1. Environmental and human dimensions of deer-vehicle collisions in southeastern Michigan. Shawn J. Riley Alix Marcoux Krishnan Sudharsan Brent Rudolph

2. Acknowledgements Michigan Department of Transportation The Institute for Public Policy and Social Research Michigan Deer Crash Coalition AAA Michigan

3. DVCs in Michigan Annually 64-68K DVCs (reported) 1,500+ injuries 10+ fatalities 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 196019701980199020002010 Year Number of DVCs

4. Conceptual Model DEER + LANDSCAPE DRIVER

5. Environmental Dimension

6. Objectives Identify and assess environmental factors affecting the frequency and rate of DVCs in southern Michigan Develop predictive models that explain why DVCs occur on the landscape Provide management recommendations on how environmental factors may be managed to alleviate DVCs based on knowledge gained in objectives 1 and 2

7. Study Area Detroit

8. MONROE OAKLAND WASHTENAW DVCs in the study area Y2000-2003 6.4% of total crashes 10% of total crashes 3.5% of total crashes

9. Methods 1999-2001 DVC locations (SEMCOG) 450 random DVC points selected from each county (150 each from 1999 to 2001) 800 meter radius buffers built (502 acres) 450 random non-DVC points at least 800 meters away from DVC points placed on roads 800 meter radius buffers built Buffers clipped from 2001 land cover classification

10. Model Results MODELLOG LIKELIHOOD AIC c ∆i∆i wiwi K HSI + TV + S + (TV * S) -112 2650111 HSI + TV + S -276 57931409 HSI + TV -364 74548007 HSI + S -460 94267708 TV + S -789 1592132706

11. MONROE

12. WASHTENAW

13. OAKLAND

14. Human dimensions: driver characteristics, knowledge, and attitudes related to DVCs

15. UD-10 Crash Report Data 186,930 collisions reported 9,790 (5.2%) involved deer Rate: 1.8 – 5.3 DVCs/1,000 drivers

16. Time of Day Collisions per 100,000 drivers Non-DVCs 0 10 20 30 40 50 60 70 80 0:00 4:00 8:00 12:00 16:00 20:00 24:00 Time of day DVCs 0 200 400 600 800 1000 1200 1400 Accident Timing Characteristics

17. Month of Year: DVCs vs Non-DVCs per 100K drivers Collisions per 100,000 drivers 0 20 40 60 80 100 120 140 160 180 May June July Aug Sept Oct Nov Dec Jan Feb March April 0 1000 2000 3000 4000 DVCs Non-DVCs

18. Gender Driver Characteristics 0 10 20 30 40 50 60 70 DVCsNon-DVCsLicensed drivers Percentage Male Female

19. Age & Gender 0 2 4 6 <20 25-29 35-39 45-49 55-5965-6975-79 Driver age (Years) DVCs as a % of all accidents Male Female Driver Characteristics Average DVC driver age = 39.9 years

20. Survey Research Deer-Vehicle Collision in Michigan: A Survey of Your Views

21. Survey Response Rate 3,681 surveys sent 266 Ineligible surveys 1,653 Responses 48.4% Response 0 100 200 300 400 500 600 MonroeOaklandWashtenaw Number of Respondents Male Female

22. Respondent Demographics Gender 46.2% Male 52.7% Female 1.1% No Response Age average 47.9 years Years in County average 23 years Level of Education 22.1% High School or less 36.3% Some College 21.9% 4-year college degree 19.7% graduate/professional degree

23. DVC Involvement 284 (12%) respondents were a driver in a DVC 196 of the DVCs occurred within the last 5 years 64% of drivers were male 18% of drivers involved in at least one DVC within the past 5 years have had more than one 102 respondents involved as passenger Only 1 injury was reported

24. Percentage of respondents who reported past involvement in a DVC 0 5 10 15 20 25 30 UrbanSuburbanRural Area where respondent lived Percentage

25. DVC Non-reporting Rates 53.7 % did not report their DVC to the police 71.5% thought it wasn’t necessary 15.4% experienced no damage to deer and/or car 47.9 % did not report their DVC to their insurance co. 37.3% thought it wasn’t necessary 27.3% experienced little or no damage 13.6% thought it would affect insurance rates 10.0% thought they did not have the correct coverage

26. Deer and Drivers (cont.) 77.9% think DVCs are a serious problem in Michigan ( Drivers involved in DVCs (85.5%) were more likely to perceive DVCs as a serious problem than those who had no prior involvement ) 78.6% of respondents involved in a DVC believed it could not have been prevented

27. Concerns that respondents had about DVCs Losing control of car while swerving to avoid a deer Injuring others Cost of car and property damage Being injured Insurance rate increase Injuring or killing deer Cost of repairing other property damage Medical bills

28. Behavioral Intentions A majority of respondents expressed a willingness to slow down by 10mph if it would significantly reduce their chances of DVC involvement Drivers who had been in a DVC were more likely to slow down in response to a deer crossing sign

29. Calculating Mean Knowledge Scores Answered a series of 5 questions Score between 0 – 10 0 having no knowledge and 10 being most knowledgeable 20-30% were unsure about: Peak DVC times Peak DVC season Type of road DVCs occur on

30. Mean Knowledge Scores of Respondents Respondents previously involved in DVCs had higher mean scores Men had higher scores than women People from rural areas had higher scores

31. Driver Attitudes of Current Deer Population Levels 48.0% want deer population kept the same 22.7% want deer population reduced 21.4% are unsure 8.0% want deer population increased Drivers involved in DVCs were more likely to want reduced deer populations than those who had no DVC

32. Drivers’ Preferred Education Channels Channel% Yes Newspaper47 Brochures Billboards 27 26 Drivers Ed21 Magazines14 Television4 Internet3 (Respondents could choose more than 1 option)

33. Dispelling myths DVCs are not random There ARE actions that can be taken to reduce DVCs “Place” matters!

34. Management Implications Underreporting rate means that there in southern Michigan DVCs may be as great as 2X current estimate. Need to educate about specific risk factors –E.g., Season, road types, deer activity patterns, rural - urban risks Need to communicate that DVCs can be avoided. They are not “unavoidable.” Need to report? Drivers don’t know why...

35. Research Needs Calculations of individual driver risks under different situations. We assessed the risk of DVCs, but not the individual risk to individual drivers. Assessment of fine scale factors, such as sight distances, topography, vegetation management, etc.

36. Research Needs Education is always suggested, but... Seldom a specific message, seldom a specific approach … and, Seldom evaluated … Specific information and education campaigns to reach “highest risk” populations, e.g., rural male commuters. Sources and channels to affect driver behavior?

37. - Thank you - For more information: www.fw.msu.edu/people/riley/