treatment effect at various temporal levels. To validate and test the proposed approach, a statistical simulation study and an empirical case study that investigates the safety impact of COVID-19 lockdown in Manhattan, New York, are conducted. The statistical simulation study shows that the SARP method can unbiasedly estimate different patterns of temporally instable treatment effect at various temporal levels. The estimated monthly crash modification factors from the case study display an increasing trend after the largest decrease in the first month after the lockdown, which implies that traffic safety conditions are gradually returning to normal and provides evidence of temporal instability in treatment effect. The proposed SARP approach is promising to investigate the evolving safety impact of emerging technologies in transportation, such as the deployment of connected and autonomous vehicles.

Developing Safety Performance Functions and Crash Modification Factors for Urban Roundabouts in Heterogeneous Non-Lane-Based Traffic Conditions

This study aims to develop safety performance functions (SPFs) and crash modification factors (CMFs) for the safety assessment of roundabouts as a whole and their components, especially at entry, exit, and circulating lanes. This study uses historical crash data collected over five years (2015–2019) from 21 roundabouts (78 approaches) situated in some of the major cities in India. SPF and CMF models were developed using negative binomial and cross-sectional approaches. Results show that the percentage of motorized two-wheelers, average daily traffic, central island diameter, entry angle, weaving width, departure width, number of lanes at approach, exit angle, exit width, posted speed limit, weaving length, circulating roadway width, road surface condition, number of circulatory lanes, central island height, and number of legs contribute to the crash occurrence in the roundabout vicinity. In addition to this, circulating roadway width, average daily traffic, and posted speed limit are the most influencing risk factors across the entire roundabout vicinity. Furthermore, an interesting fact is that, given the asymmetrical impact of geometric and traffic factors, the overall crash rate varies across roundabout segments. The findings of this study may be useful for updating the current design guidelines for roundabouts, considering the safety perceptive. Besides, the proposed SPF and CMF tools could be used to investigate the likelihood of crashes at roundabouts. Moreover, this model would help safety experts to implement adequate safety treatment in the vicinity of roundabouts under heterogenous non-lane-based traffic conditions.

Safety Evaluation for Conversion From Protected-Only Left-Turn Phasing to Time-of-Day Protected-Permissive Left-Turn Phasing Using Flashing Yellow Arrows

This study investigated the safety effects of the conversion from a protected-only left turn to protected-permissive left turn with flashing yellow arrow (FYA−PPLT) with time-of-day operation. The observational before–after study with the comparison group method was used to develop crash modification factors (CMFs) for the total crashes and two types of target crashes that involve left-turning vehicles on treated approaches (left-turn−same roadway and rear-end crashes). For all potential crashes, crash reports, crash diagrams, and narratives were manually inspected to identify the actual target crashes. The CMFs were separately developed for a full 24-h day and specific time-of-day based on FYA-PPLT operation, and for two severity categories (all severities and fatal & injury). The results showed that the total crashes for 24 h had a slight increase, whereas the target crashes had substantially larger changes (increase in left-turn−same roadway crashes and decrease in rear-end crashes). When looking at the specific time-of-day use of FYA-PPLT, the increase in left-turn−same roadway crashes was significantly higher than the full 24-h period. This implies that engineers could extend protected-only use more on the fringes of the peak periods to mitigate the increase in left-turn-related crashes. The analysis results also showed a trade-off between left-turn–same roadway and rear-end crashes after the signal conversion. The findings reveal how important it is for engineers to properly understand the safety effects on the different categories of target crashes and time periods when considering the signal conversion from a protected-only left turn to FYA-PPLT.

