Severity models of cross-median and rollover crashes on rural divided highways in Pennsylvania

Introduction

Crossover and rollover crashes in earth-divided, traversable medians on rural divided highways can lead to severe injury outcomes. This study estimated severity models of these two crash types. Vehicle, driver, roadway, and median cross-section design data were factors considered in the models. A unique aspect of the data used to estimate the models were the availability of median cross-slope data, which are not commonly included in roadway inventory data files.

Methods

A binary logit model of cross-median crash severity and a multinomial logit model of rollover crash severity were estimated using five years of data from rural divided highways in Pennsylvania.

Results

The highest probability of a fatal or major injury in cross-median and rollover crashes was found to occur in cases when a driver was not wearing a seatbelt. While flatter cross-slopes and narrower medians were associated with more severe cross-median crash outcomes, steeper cross-slopes and narrower medians significantly increased rollover crash severity outcomes. The presence of horizontal curves was associated with increased probabilities of high-severity outcomes in a median rollover crash.

Impact on Industry

Modeling results in this study confirmed that cross-median and median rollover crash severity outcomes are associated with median cross-section design characteristics. Based on the estimated models, it appears that flatter and narrower medians lead to more severe injury outcomes in cross-median crashes. Steeper median cross-slopes and narrower medians were associated with higher probabilities of more severe outcomes in median rollover crashes. The results presented in this study suggest that there is a trade-off between median cross-section design and cross-median and rollover crashes in earth-divided, traversable medians on rural divided highways. While the severity models can be included in a framework to develop design guidance in relation to this trade-off, models of crash frequency should also be considered.     

Injury outcomes and costs for cross-median and median barrier crashes

Introduction

The objective of this research was to quantify the injury outcomes and develop reliable and comprehensive injury costs for cross-median crashes (CMC) and median barrier crashes (MBC).

Method

A three-step methodology was developed to quantify the crash costs for each crash severity and type. All CMC and MBC between 2001 and 2007 in Wisconsin were identified and used in this analysis. The Wisconsin CODES database provided comprehensive injury costs based on the injury types and severities suffered by participants in study crashes.

Results

As expected, multi-vehicle CMC result in more total injuries and more severe injuries than single-vehicle CMC. Injury costs for the same injury level on KABCO scale are different for different crash types. Injury costs for concrete MBC are 33% to 50% less than those of multi-vehicle CMC, while the injury costs of concrete MBC for lower severities (B and C) are similar to those of single-vehicle CMC for the same severities; but for incapacitating injuries the costs are 30% less. As expected, concrete MBC result in lower severities than CMC. The costs, by crash severity, vary significantly between different crash types. Concrete median barrier injury crashes are roughly 20% of multi-vehicle CMC costs and 50% of single-vehicle CMC costs.

Conclusions

Results indicate that using one set of crash costs for all crash types biases any evaluation. Therefore, it is recommended that crash-type-specific costs be used in applications such as development of median barrier warrant where specific types of crashes are considered (CMC and MBC).

Impact on industry

Using crash specific costs can lead to a more realistic benefit-cost analysis and enable better decision-making.     

Age and gender differences in conviction and crash occurrence subsequent to being directed to Iowa's driver improvement program

Introduction

This paper investigates potential gender and age differences in conviction and crash occurrence subsequent to being directed to attend Iowa's Driver Improvement Program (DIP).

Methods

Binary logit models were developed to investigate the factors that influence conviction occurrence after DIP by gender and age. Because of the low crash occurrence subsequent to DIP, association rules were applied to investigate the factors that influence crash occurrence subsequent to DIP, in lieu of econometric models.

Results

There were statistical significant differences by driver gender, age, and conviction history in the likelihood of subsequent convictions. However, this paper found no association between DIP outcome, crash history, and crash occurrence.

Impact on industry

Evaluating the differences in conviction and crash occurrence subsequent to DIP between female and male drivers, and among different age groups can lead to improvements of the effectiveness of DIPs and help to identify low-cost intervention measures, customized based on drivers’ gender and age, for improving driving behaviors.     

