Relating Vehicle-Wildlife Crashes to Road Reconstruction · (HCM) Two-Lane Highway methodology was used to estimate average travel speed based on roadway features, such as lane width,

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Relating Vehicle-Wildlife Crashes to Road Reconstruction

Christopher S Vokurka, Graduate Research Assistant

Department of Civil & Architectural Engineering University of Wyoming

1000 E. University Avenue, Dept. 3295 Laramie, WY 82071-3295

Voice: 307-766-3427 Fax: 307-766-2221

Email: [email protected]

Rhonda K Young, Assistant Professor Department of Civil & Architectural Engineering

University of Wyoming 1000 E. University Avenue, Dept. 3295

Laramie, WY 82071-3295 Voice: 307-766-2184 Fax: 307-766-2221

Email: [email protected]

Word Count : 3,422+ (6 * 250) = 4,922

Submitted on August 1, 2007 to

Transportation Research Board

86th Annual Meeting January 13-17, 2008

Washington, DC

TRB 2008 Annual Meeting CD-ROM Original paper submittal - not revised by author.

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ABSTRACT Animal-vehicle crashes are a growing trend in America, particularly in rural states such as Wyoming. This research focuses on determining the effect of road reconstruction on the number of reported wild animal crashes using changes in the animal-vehicle crash rates along those segments of roadway. Using GIS tools, the Wyoming highway system was analyzed to locate sections of roadway where animal-vehicle crashes were occurring. From these sections, seven reconstruction projects were selected for the study. Statistical analyses were performed with a focus on crash rates. The seven sections were analyzed as an aggregate data set and it was determined that wild animal-vehicle crash rates increased following reconstruction. During this same time period, crash rates not associated with animal-vehicle crashes, as well as the overall crash rate, generally decreased. Changes in roadway design attributes were analyzed, and the only attribute observed to have a statistically significant impact on the animal-vehicle crash rate was design speed. Keywords: Reconstruction, Safety, Wildlife, Wyoming, WYDOT

INTRODUCTION It is not unusual for motorists driving frequently throughout Wyoming and almost any other rural area to have a near miss with some sort of wild animal, most often deer, at some point during their travels. This type of conflict is so frequent that it is considered an unavoidable risk of rural driving. In rural areas, some of the most common types of vehicular accidents involve large animals. There are over 1.5 million impacts with deer every year, resulting in 150 lives lost and more than one billion dollars in damage (1). In Wyoming alone, there were more than 16,000 reported accidents involving wild animals between 1995 and 2005 according to data from the Wyoming Department of Transportation’s Safety Program. These collisions resulted in 14 human deaths. This same data indicates that this problem is increasing every year, as shown in Figure 1. During this time period, the total vehicle miles traveled in Wyoming increased from 4.7 billion miles per year to 6.2 billion miles per year, an increase of 32%, while the reported animal-vehicle crashes increased 99% (2).

One factor in the increase in animal-vehicle crashes (AVCs) may be that many of Wyoming’s rural two-lane highways are being reconstructed to bring them up to modern lane and shoulder width standards. There are two competing philosophies concerning roadway improvements’ effects on AVC safety concerns. One is that the increased sightlines, clear spaces, and improved geometries of the reconstructed road will result in lower vehicle-wildlife crash rates because drivers will have greater visibility and more time and room to react. The other philosophy is that the improvements encourage drivers to drive at higher speeds and that will ultimately lead to higher AVC rates. This research effort aims to determine the effects of roadway reconstruction on AVC rates and whether particular roadway features are associated with high AVC rates.


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Figure 1: Reported Animal-Vehicle Crashes in Wyoming, 1995-2004 PREVIOUS RESEARCH There is considerable literature available on the subject of animal-vehicle collisions. Previous work looked at the time of day and season that AVCs were more likely to occur and the age of the animals that were typically involved in the crashes (3,4). Other factors such as roadside vegetation, cover, and mineral deposits have also been studied (5, 6). The majority of the research covered the types and effectiveness of different AVC countermeasures such as signing, fencing, wildlife crossing structures, and animal detection systems. Two comprehensive publications regarding countermeasures are Deer-Vehicle Crash Countermeasure Toolbox (7) and Animal Vehicle Crash Mitigation Using Advanced Technologies (8). Two types of studies have addressed geometric features of the roadways. The first type analyze the animal-vehicle collisions based on specific roadway features such as two-lane versus four-lane roadways or speed limits (9, 10). One Kansas study looked at 123 roadway segments and 14 roadway characteristics (11). Other studies compared before and after reconstruction on a single section of roadway (12, 13). The previous research suggests that geometric design features, such as roadway curvature and cross-section design, play a role in AVC rates and call for more research (14). Unlike previous studies, this project performs a before and after study of multiple roadway segments to determine the effects of road reconstruction on AVC rates.