Exploration of Some Key Issues in Developing and Applying Crash–Conflict Models for Signalized Intersections

The evaluation process for some roads safety strategies, especially innovative ones, may be challenging, as prior information may be non-existent. This challenge could be addressed with the use of surrogate measures, such as traffic conflicts. Statistical models relating crashes to conflicts are fundamental to this application. The aim of the paper’s research was to investigate some key issues related to the development and application of crash–conflict models. Among the issues addressed are the model specification, the very definition of conflicts, model transferability, and application of the models for estimating crash modification factors (CMFs). Issues are addressed with a case study in which traffic conflicts identified from both time to collision and post encroachment time are generated from the microsimulation of four-legged signalized intersections. These conflicts, in addition to the speed of conflicting vehicles, are used to explore the improved statistical relationships between the frequency of crashes and surrogate measures. Transferability of the models to another jurisdiction is also investigated. The results indicate that the inclusion of the speed variable along with conflicts provides stronger relationships than those with conflicts as a standalone variable. In particular, the results confirm the viability of estimating CMFs with the improved models. The transferability investigation results indicate that it is reasonable to apply the models to the other jurisdiction with caution. Importantly, where such an application is valid, a key conclusion is that calibration of the models would not be necessary to estimate CMFs and apply them to estimate the potential safety impact of a contemplated treatment.

A bootstrap-based Markov chain Monte Carlo reliability assessment of crash modification factors calculated by full Bayesian method

A bootstrap-based Markov chain Monte Carlo reliability assessment of crash modification factors calculated by full Bayesian method

Evaluation of Direct and Indirect Safety Effects of Speed-Limit Reduction on Urban Networks

This study develops a set of crash modification factors (CMFs) to evaluate the effects of lowering urban-road speed limits on vehicle and pedestrian safety. Cross-sectional methods and observation before–after methods are used to develop CMFs. In general, a CMF estimates the expected change in the frequency of crashes after specific countermeasures are applied on the road. In this study, the safety improvement effect in the section adjacent to the applied section as well as the section for which the policy to lower the speed limit was applied were evaluated. The results indicate that lowering the speed limit is effective in reducing the number of crashes. In particular, the CMFs for crashes involving serious injury and death are 0.6656–0.7804 in the application sections and 0.7979–0.8273 in the adjacent sections. This means that lowering the speed limit can reduce not only the number of crashes but also the occurrence of serious crashes. This study can be used to promote safety by analyzing the effect of the policy to lower the speed limits in the future and can be applied to the evaluation of the effectiveness of various safety policies in cities.

Vehicle collisions analysis on highways based on multi-user driving simulator and multinomial logistic regression model on US highways in Michigan

Traffic collision on the highway has become a serious issue because they delay the sustainable development of society. Highway accidents on I-69 have one of the highest crash rates in the U.S. in Michigan and a higher fatality rate than average. This study aimed to identify the factors contributing to highway user crashes on I-69 in Flint, Michigan. This study also aims to find the relationship between the change in the speed limit in certain weather conditions and the number of crashes that are likely to occur as a sequence of this change. A multi-user driving simulator is applied in this study with ten driving simulator scenarios. The multinomial logistic regression (MNL) model has been investigated in this study to identify statistically significant factors that contribute to crashes. The analyses indicated that speeding and speed limits during inclement road/weather conditions significantly affected crashes. Most frequent crashes occur during snowy and icy weather conditions and by changing the speed limit during these weather conditions. Therefore, driver speed is suspected to be the most factor that caused the Vehicle crash on I-69. The method of developing Crash modification factors (CMFs) used in this study will help to reduce crashes and improve traffic system safety performance on highways in Michigan.

Influence of segmentation approaches on the before-after evaluation of engineering treatments: A hypothetical treatment approach

The segmentation of highways is a fundamental step in estimating crash frequency models and conducting a before-after evaluation of engineering treatments, but the effects of segmentation approaches on the engineering treatment evaluations are not known very well. This study examined the effects of segmentation approaches on the before-after evaluation of engineering treatments. In particular, this study evaluated four segmentation approaches by applying the Empirical Bayes technique to a dataset for which the ground truth was known. Four segmentation approaches included Highway Safety Manual (HSM), Fixed (kilometre post), Fisher’s, and K-means segmentation. This study utilized a 440 km stretch of rural two-lane two-way highway in Queensland, Australia, to prepare a dataset with known ground truth. The treatment under evaluation was a hypothetical treatment, which should yield a crash modification factor (CMF) of 1. For assigning hypothetical treatment, a total of fifteen datasets were prepared, including ten datasets based on the random assignment and five datasets based on the hotspot identification method. Following the before-after evaluation using the Empirical Bayes technique, the results showed that HSM and Fixed segmentation approaches predict the ground truth in both dataset types. From random assignment datasets, the estimated CMFs using HSM, Fixed, Fisher’s, and K-means segmentation approaches deviated from the true CMF (i.e., 1) by 2.32 %, 5.30 %, 6.08 %, and 8.62 %, respectively. In the case of hotspots, the corresponding deviations of CMFs were 8.57 %, 9.37 %, 28.84 %, and 35.43 %, respectively. Overall, HSM segmentation best identified the actual treatment effect, followed by the Fixed segmentation. If the variables to define homogeneity for HSM segmentation are limited, then Fixed segmentation can yield reliable crash modification factors from the before-after treatment evaluations than the crash-based segmentation approaches.