Efficacies of roadway safety improvements across functional subclasses of rural two-lane highways

Introduction

Highway crash occurrence is a leading cause of unnatural deaths, and highway agencies continually seek to identify engineering measures to reduce crashes and to assess the efficacy of such measures. Most past studies on the effectiveness of roadway improvements in terms of crash reduction considered all rural two-lane sections as a single category of roads. However, it may be hypothesized that the differences in the mobility and accessibility characteristics that are reflected in (and due to) the different design standards between different functional subclasses in the rural two-lane highway system can lead to differences in efficacies of safety improvements at these subclasses. This paper investigates the efficacy of roadway improvements, in terms of crash reduction, at the various subclasses of rural two-lane highways.

Methods

An empirical analysis of safety performance at each of the three subclasses of rural two-lane highways was carried out using the negative binomial modeling technique. For each subclass, crash prediction models were developed separately for the three levels of crash severity: property-damage only, injury, and fatal/injury. The crash factors that were considered include lane width, shoulder width, pavement surface friction, pavement condition, and horizontal and vertical alignments. After having developed the safety performance functions, the effectiveness (in terms of the extent of crash reduction, for different levels of crash severity) of highway safety enhancements at each highway subclass were determined using the theoretical concepts established in past literature. These enhancements include widening lanes, widening shoulders, enhancing pavement surface friction, and improving the vertical or horizontal alignment.

Results and Conclusion

The study found that there is empirical evidence to justify the decomposition of the family of rural two-lane roads into its constituent subclasses for purposes of analyzing the effectiveness of safety enhancement projects and thus to avoid underestimation or overestimation of benefits of safety improvements at this class of highways.     

Case-control and cross-sectional methods for estimating crash modification factors: comparisons from roadway lighting and lane and shoulder width safety effect studies

Problem

While observational before-after studies are considered the industry standard for developing crash modification factors (CMFs), there are practical limitations that may preclude their use in highway safety analysis. There is a need to explore alternative methods for estimating CMFs.

Method

This paper employs case-control and cross-sectional analyses to estimate CMFs for fixed roadway lighting and the allocation of lane and shoulder widths.

Results

Based on the case-control method, the CMF for intersection lighting is 0.886, while the cross-sectional study indicates a CMF of 0.881. The CMFs developed for lane and shoulder widths are also similar when comparing the two methods.

Conclusions

This paper suggests that case-control and cross-sectional studies produce consistent results if care is taken in the study design and model development.

Impact on industry

Case-control and cross-sectional studies may provide a viable alternative to estimate CMFs when a before-after study is impractical due to data restrictions.     

Injury crashes with bicyclists at roundabouts: influence of some location characteristics and the design of cycle facilities

Problem

Previous research indicated that conversions of intersections into roundabouts appear to increase the number of injury crashes with bicyclists. However, it was assumed that the effectiveness of roundabouts could vary according to some differences in design types of cycle, facilities and other geometrical factors.

Method

Regression analyses on effectiveness-indices resulting from a before-and-after study of injury crashes with bicyclists at 90 roundabouts in Flanders, Belgium.

Results

Regarding all injury crashes with bicyclists, roundabouts with cycle lanes appear to perform significantly worse compared to three other design types (mixed traffic, separate cycle paths, and grade-separated cycle paths). Nevertheless, an increase of the severest crashes was noticed, regardless of the design type of the cycle facilities. Roundabouts that are replacing signal-controlled intersections seem to have had a worse evolution compared to roundabouts on other types of intersections.

Impact on industry

The results might affect design guidelines for roundabouts, particularly for the accommodation of bicyclists.     

Effects of red light camera enforcement on fatal crashes in large U.S. cities

Objective

To estimate the effects of red light camera enforcement on per capita fatal crash rates at intersections with signal lights.

Methods

From the 99 large U.S. cities with more than 200,000 residents in 2008, 14 cities were identified with red light camera enforcement programs for all of 2004-2008 but not at any time during 1992-1996, and 48 cities were identified without camera programs during either period. Analyses compared the citywide per capita rate of fatal red light running crashes and the citywide per capita rate of all fatal crashes at signalized intersections during the two study periods, and rate changes then were compared for cities with and without cameras programs. Poisson regression was used to model crash rates as a function of red light camera enforcement, land area, and population density.

Results

The average annual rate of fatal red light running crashes declined for both study groups, but the decline was larger for cities with red light camera enforcement programs than for cities without camera programs (35% vs. 14%). The average annual rate of all fatal crashes at signalized intersections decreased by 14% for cities with camera programs and increased slightly (2%) for cities without cameras. After controlling for population density and land area, the rate of fatal red light running crashes during 2004-2008 for cities with camera programs was an estimated 24% lower than what would have been expected without cameras. The rate of all fatal crashes at signalized intersections during 2004-2008 for cities with camera programs was an estimated 17% lower than what would have been expected without cameras.