PROJECT LOCATIONS The first task in the research effort was to analyze reported AVCs across the state from 1995 to 2003. The Wyoming Department of Transportation (WYDOT), which maintains crash records for all crashes occurring in the state regardless of the roadway’s jurisdiction, provided the animal-vehicle crash records. Using a Geographic Information System (GIS), the crash frequency and crash rates were calculated for each roadway segment and shown graphically on a


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statewide map. Then past Statewide Transportation Improvement Program (STIP) documents were reviewed to identify roads that had been reconstructed between 1996 and 2002 in areas where animal-vehicle crashes were occurring. These roadways do not necessarily represent the highest crash occurrence locations but are roadways where at least some reported AVCs have occurred. This helps ensure that statistical significance can be achieved but is less likely to have the regression to the mean bias often associated with high hazard locations. This generated a list of 36 potential locations that WYDOT later shortened to the 7 final project locations shown in Figure 2.

Figure 2: Project Locations

PROJECT DATA Each of the seven project locations was visited and both quantitative and qualitative data were collected. The qualitative data included general descriptions of terrain, vegetation, fencing, and nearby water sources as well as pictures of the roadway sections. The quantitative data (summarized for each location in Table 1) included bridge and culvert underpass dimensions, speeds, and traffic volumes. In addition to the data from the site visits, archived data was compiled including as-constructed plans of the roadways, historical traffic volumes, animal herd population estimates, and historical speeds if available.

The reconstruction projects focused on widening the lanes and shoulders of the rural, two-lane highways. As shown in Table 1, prior to construction most of the roadways had 11-foot lanes and no shoulders. After construction the lane widths were 12feet with at least 4-foot


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shoulders. The Torrington West project was the only project that increased the number of lanes from two to four.

The reconstruction projects also addressed horizontal and vertical curve deficiencies, increasing the design speed of the roadways. The 2004 edition of the Policy on Geometric Design of Highways and Streets was utilized to determine the difference in design speeds before and after reconstruction (15). During the site visits, 48-hour speed and volume counts were performed on the roadways. Pneumatic tube counters were utilized on either ends of the projects to determine the 85th percentile speed. Ideally, actual speeds prior to reconstruction would be utilized in the analysis, but because these roadways are located in rural areas, there was little speed study data available. Only two of the seven projects had past speed study data. To compensate for the lack of speed data from before reconstruction, the Highway Capacity Manual (HCM) Two-Lane Highway methodology was used to estimate average travel speed based on roadway features, such as lane width, shoulder width, passing opportunities, traffic volumes, and driveways densities (16). Using the roadway features both before and after reconstruction, an HCM reduction factor in miles per hour was estimated. This reduction factor is an estimation of the amount the average travel speed is below the base free flow speed. This analysis used an adjusted speed that subtracted the HCM reduction factor from the roadway’s design speed.

To calculate the crash rates in terms of crashes per million vehicle miles traveled (MVMT), traffic volumes in the form of annual average daily traffic (ADT) values, available from WYDOT,were used. . Crash rates, as opposed to crash frequencies, account for the changes in crashes from increased exposure because of more vehicles using the roadway. Both crash rates and crash frequencies were calculated but the analyses used the crash rates.