Safety evaluation of centre line, edge line, and dual application rumble strips on Ontario two-lane rural roads

The study builds on previous rumble strip safety evaluations by providing some Canadian-specific experience and in the process offering some definitive insights into differences in safety effects between installations on curved and tangent segments. An empirical Bayes before–after study estimated crash modification factors (CMFs) for installing edge line rumble strips (ELRS) and centerline rumble strips (CLRS), separately and in combination, on two-lane rural roads in Ontario. Separate CMFs were estimated for ELRS and CLRS for curved and tangent segments. The estimated CMFs indicate that rumble strips can be beneficial, except for CLRS on curved segments, and especially if applied in combination on tangents. The results also indicate that edge line and dual rumble strips are more effective on curved segments, so priority should be given to their application on such segments. It is noteworthy that dual application is more safety effective than either CLRS or ELRS, for tangents and overall.

Investigating the Safety Impact of Segment- and Intersection-Level Bicycle Treatments on Bicycle–Motorized Vehicle Crashes

Bicycle treatments are installed to elevate motorists’ awareness of the presence of bicyclists and to enhance bicycle safety and mobility. To date, no studies have compared the safety benefits of sharrows and protected- and conventional bike lanes, or intersection-level treatments like bike boxes and intersection-crossing pavement markings. One factor that limits bicycle safety research is the lack of adequate bicycle exposure data. For this study, a crowdsource app was used for estimating networkwide bicycle demand data for Portland, OR. Crash prediction models were developed for road segments and signalized intersections to associate bicycle treatment presence and type with crash frequency. Compared with the “no treatment” case, protected bike lanes (odds ratio [OR] = 0.032), sharrows (OR = 0.211), and conventional bike lanes (OR = 0.552) were safer for road segments. Signalized intersections where segment-level bicycle treatments exist at more than one of the intersecting roads were associated with higher crash frequency. Specifically, for signalized intersections with one conventional bike lane, with two conventional bike lanes, or with a conventional- and a protected bike lane, the respective CMFs were 1.94, 2.07, and 3.38. Signalized intersections with at least one bike box or intersection-crossing pavement markings experienced higher crash frequency than intersections with no treatments, however not necessarily in the approach where the treatment was located. The respective Crash Modification Factors (CMFs) were 1.39 and 1.76. The findings could guide practitioners in selecting bicycle treatments for segments, whereas the models for signalized intersections could identify intersections with high crash frequency that need safety improvements.

Safety Evaluation of Changing Speed Limit from 55 mph to 60 mph on Two-Lane, Two-Way Road Segments

This paper describes the efforts to evaluate the safety impacts of increasing the speed limit from 55 mph to 60 mph on selected two-lane, two-way state highway road segments in Minnesota, U.S. An empirical Bayes (EB) before–after analysis was used to estimate crash modification factors (CMFs) for both segments (1,909.11 mi) and intersections (1,722 3-leg and 1,191 4-leg). Aggregate analysis conducted using all the segment and intersection data showed a 2.9% increase in total crashes, a 2.5% increase in injury (KABC) crashes, and a 0.05% reduction in the injury (KAB) crashes. These results—along with before-and-after operating speed data from another study by Minnesota Department of Transportation (MnDOT) (2019) showing that the 85th percentile operating speed remained the same and that the mean operating speeds increased by 1 mph following the speed limit increase—can lead to a conclusion that the speed limit increase from 55 mph to 60 mph had a minor effect on combined segment and intersection crashes or operating speeds. It is important to note that these results are specific to the corridors that were selected by MnDOT for the increase in speed limit; caution must be exercised when extending these to systemwide increases in speed limits in Minnesota or in other states, and when estimating long-term effects of speed limit increases as operating speeds can change over a longer period of time.