Conclusions

Red light camera enforcement programs were associated with a statistically significant reduction in the citywide rate of fatal red light running crashes and a smaller but still significant reduction in the rate of all fatal crashes at signalized intersections.

Impact on Industry

The study adds to the large body of evidence that red light camera enforcement can prevent the most serious crashes. Communities seeking to reduce crashes at intersections should consider this evidence.     

Trends and characteristics of animal-vehicle collisions in the United States

Introduction

Since 1990, fatal animal-vehicle collisions (AVCs) in the United States have more than doubled. This paper examines annual AVC trends in the United States over a 19-year period, seasonal and diurnal patterns of AVC risk, the geographic distribution of crash risk by state, and the association between posted speed limit and AVC crash risk in darkness.

Method

AVCs were compiled from the Fatality Analysis Reporting System (FARS) and the General Estimates System (GES) for the years 1990-2008 to examine annual crash trends for fatal and nonfatal crashes. Seasonal trends for fatal AVCs were examined with the aggregated FARS dataset; seasonal trends for fatal and nonfatal AVCs were also examined by aggregating four years of Michigan crash data. State-by-state distributions of fatal AVCs were also described with the aggregated FARS dataset. Finally, the relationship between posted speed limit and the odds that a fatal or nonfatal AVC occurred in darkness were examined with logistic regressions using the aggregated FARS and Michigan datasets.

Results

Between 1990 and 2008, fatal AVCs increased by 104% and by 1.3 crashes per trillion vehicle miles travelled per year. Although not all AVCs involve deer, daily and seasonal AVC crash trends follow the general activity pattern of deer populations, consistent with prior reports. The odds that a fatal AVC occurred in darkness were also found to increase by 2.3% for each mile-per-hour increase in speed; a similar, albeit smaller, effect was also observed in the aggregated Michigan dataset, among nonfatal crashes.

Conclusion

AVCs represent a small but increasing share of crashes in the United States. Seasonal and daily variation in the pattern of AVCs seem to follow variation in deer exposure and ambient light level. Finally, the relative risk that a fatal and nonfatal AVC occurred in darkness is influenced by posted speed limit, suggesting that a driver's limited forward vision at night plays a role in AVCs, as it does in pedestrian collisions.

Impact on Industry

The association between speed limit and crash risk in darkness suggests that AVC risk might be reduced with countermeasures that improve a driver's forward view of the road.     

Investigating factors influencing pedestrian injury severity at intersections

Objective: Vehicle crashes that involve pedestrians at intersections have been reported occasionally. Pedestrian injury severity in these crashes is significantly related to driver and pedestrian attributes, vehicle characteristics, and the geometry of intersections. Identifying factors associated with pedestrian injury severity (PIS) is critical for reducing crashes and improving safety. For developing the proposed probit models, drivers involved in crashes are classified into 3 groups: young drivers (16 ≤ age ≤ 24), middle-aged drivers (25 ≤ age ≤ 64), and older drivers (age ≥ 65). This study determines that PIS is significantly but differently affected by these grouped drivers with different sets of explanatory variables.

Methods: A total of 2,614 crash records (2011–2012) at intersections in Cook County, Illinois, were collected. An ordered probit modeling approach was employed to develop the proposed model and examine factors influencing PIS. The likelihood ratio test was used to assess model performance. Elasticity analysis was conducted to interpret the marginal effect of contributing factors on PIS associated with different driver groups by age.

Results: The results show that 4 independent variables, including pedestrian age, vehicle type, point of first contact, and weather condition, significantly affect PIS at intersections for all drivers. Two additional independent variables (i.e., number of vehicles and traffic type) affect PIS for young and middle-aged drivers, and 2 other variables (i.e., divided type and hit-and-run related) are significant to PIS for both young and older drivers.

Conclusions: The independent variables significant to PIS at intersections for young, middle-aged, and older driver groups were identified and the marginal effect of each variable to the likelihood of PIS were assessed.     

Crash involvement during the different phases of the New Zealand Graduated Driver Licensing System (GDLS)

Introduction

The New Zealand Graduated Driver Licensing System (GDLS) is designed to allow novice drivers to gain driving experience under conditions of reduced risk.