TABLE 1: Project Data

Centennial East

Morton Pass

Clearmont North

Hanging Rock Astoria

Round Mountain

Torrington West

Reconstruction Details Beginning Date Nov-96 Mar-01 Nov-99 Jun-98 Mar-00 Apr-99 Oct-97

Ending Date Project Length

May-99 6.1

Sep-02 6.8

Nov-00 7.4

Dec-99 8.2

Nov-01 4.2

Oct-00 7.6

Dec-99 8.3

Animal-Vehicle Crashes Before 4 0 1 2 4 3 11 After 7 2 5 4 16 4 11 Total Crashes Before 12 19 6 12 25 33 67 After 10 7 7 8 33 10 72 Traffic Data (avg. daily traffic) Before 500 630 270 1,630 3,070 550 5,820 After 700 520 530 1,680 3,650 600 6,100 Design Speed (mph) Before 65 40 60 30 55 65 65 After 65 55 65 50 55 65 65 Number of Lanes Before 2 2 2 2 2 2 2 After 2 2 2 2 2 2 4 Lane Width (ft) Before 11 11 11 10 11 11 12 After 12 12 12 12 12 12 12 Shoulder Width (ft)


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Centennial East

Morton Pass

Clearmont North

Hanging Rock Astoria

Round Mountain

Torrington West

Before 0 0 0 0 0 2 2 After 6 4 4 6 8 6 6 Pavement Width (ft) Before 22 22 22 20 22 22 28 After 36 32 32 36 40 36 72 HCM Reduction Factor (mph) Before 4.7 4.7 4.7 4.7 4.7 3 2.6 After 0 1.3 1.3 0 0 0 0 Adjusted Speed (mph) [Design Speed-HCM Reduction] Before 60.3 35.3 55.3 25.3 50.3 62 62.4 After 65 53.7 63.7 50 55 65 65 Measured 85th% Speed (mph) Before --- --- --- 52 --- --- 51 After (Eastern/Northern) 76 72 73 61 61 76 60 After (Western/Southern) 65 74 76 65 62 78 67 Animal Density (animals/sq. mile) Before 11.008 14.669 10.975 7.556 12.163 10.150 2.856 After 17.397 13.043 11.616 7.542 13.162 10.591 4.009 AVC Frequency (crashes/mile/year) Before 0.364 0.000 0.045 0.082 0.330 0.132 0.472 After 1.364 0.097 0.227 0.165 1.320 0.175 0.472 Total Frequency (crashes/mile/year) Before 1.091 0.925 0.272 0.494 2.063 1.447 2.874 After 2.455 0.341 0.317 0.329 2.723 0.439 3.089 AVC Rate (crashes/MVMT) Before 1.949 0.000 0.440 0.139 0.279 0.656 0.286 After 3.440 0.475 1.200 0.268 0.978 0.794 0.307 Total Crash Rate (crashes/MVMT) Before 5.846 5.753 2.641 0.835 1.744 7.221 1.740 After 13.267 1.661 1.681 0.536 2.017 1.985 2.009 Ratio [AVC Rate/Animal Density] Before 0.177 0.000 0.040 0.018 0.023 0.065 0.100 After 0.198 0.036 0.103 0.036 0.074 0.075 0.077

The Wyoming Game and Fish Department, which maintains a database of the populations of all managed game herds within the state, provided wildlife population estimates. The species of concern for this study included mule deer, white-tailed deer, pronghorn antelope, elk, and moose. Each species is broken down into herd units for management purposes and population estimates are made yearly. Each project location was matched to the appropriate herd(s). In some cases herds were merged during the study period or the boundaries of the herd management area were changed. To compensate for these changes and to account for the differing sizes of the herd boundaries, an animal density measure in terms of total animals per square mile was used rather than straight population numbers.

DATA ANALYSIS Three different models were used to determine if the crash rates on the roadway sections showed statistically significant differences before and after reconstruction. The first two models


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aggregated the data for all seven projects while the third model analyzed each section independently.

Aggregate Analysis of Crash Rates The aggregated data from the seven study locations were examined using a paired t-test to determine if there was a statistically significant difference in the change in crash rates for animal-vehicle crashes, non animal-vehicle crashes, and total crashes. The paired t-test matched the before and after data for each roadway section utilizing a change in crash rate as opposed to the actual before and after crash rates. The tested null hypothesis was that the crash rates did not change as a result of the roadway’s reconstruction. Table 2 shows the difference between the after crash rates and the before crash rates for each of the seven projects for animal-vehicle crashes, non-AVCs, and total crashes. The ratio of animal-vehicle crashes to animal densities was also tested. The bottom part of Table 2 summarizes the statistics for this analysis. The animal-vehicle crash rate increased with a 97% confidence level. When the animal populations were accounted for, the increase was still significant with a 96% confidence level. The analysis of all non-animal-vehicle crashes showed that the crash rate decreased with a 95% level of confidence. Lastly, a model that accounted for all reported crashes showed that the trend was decreasing, with an 87% confidence level. Because the AVC and non-AVC crash rate trends work in opposite directions, the total crash rate has a lower confidence level.