Dynamic All-Red Extension: An Innovative Safety Countermeasure to Treat Red Light Running Crashes

The purpose of this project was to evaluate the safety effectiveness of Dynamic All-Red Extension (DARE) systems. North Carolina Department of Transportation has used DARE to combat red light running (RLR) crashes on major road approaches of selected rural, isolated traffic signals since 2011. Sixteen intersections were included in the before–after analysis. DARE systems in this study were implemented to target a specific crash type: frontal impact crashes (angle, left turn, right turn, head on) caused by vehicles traveling through the intersection and running the red light. Although there was some variability in the magnitude and significance of the results among treatment groups, there was a general reduction in the frequency of target RLR crashes. The crash modification factor (CMF) using empirical Bayes (EB) methodology was 0.93 (7% reduction in target RLR crashes) for all 16 treatment sites; for seven multilane at two-lane sites where DARE was the sole treatment, CMF was 0.65 (35% reduction in target RLR crashes), which was statistically significant at the 95% confidence level. The benefit–cost ratio of the treatment was 143:1, realized from low installation cost and the high cost of RLR crashes. The treatment appeared promising as a systemic safety treatment applied to isolated intersections with higher speed limits, especially for intersections with multilane major roads. Safety professionals should consider adding this safety countermeasure to the limited list of tools available to treat RLR crashes. DARE was inexpensive, demonstrated safety benefits, and caused minimal delays in rural applications without creating driver habituation.

Crash Modification Functions for Rural Skewed Intersections

This study evaluated the safety influence of intersection skew angle on rural two-lane, two-way facilities by calibrating crash modification factors. Ten years of crash history among federal aid and nonfederal aid highways was used to develop crash modification functions at three-leg and four-leg stop-controlled intersections. Skew angle was investigated as a parameter in the safety performance functions models both as a continuous variable, with observed values ranging from zero to 80°, and categorized into ranges. A few transformations of the skew parameter were considered, such as the flexible-form model having skew interaction with annual average daily traffic, and a Hoerl curve. Both three-leg and four-leg intersections exhibited an initially increasing trend of crash rates followed by a decreasing trend as the skew angle increased. A categorical model was found to best describe the skew relationship using discrete skew angle ranges. Among three-leg intersections, a skew angle between 17° and 27° experienced 22% more crashes than perpendicular intersections. However, more highly skewed three-leg intersections exhibited a decreasing relationship to increasing skew angle. Among four-leg intersections, a skew angle between 17° and 27° experienced 40% more crashes, whereas intersections with a skew angle greater than 45° did not have significantly different crash occurrence than perpendicular intersections. The implications of assuming a monotonic increasing relationship to skew angle are challenged as a result of this study.

Safety Performance of Unsignalized Median U-Turn Intersections

Alternative intersection designs can offer safety and operational benefits with potentially lower costs than conventional intersections when implemented in the proper setting. The Federal Highway Administration has previously identified a subset of alternative designs called reduced left-turn conflict intersections as a proven safety countermeasure. Median U-turn intersections (also known as “Michigan lefts” or “boulevard turnarounds”) are one such design that accommodates all left-turn movements via directional U-turn crossovers within the median. Prior work has consistently shown that median U-turn intersections can provide superior safety performance when used in the appropriate conditions. However, research that is specific to unsignalized reduced left-turn conflict intersections continues to be limited to work conducted before the Highway Safety Manual, or which includes restricted crossing U-turn intersections. This study included the evaluation of historical traffic crashes and volume data at 95 unsignalized intersections in the state of Michigan. This included the collection of data for 39 median U-turn sites and 56 reference group sites to estimate safety performance functions and crash modification factors that can be used when considering future conversions. Ultimately, crash modification factors for fatal and injury crashes of 0.438 and 0.686 are recommended when converting intersections with undivided two-lane two-way major approaches and four-lane divided boulevard major approaches, respectively. Although there was no significant difference in property damage only crashes associated with converting intersections with undivided, two-lane, two-way major approaches, a crash modification factor of 1.325 is recommended for property damage only crashes specific to conversions with four-lane, divided boulevard major approaches.

