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50 patterns are different. This fact is important when choosing a becomes more obvious along the shorter roadway segments database for public information purposes, future research ac- (Figure 5). The plots and safety measures calculated as part of tivities, and countermeasure implementation/evaluation this project also indicate that the two databases define the mag- choices. The objectives of the activities and the validity of the nitude of the animal collision problem differently. In addition, databases available need to be considered. the prediction models developed for reported WVCs and deer The GIS figures, summary data, and models developed as carcass removals had different coefficients and/or input part of this research could be useful to the IaDOT, but require variables. The use of any of these guides to set WVC-related recalculation and/or recalibration for application in other policies or determine potential locations for WVC counter- states. For example, the statewide tallies and rates in Tables 15 measures will likely produce different and possibly less efficient and 16 can be used for an initial or gross comparison to the and effective results. The choice of safety measures (e.g., WVCs WVC or deer carcass removal experience along particular per year) may also impact the results of any comparison. It is roadway segments. Potential hotspot locations for WVCs or important to understand the basis and defining criteria of the deer carcass removals might be defined initially for further ex- database(s) being considered. amination. In the following discussion, the focus is on the im- pact of the reported WVCs and deer carcass removal compar- Some of the difference in the reported WVC and deer ison results rather than the direct application of the plots, carcass removal GIS plot patterns, safety measures, and mod- measures, and models calculated. Some of the challenges els are the result of different data collection patterns and related to combining and presenting these data in a GIS approaches (e.g., spatial accuracy and consistency). Another platform are also discussed. portion of the difference is likely because often more carcasses are removed than WVCs reported to the police (i.e., the dataset WVC and carcass removal GIS activities. The combi- size is different). For example, WVCs that result only in prop- nation of collision and carcass data within a GIS platform, if erty damage are reported only if an estimated minimum dollar available by location, can be difficult. The importation of dif- amount of vehicle damage results (e.g., $1,000). Therefore, ferent datasets into a GIS platform requires the definition reported WVC data might best describe the more serious WVC and compatibility of the systems used to locate these data. In events, and carcass removal data might best describe the overall this project, the objective was to have WVC and deer carcass number of conflicts between vehicles and animals. Unfortu- removal information in the same GIS platform for compar- nately, the reporting of WVCs (even if the minimum property ison and modeling purposes. The locations of the WVCs damage requirement is met) appears to vary widely from state were available in latitude and longitude for the 3 years con- to state and carcass removal locations are not typically collected sidered, however, the deer carcass removal locations were es- in any consistent manner. Whether one or both datasets can or timated to the nearest 0.1 milepost and, because of project should be used within a particular state needs to be decided on constraints, could only be summed, plotted, and modeled to a case-by-case basis. As indicated earlier, similar accuracy and the nearest milepost. The deer carcass removals were plotted consistency in the collection of both types of data are also as proportional circles to represent the different number of desirable. This similarity allows the proper visual or quantita- removals at one location (rather than stacked), but the tive combination and comparison of the databases. reported WVCs (located by latitude and longitude) were plotted individually. As noted throughout this report, these Conclusions and Suggested Research differences in accuracy and data collection did have an im- pact on the comparison results, but were not considered Ambitious objectives were set out in defining a plan of work atypical. It is also unlikely the conclusions of this research for the safety data analysis for this project. These objectives would change if the spatial accuracy and/or plotting were were complementary to the overall project objectives to pro- more similar. However, a similar accuracy and consistency vide guidance in the form of clearly written guidelines for the in the collection of both types of data would be desirable, but selection of crossing types, their configuration, their appro- is not currently typical at DOTs. The availability of WVCs, priate location, monitoring and evaluation of crossing effec- deer carcass removals, and roadway cross section informa- tiveness, and maintenance. The significant progress that has tion within a GIS platform did, however, allow a relatively been made in achieving these safety data analysis objectives is easy summary, comparison, and modeling of the Iowa data. summarized as bulleted conclusions for this part of the proj- ect. Yet, further effort and consideration are needed because Statewide, example corridor, and model comparisons. The of limitations in data currently available to effectively address statewide and sample transportation corridor reported WVC all of the objectives set out and because of the implications of and deer carcass removal patterns in the GIS plots of this re- some of the findings. Recommendations for further work and port are clearly different (Figure 4 and 5). The difference considerations are identified in a separate subsection.