Method

To examine the effectiveness of the GDLS, an analysis of how the crash involvement of novice drivers changes as drivers move through the GDLS was undertaken. Crash profiles were created by data matching the New Zealand license and crash databases, covering a time period from 1999-2006.

Results

The crash profiles show that the initial learner period of the GDLS is relatively safe and the time at which novice drivers have the highest rate of crash involvement is during the first few months of solo driving. Analysis using logistic regression also showed an effect of age and gender, with higher crash involvement associated with younger drivers and males. In addition, individuals who gained a full license within 12-18 months of holding a restricted license, due to completion of a time-discount associated educational program, had a higher level of involvement in crashes than individuals who gained a full license after 18 months.

Conclusions

The crash profiles provide an insight into the crash risk associated with different phases of the New Zealand GDLS.

Impact on Industry

Increasing the age at which drivers first begin to solo drive and the removal of the time-discount associated with completion of an educational program should be considered.     

Pediatrician attitudes, knowledge, and practice behavior regarding teen driving safety

Problem

Each year about 4,000 teens ages 16-19 die on U.S. roads. Injury prevention counseling is recommended as a valuable and cost-effective part of routine health supervision. This study describes pediatrician knowledge and practice regarding teen driving safety.

Methods

A 31-item self-administered survey was mailed to pediatricians.

Results

160 of 392 pediatricians (41%) completed the survey. During a health supervision visit 93% of pediatricians reported discussing seat belt use, 89% impaired driving, 54% teen licensing laws, and 16% parent teen contract. Half reported having a teen in their practice killed in a crash.

Conclusions

A majority surveyed report discussing and counseling teens on first wave teen driver safety issues (seat belts, alcohol use), but most do not discuss graduated driver licensing laws or related issues. Impact on Industry: Broadly adopted, this inexpensive counseling approach, could lead to reductions in teen motorvehicle crash injuries.     

A traffic safety evaluation of California's traffic violator school citation dismissal policy

Introduction

This study evaluated California's traffic violator school (TVS) citation dismissal policy.

Method

This study identified and compared two large samples of drivers either completing a TVS (N = 210,015) or convicted of a traffic citation (N = 168,563).

Results

Prior to adjudication, the TVS group had characteristics (e.g., lower prior conviction rate and smaller proportion of males) that were predictive of a lower subsequent crash risk. However, the TVS group exhibited significantly more crashes than did the convicted group in the subsequent one-year period. The difference (4.83%) increased to 10% after adjusting for the more favorable characteristics of the TVS group. The TVS group also had a higher adjusted subsequent crash rate at each prior driver record entry level, reflecting a loss in the general and specific deterrence of the non-conviction masked status of TVS dismissed citations. It was reported that the TVS dismissal policy results in approximately 12,300 additional crashes annually with economic costs of approximately $398,000,000.

Conclusions

The avoidance of licensing actions resulting from the dismissal policy assists in explaining why the driving public is exposed to an increased crash risk. A number of recommendations are offered to reduce the negative traffic safety impact of the TVS citation dismissal policy.     

A method for simplifying the analysis of traffic accidents injury severity on two-lane highways using Bayesian networks

Introduction

This study describes a method for reducing the number of variables frequently considered in modeling the severity of traffic accidents. The method's efficiency is assessed by constructing Bayesian networks (BN).

Method

It is based on a two stage selection process. Several variable selection algorithms, commonly used in data mining, are applied in order to select subsets of variables. BNs are built using the selected subsets and their performance is compared with the original BN (with all the variables) using five indicators. The BNs that improve the indicators’ values are further analyzed for identifying the most significant variables (accident type, age, atmospheric factors, gender, lighting, number of injured, and occupant involved). A new BN is built using these variables, where the results of the indicators indicate, in most of the cases, a statistically significant improvement with respect to the original BN.

Conclusions

It is possible to reduce the number of variables used to model traffic accidents injury severity through BNs without reducing the performance of the model.

Impact on Industry

The study provides the safety analysts a methodology that could be used to minimize the number of variables used in order to determine efficiently the injury severity of traffic accidents without reducing the performance of the model.     