TABLE 2: Aggregate Crash Rate Analyses Results

Difference in AVC Rate

Difference in AVC Rate /Animal Density Ratio

Difference in Non-AVC Rate

Difference in Total Crash Rate

Centennial East 1.491 0.041 -2.423 -0.932 Morton Pass 0.475 0.036 -4.567 -4.092 Clearmont North 0.760 0.063 -1.721 -0.961 Hanging Rock 0.193 0.026 0.054 0.247 Astoria 0.699 0.051 -0.426 0.273 Round Mountain 0.138 0.010 -5.374 -5.236 Torrington West 0.021 -0.024 0.248 0.269

Model Statistics Mean of diff. 0.540 0.029 -2.030 -1.490 SSdiff. 1.534 0.005 29.969 30.615 t -stat 2.823 2.682 -2.403 -1.746 Change Increase Increase Decrease Decrease Confidence Level 97% 96% 95% 87%


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Roadway Attribute Analysis This research effort utilizes several different approaches to modeling the change in speed because actual measured before and after reconstruction speeds were not available for all seven projects. The first used the estimated design speed of the roadway before and after reconstruction based on the green book design charts, referred to as the design speed. The second used the same design speeds as the first method but then applied the speed reduction factors from the HCM methodology, called the adjusted speed. The third method used the recorded after speeds and then applied a percent change between the before and after design speeds to estimate the before speed. The last method was similar to the third but used change in speed in mph instead of a percent change. Each of these four speed approaches were tested in the model and the first two speed variables, design speed and adjusted speed, were found to explain more of the variation in the models and were therefore the only ones considered in further analysis.

The next analysis looked at what attributes of the reconstruction efforts may have had a statistically significant effect on crash rates. The first part of this analysis included a single variable regression analysis using animal-vehicle crash rates as the response variable on six different explanatory variables: animal population, design speed, lane width, shoulder width, overall pavement width, and the estimated HCM reduction factor changes. This analysis was performed a second time using the ratio of AVCs to animal density as the response variable. Table 3 shows the results of this analysis. The use of multiple single variable regression models limits the usefulness of the t-values as a quantifiable statistic but the relative values can be used to compare variables qualitatively. This analysis shows that the most important factors are animal density and design speed.

TABLE 3: Roadway Attribute Analysis Results

Crash Rate Crash Rate w/ Animal Density

R2 t-value R2 t-value Animal Density 0.290 2.218 --- --- Design Speed 0.213 1.804 0.430 3.011 Lane Width 0.067 0.929 0.122 1.292 Shoulder Width 0.084 1.051 0.072 0.962 Pavement Width 0.002 0.148 0.027 1.232 Adjusted Speed [Design Speed-HCM Reduction Factor] 0.226 1.871 0.428 2.990

The next task in analyzing the roadway attributes was to build a multiple variable regression model using stepwise regression. This process adds the most significant variable to the model, provided the variable is significant to a user specified level. For this analysis a low alpha value that corresponded to a confidence interval of only 50% was used as the threshold for variables to enter the model. The initial model used an alpha level of 0.5 for both model entry and retention and it was determined that only animal density and design speed were significant enough to be included in