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51 Conclusions used to define the WVC problem, but the results will often differ. Aspect 1: Application of reported wildlifevehicle colli- The WVC and deer carcass removal data used in this sion data. This aspect of the work involved the develop- research was obtained from the IaDOT. These two datasets ment of safety performance functions and illustrated their were collected with different methods and at different lev- potential applications related to the objectives of the project, els of accuracy. This situation is not surprising, but it did rather than investigative research. Nevertheless, a few con- lead to some challenges related to their combination and clusions may be drawn: comparison in a GIS platform. The WVC data from 2001 Safety performance functions were successfully calibrated to 2003 was available by latitude and longitude, but the deer carcass removal locations were adjusted to the closest for four states (in addition to that calibrated for Aspect 2) to milepost and summed. The impacts of modifying the deer relate police-reported wildlifevehicle collisions to variables carcass removal locations on the results of this research are normally available in state DOT databases. For these func- noted where appropriate. tions, AADT was the dominant variable, with additional sig- A quantitative summary of the 2001 to 2003 WVC and deer nificant variables, such as speed, lane and shoulder width, carcass removal data used in this research confirmed that and median type, making relatively small contributions to there is a difference in their magnitude. There are more deer the explanatory power of the SPFs. The SPFs varied considerably across states in terms of the carcasses removed than WVCs reported. In addition, and not surprisingly, the WVC and deer carcass removal data are effect of the key AADT variable. The empirical Bayes procedure can be used to combine collected from different types of roadways. IaDOT primarily removes deer carcasses from interstates and U.S. Highways. SPF predictions with WVC history to better estimate a lo- A greater percentage of the police-reported WVCs occur on cation's safety in accounting for key factors such as animal farm to market routes and local roadways. movements not in the SPFs. A visual comparison of statewide and regional WVC and The empirical Bayes estimate can be used for screening the road network to identify candidate locations for WVC deer carcass removal plots support the hypothesis that the countermeasures. However, for situations where SPFs, or data from these two databases may result in the identifica- the resources required to calibrate them, are not available, tion of different roadway segments as potential locations of a method that ranks locations according to their propor- concern. A similar comparison along example segments of tion of WVCs can produce reasonable results. Interstate 80 and U.S. Highway 18 resulted in the same conclusion. A quantitative comparison of the WVC and An illustration was presented of the application of SPFs deer carcass removal safety measures along these segments in an empirical Bayes before-after study of safety effective- to relevant statewide calculations also supported the con- ness of a wildlife crossing installation. Sufficient installation clusion that the choice of dataset (e.g., WVC or deer data were not available to enable the formal study that was carcass removal) does matter. In addition, and not envisaged. surprisingly, the choice of the safety measure used in the comparison also has an impact. The data used, type of Aspect 2: Comparison of wildlifevehicle collision and safety measure calculated, and the analysis approach carcass removal data. The following conclusions are based applied all impact how "high" collision locations are iden- on the data combination, comparison, and analysis activities tified. Some of the differences observed in the data and the previously described. The general objective of these activities models developed are caused by the dissimilarity in the ac- was to visually and quantitatively determine whether the use curacy and plotting approach of the WVC and deer carcass of WVC and deer carcass removal data might lead to the removal data used. identification of different roadway segments for potential WVC and deer carcass removal regression models were countermeasure implementation. created for rural two-lane and multilane roadways. The rural two-lane and multilane roadway WVC and deer Police-reported WVC and/or deervehicle collision carcass removal models have different coefficients (DVC) data by roadway location are available throughout and/or variables. The results of these WVC and deer car- the United States, but animal or deer carcass removal data cass removal prediction models would be different for by location are rarely collected and/or summarized. the same roadway segment. This difference could impact Carcass removal data may sometimes be available for decisions related to countermeasure implementation. short periods of time and/or for specific roadway seg- Overall, the WVC models generally had better explana- ments, but is not typically collected consistently through- tory value than the deer carcass removal models, and the out a state for many years. Both of these databases can be deer carcass removal models should be used with caution