Using conditional inference forests to identify the factors affecting crash severity on arterial corridors

Introduction

The study aims at identifying traffic/highway design/driver-vehicle information significantly related with fatal/severe crashes on urban arterials for different crash types. Since the data used in this study are observational (i.e., collected outside the purview of a designed experiment), an information discovery approach is adopted for this study.

Method

Random Forests, which are ensembles of individual trees grown by CART (Classification and Regression Tree) algorithm, are applied in numerous applications for this purpose. Specifically, conditional inference forests have been implemented. In each tree of the conditional inference forest, splits are based on how good the association is. Chi-square test statistics are used to measure the association. Apart from identifying the variables that improve classification accuracy, the methodology also clearly identifies the variables that are neutral to accuracy, and also those that decrease it.

Results

The methodology is quite insightful in identifying the variables of interest in the database (e.g., alcohol/ drug use and higher posted speed limits contribute to severe crashes). Failure to use safety equipment by all passengers and presence of driver/passenger in the vulnerable age group (more than 55 years or less than 3 years) increased the severity of injuries given a crash had occurred. A new variable, ‘element’ has been used in this study, which assigns crashes to segments, intersections, or access points based on the information from site location, traffic control, and presence of signals.

Impact

The authors were able to identify roadway locations where severe crashes tend to occur. For example, segments and access points were found to be riskier for single vehicle crashes. Higher skid resistance and k-factor also contributed toward increased severity of injuries in crashes.     

Injury severity analysis of accidents involving young male drivers in Great Britain

Introduction

Young male drivers are over-represented in traffic accidents; they were involved in 14% of fatal accidents from 1991 to 2003 while holding only 8% of all drivers licenses in the UK. In this study, a subset of the UK national road accident data from 1991 to 2003 has been analyzed. The primary aim is to determine how to best use monetary and progressive resources to understand how road safety measures will reduce the severity of accidents involving young male drivers in both London and Great Britain.

Method

Ordered probit models were used to identify specific accident characteristics that increase the likelihood of one of three categorical outcomes of accident severity: slight, serious, or fatal.

Results

Characteristics found to lead to a higher likelihood of serious and fatal injuries are generally similar across Great Britain and London but are different from those predicted to lead to a higher likelihood of slight injuries. Those characteristics predicted to lead to serious and fatal injuries include driving in darkness, between Friday and Sunday, on roads with a speed limit of 60 mph, on single carriageways, overtaking, skidding, hitting an object off the carriageway, and when passing the site of a previous accident. Characteristics predicted to lead to slight injuries include driving in daylight, between Monday and Thursday, on roads with a speed limit of 30 mph or less, at a roundabout, waiting to move, and when an animal is on the carriageway.

Impact on Industry

These results aid the selection of policy options that are most likely to reduce the severity of accidents involving young male drivers.     

A classification tree based modeling approach for segment related crashes on multilane highways

Introduction

This study presents a classification tree based alternative to crash frequency analysis for analyzing crashes on mid-block segments of multilane arterials.

Method

The traditional approach of modeling counts of crashes that occur over a period of time works well for intersection crashes where each intersection itself provides a well-defined unit over which to aggregate the crash data. However, in the case of mid-block segments the crash frequency based approach requires segmentation of the arterial corridor into segments of arbitrary lengths. In this study we have used random samples of time, day of week, and location (i.e., milepost) combinations and compared them with the sample of crashes from the same arterial corridor. For crash and non-crash cases, geometric design/roadside and traffic characteristics were derived based on their milepost locations. The variables used in the analysis are non-event specific and therefore more relevant for roadway safety feature improvement programs. First classification tree model is a model comparing all crashes with the non-crash data and then four groups of crashes (rear-end, lane-change related, pedestrian, and single-vehicle/off-road crashes) are separately compared to the non-crash cases. The classification tree models provide a list of significant variables as well as a measure to classify crash from non-crash cases. ADT along with time of day/day of week are significantly related to all crash types with different groups of crashes being more likely to occur at different times.

Conclusions

From the classification performance of different models it was apparent that using non-event specific information may not be suitable for single vehicle/off-road crashes.

Impact on Industry

The study provides the safety analysis community an additional tool to assess safety without having to aggregate the corridor crash data over arbitrary segment lengths.     

The Long Beach/Fort Lauderdale relative risk study

Problem

The role of alcohol as a major factor in traffic crash causation has been firmly established. However, controversy remains as to the precise shape of the relative risk function and the BAC at which crash risk begins to increase.