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the model. This modeling process was repeated using a more stringent value of 0.05 for entry and 0.15 for retention and again only the variables of animal density and design speed were significant enough to be included. The resulting linear regression model is as follows:

y = 0.13169(Animal Density) + 0.03902(Design Speed) - 2.72070 The R2 for the model is 0.55 with an adjusted R2 of 0.45. The sign of the coefficients are both positive meaning that increases in animal densities and/or design speeds yield increases in AVC rates. The modeling process was repeated using the ratio of animal-vehicle crash rates to animal density as the response variable. The same stepwise regression process was repeated, first with the less stringent 0.5 entry and retention threshold and again with the 0.05 entry and 0.15 retention parameters. Design speed was the only variable in both cases that was included in the model. The resulting equation from this second process is as follows:

y = 0.00346(Design Speed) - 0.12478

The resulting R2 for this model is 0.43 and because there is only one variable the adjusted R2 is also 0.43. The positive coefficient indicates that increases in design speed lead to increases in AVC rates. The purpose of both of the above models is to test the statistical significance of the roadway attributes, not in creating predictive models. Because of this, the overall R2 values are less important than the inclusion of variables in the model.

Individual Section Analysis The last analysis approach looked at each of the seven reconstruction projects individually. The method chosen was based on the assumption that the crash counts are Poisson distributed and the test statistic accounts for the crash counts both before and after and their associated MVMT. In the formula below, n is the crash count and period 1 is before reconstruction and period 2 is after reconstruction.

Test Statistic = ( )

( )21

21

21

2

2

1

1

11MVMTMVMTnn

MVMTMVMT

MVMTn

MVMTn

++

⎟⎠⎞⎜

⎝⎛ +

−

The test statistic in the equation is assumed to be normally distributed and the value of the statistic can be used to find the probability value (p-value), which is the probability of getting the observed differences given that there was no real effect associated with the roadway reconstruction. For each section an analysis was run on the AVC rate, the non-AVC rate, and the total crash rate. Table 4 summarizes the results from this analysis and includes the p-value and the associated trend. The statistically significant trends, using a confidence level of 90%, are shown in bold. As Table 4 shows, only the Astoria section has a statistically significant trend for the AVC rate, although all the projects show an increasing trend. The non-AVC rates on the individual sections show both increasing and decreasing trends, but the three statistically


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significant trends are all decreasing. The total crash rates on the sections once again show both increasing and decreasing trends, but the two statistically significant trends are both decreasing.

TABLE 4: Individual Segment Analyses Results

AVC Rates Non-AVC Rates Total Crash Rate p-value Trend p-value Trend p-value Trend

Centennial East 0.358 Increase 0.135 Decrease 0.685 Decrease

Morton Pass 0.211 Increase 0.001 Decrease 0.004 Decrease

Clearmont North 0.340 Increase 0.045 Decrease 0.412 Decrease

Hanging Rock 0.346 Increase 0.812 Increase 0.419 Increase

Astoria 0.017 Increase 0.290 Decrease 0.583 Increase

Round Mountain 0.803 Increase 0.000 Decrease 0.000 Decrease

Torrington West 0.866 Increase 0.573 Increase 0.560 Increase

Statistically significant results shown in bold (90% Confidence).

CONCLUSIONS The roadway attribute analysis was performed to gauge the effect of roadway design variables including animal density, design speed, design speed with HCM speed factors, lane width, shoulder width, and pavement width. Only animal density and design speed were found to be statistically significant. This type of analysis of roadway segments is limited by the lack in variation in the data. Most of the rural roadways in the state that have not been reconstructed have narrow lanes and no shoulders. After these roads are reconstructed, they usually have 12-foot lanes and 4- to 6-foot shoulders. To adequately determine the effects of lane and shoulder widths on AVCs, projects with a variety of lane and shoulder widths should be investigated to isolate these factors.

The individual analysis of the seven roadway sections showed general trends toward increasing AVC rates, decreasing non-AVC rates, and decreasing total crashes, but only a handful of the sections showed these trends at a statistically significant level. The strength of this research effort over previous research is in the aggregation of multiple roadway segments in a before and after approach. The aggregated research results show an observed increase in AVC rates after roadway reconstruction but a decrease in non-AVC rates and overall crash rates. Roadway agencies are responsible for the overall level of safety of roadway segments so these results do not suggest that roadway reconstruction projects are not beneficial. A more reasonable response to the likelihood of increased AVCs is to investigate specific AVC countermeasures that could be applied on a site-specific basis and incorporate those countermeasures into reconstruction


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projects to mitigate these potential increases. A Michigan study of Interstate 75 found an increase in AVCs when that roadway was rebuilt and found that the AVC numbers returned to baseline values after five years (12). It is likely that AVCs increase when animals are presented with a new situation, such as increased crossing distances and speeds, but over time the animals adapt to the new conditions. A proposed follow up study to this project will look at these same roadway segments after more time has elapsed to determine what long-term effects roadway reconstruction has on animal-vehicle collisions.