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52 due to their high overdispersion parameters. The WVC and Aspect 2: Comparison of wildlifevehicle collision and deer carcass removal models that included only AADT did carcass removal data. not appear to be dramatically different in their predictive capability than the models that included additional cross The use of police-reported WVCs to identify potential section variables. The proper use and calibration of these countermeasure locations may only define a portion of a models is explained in other sections of this report. statewide or corridor-specific wildlife collision problem. There is some potential to the use of WVC prediction The locations identified as "high" reported WVC locations models for the estimation of deer carcass removals along may not be the same as those identified as "high" wildlife a roadway segment, but a suitable database of deer carcass or deer carcass removal locations. removals needs to be available for recalibrating the WVC Currently, some type of police-reported animalvehicle/ model. More research is needed on the value of this type deervehicle collision (AVC/DVC) data is typically avail- of application. able at every state transportation agency. The total number and location of deer carcass removals, on the other hand, are rarely collected consistently statewide. For this type of Recommendations situation, the research team recommends that reported Aspect 1: Application of reported wildlifevehicle colli- AVC/DVC data should be used if safety improvements are sion data. the primary objective, and deer or animal carcass removal data (if not available by roadway location) should be used Empirical Bayes procedures, using the safety performance for public education and to describe the magnitude of the functions presented and police-reported WVCs (where animal collision problem from an ecological point of view. accurate carcass removal data are unavailable), can be used However, when the following recommendation is accom- for several tasks related to the project objectives: plished, a more well-defined application of both databases Network screening to identify candidate roadway would be desirable. The collection of statewide or corridor-specific WVCs or segments for WVC countermeasures; DVCs and large-animal carcass removal locations is rec- Evaluation of the safety effectiveness of wildlife crossing ommended to define the magnitude and patterns of the installation and other WVC countermeasures; and safety concerns related to this issue. The consistent collec- Estimation of the cost effectiveness, specifically the tion and plotting of both types of data with the same spa- safety benefits, of a contemplated wildlife crossing or tial accuracy is desirable. other WVC countermeasure. When feasible and available, both WVCs or DVCs and Sufficient data should be collected to enable a full study of large-animal carcass removal locations are recommended the safety effectiveness of crossings installed, using the for use in combination to help define the magnitude and methodology illustrated in previous sections. A minimum patterns of this safety concern both statewide and along of 20 installations should provide useful results. specific corridors. However, the double counting of An expert panel, similar to panels conducted recently for animalvehicle collisions should be avoided; e.g., deer car- traffic engineering countermeasures under NCHRP 17-25, cass removals should be ignored that occur at the same should be convened to develop collision modification fac- time and location as a reported WVC or DVC. In this case, tors for WVC countermeasures. These factors are used to the attributes collected with the animal or deer removal estimate the safety benefits of a contemplated wildlife (e.g., gender, estimated age, and species) might be trans- crossing or other WVC countermeasure. ferred, if possible, to the reported WVC database. For application in states other than those for which SPFs The models developed in this research are recommended for are presented, it is most desirable to develop SPFs for that use only after they are appropriately calibrated and the users state's data. Where such development is not possible, an understand the limitations of the models. The results of SPF from one of the four states for which SPFs are these models should be appropriately applied within an em- presented can be applied, but it should be recalibrated to pirical Bayesian approach. The empirical Bayesian approach reflect differences across time and space in factors such as and model calibration of these types of models are explained collision reporting practices, weather, driver demograph- within several sections and appendices of this report. The ics, and off-roadway variables such as wildlife movements. development of AVC/DVC models with more reported and A procedure for doing this recalibration is presented in carcass removal data is also recommended. Models that ad- Appendix A. To determine which of the four models is just for the severity (e.g., property-damage-only, injury, and best to adopt for another state, some goodness-of-fit tests fatality) of the large-animal or deervehicle collisions may will need to be conducted. A summary of these tests is also be useful (if there is enough variability in this collision presented as part of Appendix B. characteristic). In general, it might be assumed that deer or