Methods

This study used a case-control design in two locations: Long Beach, California, and Fort Lauderdale, Florida. Data were collected on 2,871 crashes of all severities and a matched control group of drivers selected from the same time, location, and direction of travel as the crash drivers. Of the 14,985 sample drivers, 81.3% of the crash drivers and 97.9% of the controls provided a valid BAC specimen.

Results

When adjusted for covariates and nonparticipation bias, increases in relative risk were observed at BACs of .04-.05, and the elevations in risk became very pronounced when BACs exceeded .10.

Discussion

The results provide strong support for .08 per se laws and for state policies that increase sanctions for BACs in excess of .15.

Impact on Industry

This study provides further precision on the deleterious effects of alcohol on driving and, by implication, on other complex tasks.     

Are drivers' comparative risk judgments about speeding realistic?

Introduction

This study focused on comparative judgments about speeding risks among young drivers who have a high risk of being involved in a traffic accident.

Method

We examined (a) how these drivers assess their risk of sanctions and their risk of causing an automobile crash because of speeding in comparison to the estimated risks of other drivers, and (b) how realistic their comparative risk judgments are. We measured the relationship between the drivers' comparative risk judgments, self-reported speeding, and driving-related sensation-seeking. We hypothesized that (a) they would think they have less risk of sanctions and of causing a car accident than others, and (b) their comparative judgments of speeding risks would be linked to self-reported speeding and driving-related sensation-seeking. The study was based on a computerized questionnaire survey conducted with 3,002 young drivers (mean age = 22.3) administered by professional investigators.

Results

The results confirmed our hypotheses.

Impact on Industry

In order to improve the effectiveness of prevention measures and to evaluate the effect of them, road-safety interventions should take into account comparative risk judgments about the targeted risk behavior.     

A Bayesian assessment of the effect of highway bypasses in Iowa on crashes and crash rate

Introduction

A common contention is that the construction of highway bypasses negatively impacts the economy of local communities by reducing pass-by traffic for businesses. However, as access to specific business' account records is limited, this impact is difficult to quantify. Another common contention is that bypasses contribute to a reduction in overall crashes in the community and in the surrounding areas. Even though a large number of bypasses have been constructed in the State of Iowa over the past several years, their actual impact in terms of traffic safety has not been quantified.

Objectives

This study seeks answers to the following questions: (a) Are bypasses in Iowa associated with a reduction in crash frequencies and crash rates on the bypassed highway? (b) Do bypasses in Iowa introduce a reduction of overall crash frequencies and rates or do they merely shift crashes from the highways through the communities to the bypasses with no significant overall reduction?

Method

We obtained crash information from the Iowa DOT at 19 sites on which a bypass was constructed sometime during the past 23 years. We also obtained the same information at six sites used as comparison sites on which no bypasses were constructed at least until 2005. We them employed a Bayesian approach to estimating the association between the construction of the bypass and crash rates, while also accounting for other factors.

Results

The construction of bypasses in Iowa is associated with a significant increase in traffic safety both on the main road through town and on the combined main road and bypass roadway.     

The efficiency of using non-culpable crash-claim involvements from insurance data as a means of estimating travel exposure for road user sub-groups

Introduction

Induced exposure has a long history of development and usage in traffic safety research but a major question has always concerned the extent to which the accumulation of culpable and non-culpable involvements can be considered independent.

Method

Culpability assessments of 32,630 vehicles' crash-claim involvements adjudicated by insurance adjusters were matched with vehicle odometer readings taken at emission testing using consistent identification of vehicles and principal operators over a 5-year period.

Result

It was found that the accumulation of culpable crash involvements was not entirely independent of that for non-culpable involvements. However, the rate of non-culpable involvements was determined to be an acceptable surrogate for travel exposure rate where sample sizes were large.

Discussion

The relationship between the rate of non-culpable involvements and the rate of travel exposure for data subsets when both were normalized by the overall sample rates was reminiscent of an accident-volume curve for roadway locations in traffic engineering theory. This suggested that only a portion of non-culpable involvements actually related directly to travel and this lead to a correction factor that could be applied.

Impact on Industry

While lack of independence of involvement rates may be problematic for a direct risk ratio application, it does not invalidate the use of non-culpable involvements to predict travel. For insurers that have a need to estimate travel amounts for different driver/vehicle groups as part of the insurance rating purposes, this can be a useful application.