Safety and Operational Effectiveness of Protected Only Versus Protected/Permitted Left-Turn Signal Phase

Roadway intersection fatalities account for around 24% of total traffic fatalities each year, with left-turning vehicles associated with most of these crashes. To manage left-turning movements, various left-turn signal phases like protected only (PO), protected/permitted left-turn (PPLT), and flashing yellow arrow (FYA) are currently in use. However, their overall effectiveness has not been well established. The paper evaluates the safety and operational effectiveness of PO over PPLT left-turn signal phase using sample intersections from Louisiana. A total of 151 signalized intersections with uniform left-turn signal phases at all of their approaches were selected. Crash data recorded over five years at those intersections comprising a total of 13,278 crashes, including 1,275 left-turn crashes, were collected. A crash modification factor (CMF) was developed using the negative binomial model (NBM) to assess the safety benefits of PO over PPLT. The Highway Capacity Manual 6th Edition (HCM 6) control delay field measurement technique was used for the operational analysis. The study first developed CMFs for total crashes and only left-turn crashes at various severity levels. CMF of PO over PPLT revealed that PO significantly reduced all severity levels of left-turn crashes by more than 50%, however, it was only able to reduce injury and fatal total crashes. Second, the study found average control delay at PO (50.69 s/vehicle) significantly higher than at PPLT (46.04 s/vehicle). The difference in delay was only significant during the morning peak hour. Overall, from both safety and operation perspectives, the results indicate that PO performs better than PPLT.

Investigating the Safety Effectiveness of Wildlife–Vehicle Crash Countermeasures using a Bayesian Approach with a Comparison between Carcass Removal Data and Traditional Crash Data

Wildlife–vehicle crashes (WVCs) pose a significant threat to not only wildlife populations but also highway safety. The most expensive WVC countermeasures include crossing structures with fencing, whereas the least expensive countermeasure is the wildlife warning signs. This study is aimed at estimating the crash modification factors (CMFs) for these two countermeasures using cross-sectional analysis. Two types of WVC data are used in this study: carcass removal data and traditional crash data. A random-intercept Bayesian approach was utilized to incorporate the contributing factors representing traffic volume, roadway geometry, weather conditions, and unobserved heterogeneity resulting from between-site variance. The No-U-Turn Hamiltonian Monte Carlo sampling technique was employed because of its high efficiency in handling complex models. The results suggest that the treatment of implementing wildlife warning signs on hotspots of high WVCs has been ineffective, perhaps because warning signs are passive devices, and the high uncertainty of wildlife interaction still remains. The crossing structures are found to be effective, with an estimated CMF of 0.66 and 0.55 using the carcass data and crash data, respectively. Recommendations could be made to implement more active information dissemination via wildlife-actuated warning signs, where crossing structures may not be feasible. The findings from this study indicate that the carcass removal data are more comprehensive than the crash data, despite the underreporting issue existing in both datasets. Therefore, a unique identifier should be added in both datasets to enable merging the data and obtain more complete results from the analyses.

Safety Effectiveness of the Road Diet Treatment in Rhode Island

A road diet is a low-cost countermeasure which typically involves converting an existing four-lane undivided roadway to a three-lane roadway, reducing the section to two through lanes and a center two-way left-turn lane. The objective of this evaluation was to estimate the safety effectiveness of road diets by developing a crash modification factor (CMF) specific to the U.S. state of Rhode Island. To account for potential selection bias and regression-to-the-mean, an empirical Bayes before-after analysis was conducted, using reference groups of untreated four-lane undivided roadways with similar characteristics to the treated sites. Results indicated a 29% decrease (CMF = 0.71) in total crashes and a 37% reduction in fatal and injury crashes (CMF = 0.63). The expected results of the evaluation will help Rhode Island Department of Transportation to determine a statewide direction for implementation of the countermeasure.