More details about the work described in this paper can be found in the full research report “Relating Wildlife Crashes to Road Reconstruction” (17).

AKNOWLEDGEMENTS The Wyoming Department of Transportation and the Mountain-Plains Consortium funded the research work described in this paper. The authors would like to thank these two groups for the opportunity to work on this project, as well as the following individuals for their assistance and support: Matt Carlson, Jim Kladianos and Thomas Hart from WYDOT; Rebecca Schilowsky from Wyoming Game and Fish for her help with animal populations; and Richard Anderson-Sprecher from the University of Wyoming for his help with the statistical analysis.

REFERENCES 1. Insurance Institute for Highway Safety. Many Deaths in Vehicle-Animal Collisions are

Avoidable. Insurance Institute for Highway Safety. November 2004. http://www.iihs.org/news/2004/iihs_news_111804.pfd. Accessed September 2006.

2. Wyoming Department of Transportation. Vehicle Miles 2004. Cheyenne, WY, 2005. 3. Perrin, J., and R. Disegni. Animal-Vehicle Accident Analysis. Publication UT-03.31. Utah

Department of Transportation, 2003. 4. Bellis, E.D., and H.B. Graves. Collisions of Vehicles with Deer Studied in Pennsylvania

Interstate Road Section. Highway Research News, Vol. 43, 1971, pp. 13-17. 5. Olson, Rich. Mule Deer Requirements and Management in Wyoming. University of

Wyoming Cooperative Extension Service. Laramie, WY. 1992. 6. Rea, R., and R. Rea. Of Moose and Mud. Public Roads Vol. 69, no. 2, 2005. 7. Knapp, K. Deer-Vehicle Crash Countermeasure Toolbox: A Decision and Choice Resource.

Department of Civil and Environmental Engineering, University of Wisconsin, Madison. 2004. http://deercrash.com/toolbox/finalreport.pdf. Accessed June 2006.

8. Huijser, M., P.T. McGowen, W. Camel, A. Hardy, P. Wright, and A.P. Clevenger. Animal Vehicle Crash Mitigation Using Advanced Technology Phase I: Review, Design and Implementation. Western Transportation Institute - Montana State University. Bozeman, MT, 2006.

9. Allen, R.E. and D.R. McCullough. Deer-Car Accidents in Southern Michigan. Journal of Wildlife Managment. Vol. 40, Issue 2, 1976, pp. 317-325.

10. Gunther, K.A., M.J. Biel, and H.L. Robinson. Factors Influencing the Frequency of Road-Killed Wildlife in Yellowstone National Park. Proceeding of the International Conference on Wildlife Ecology and Transportation. 1998, pp. 395-405.

11. Meyer, E., and I. Ahmed. Modeling of Deer-Vehicle Crash Likelihood Using Roadway and Roadside Characteristics. Proceedings of the Transportation Research Board Annual Meeting. 2004.


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12. Reilley, R.E., and H.E. Green. Deer Mortality on a Michigan Interstate Highway. Journal of Wildlife Management Vol. 38, 1974 pp. 16-19.

13. Woods, J G. Effectiveness of Fences ad Underpasses on the Trans-Canada Highway and Their Impact on Ungulate Populations Project. Canadian Parks Service, National History Division, 1990.

14. Knapp, K.K. Roadway Design Decisions and Animal-Vehcile Crashes. 3rd International Symposium on Highway Geometric Design, 2005.

15. Officials, American Association of State Highway and Transportation. A Policy on Geometric Design of Highways and Streets, 5th Edition. 2004.

16. Transportation Research Board. Highway Capacity Manual. National Research Council, Washington, D.C., 2000.

17. Young, R.K., and C. Vokurka. Relating Wildlife Crashes to Road Reconstruction. Publication FHWA-WY-07/02F. Wyoming Department of Transportation, Cheyenne, WY, 2007.


Documents

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