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Deer-Vehicle Collisions in Southeastern Michigan: Environmental and Human Dimensions

This study examines the environmental and human factors contributing to deer-vehicle collisions in southeastern Michigan. It identifies key factors affecting collision frequency and develops predictive models. Management recommendations are provided to mitigate collisions.

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Deer-Vehicle Collisions in Southeastern Michigan: Environmental and Human Dimensions

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  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 80,000 Annually • 64-68K DVCs (reported) • 1,500+ injuries • 10+ fatalities 70,000 60,000 50,000 Number of DVCs 40,000 30,000 20,000 10,000 0 1960 1970 1980 1990 2000 2010 Year

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

  11. MONROE MONROE

  12. WASHTENAW WASHTENAW

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

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

  18. Driver Characteristics Gender 70 Male Female 60 50 40 Percentage 30 20 10 0 DVCs Non-DVCs Licensed drivers

  19. Driver Characteristics Age & Gender Average DVC driver age = 39.9 years 6 Male 4 Female DVCs as a % of all accidents 2 0 <20 35-39 55-59 65-69 75-79 25-29 45-49 Driver age (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 Male Female 600 500 400 Number of Respondents 300 200 100 0 Monroe Oakland Washtenaw

  22. 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 Respondent Demographics

  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 30 25 20 Percentage 15 10 5 0 Urban Suburban Rural Area where respondent lived

  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 (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/

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