Deer–Vehicle Collisions/Data
Data and Parameters
| RegionLabel | DVC_State_Odds_Label | DVC_State_Odds_Denominator | DVC_State_Odds_DataPeriod |
|---|---|---|---|
|
Alabama |
1 in 93 |
93 |
Jul 2022–Jun 2023 |
|
Alaska |
1 in 522 |
522 |
Jul 2022–Jun 2023 |
|
Arizona |
1 in 508 |
508 |
Jul 2022–Jun 2023 |
|
Arkansas |
1 in 88 |
88 |
Jul 2022–Jun 2023 |
|
California |
1 in 388 |
388 |
Jul 2022–Jun 2023 |
|
Colorado |
1 in 240 |
240 |
Jul 2022–Jun 2023 |
|
Connecticut |
1 in 267 |
267 |
Jul 2022–Jun 2023 |
|
Delaware |
1 in 148 |
148 |
Jul 2022–Jun 2023 |
|
Florida |
1 in 487 |
487 |
Jul 2022–Jun 2023 |
|
Georgia |
1 in 108 |
108 |
Jul 2022–Jun 2023 |
|
Hawaii |
1 in 710 |
710 |
Jul 2022–Jun 2023 |
|
Idaho |
1 in 136 |
136 |
Jul 2022–Jun 2023 |
|
Illinois |
1 in 152 |
152 |
Jul 2022–Jun 2023 |
|
Indiana |
1 in 100 |
100 |
Jul 2022–Jun 2023 |
|
Iowa |
1 in 63 |
63 |
Jul 2022–Jun 2023 |
|
Kansas |
1 in 96 |
96 |
Jul 2022–Jun 2023 |
|
Kentucky |
1 in 91 |
91 |
Jul 2022–Jun 2023 |
|
Louisiana |
1 in 193 |
193 |
Jul 2022–Jun 2023 |
|
Maine |
1 in 83 |
83 |
Jul 2022–Jun 2023 |
|
Maryland |
1 in 116 |
116 |
Jul 2022–Jun 2023 |
|
Massachusetts |
1 in 109 |
109 |
Jul 2022–Jun 2023 |
|
Michigan |
1 in 60 |
60 |
Jul 2022–Jun 2023 |
|
Minnesota |
1 in 81 |
81 |
Jul 2022–Jun 2023 |
|
Mississippi |
1 in 64 |
64 |
Jul 2022–Jun 2023 |
|
Missouri |
1 in 80 |
80 |
Jul 2022–Jun 2023 |
|
Montana |
1 in 53 |
53 |
Jul 2022–Jun 2023 |
|
Nebraska |
1 in 127 |
127 |
Jul 2022–Jun 2023 |
|
Nevada |
1 in 770 |
770 |
Jul 2022–Jun 2023 |
|
New Hampshire |
1 in 169 |
169 |
Jul 2022–Jun 2023 |
|
New Jersey |
1 in 213 |
213 |
Jul 2022–Jun 2023 |
|
New Mexico |
1 in 262 |
262 |
Jul 2022–Jun 2023 |
|
New York |
1 in 144 |
144 |
Jul 2022–Jun 2023 |
|
North Carolina |
1 in 87 |
87 |
Jul 2022–Jun 2023 |
|
North Dakota |
1 in 82 |
82 |
Jul 2022–Jun 2023 |
|
Ohio |
1 in 97 |
97 |
Jul 2022–Jun 2023 |
|
Oklahoma |
1 in 119 |
119 |
Jul 2022–Jun 2023 |
|
Oregon |
1 in 197 |
197 |
Jul 2022–Jun 2023 |
|
Pennsylvania |
1 in 59 |
59 |
Jul 2022–Jun 2023 |
|
Rhode Island |
1 in 96 |
96 |
Jul 2022–Jun 2023 |
|
South Carolina |
1 in 83 |
83 |
Jul 2022–Jun 2023 |
|
South Dakota |
1 in 69 |
69 |
Jul 2022–Jun 2023 |
|
Tennessee |
1 in 107 |
107 |
Jul 2022–Jun 2023 |
|
Texas |
1 in 191 |
191 |
Jul 2022–Jun 2023 |
|
Utah |
1 in 205 |
205 |
Jul 2022–Jun 2023 |
|
Vermont |
1 in 110 |
110 |
Jul 2022–Jun 2023 |
|
Virginia |
1 in 78 |
78 |
Jul 2022–Jun 2023 |
|
Washington |
1 in 286 |
286 |
Jul 2022–Jun 2023 |
|
West Virginia |
1 in 38 |
38 |
Jul 2022–Jun 2023 |
|
Wisconsin |
1 in 60 |
60 |
Jul 2022–Jun 2023 |
|
Wyoming |
1 in 83 |
83 |
Jul 2022–Jun 2023 |
Annual per-driver odds of an animal-involved collision claim (deer are the top animal). DVC_State_Odds_Denominator is numeric for formulas.
| SeasonMonthLabel | DVC_WI_Monthly_Count_2023 | DVC_WI_Monthly_Context |
|---|---|---|
|
January |
1033 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
February |
881 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
March |
904 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
April |
857 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
May |
1575 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
June |
1543 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
July |
828 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
August |
738 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
September |
925 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
October |
2343 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
November |
3218 |
Wisconsin police-reported deer crashes (calendar year 2023) |
|
December |
1308 |
Wisconsin police-reported deer crashes (calendar year 2023) |
Monthly distribution (total = 16153). Used to weight annual odds into a month-specific probability.
| TimeOfDayOptionLabel | TimeOfDay_Relative_Multiplier | TimeOfDay_Notes |
|---|---|---|
|
Daylight (baseline) |
1 |
Baseline risk level |
|
Night (sunset→sunrise) |
3 |
Most DVCs occur after dark; conservative whole-night factor |
|
Peak window (~2 hours after sunset) |
14 |
≈14× vs. two hours before sunset (short peak window) |
Relative multipliers for time of day.
| RoadContextLabel | DVC_Rate_per100M_VehicleMiles | DVC_Rate_Context |
|---|---|---|
|
Overall (Kentucky baseline) |
7 |
Police-reported DVCs per 100M VMT (1987–1989) |
|
Rural roads |
11 |
Police-reported DVCs per 100M VMT (1987–1989) |
|
Urban roads |
2 |
Police-reported DVCs per 100M VMT (1987–1989) |
Per-mile baseline rates by road context (illustrative seed rates).
| TripLengthLabel | Trip_Miles |
|---|---|
|
Short errand (5 mi) |
5 |
|
Commute (10 mi) |
10 |
|
Suburban cross-town (20 mi) |
20 |
|
Highway leg (50 mi) |
50 |
|
Road trip segment (100 mi) |
100 |
Trip distance options used to scale the per-mile probability.
| MitigationLabel | DVC_Reduction_Percent | DVC_Mitigation_Context |
|---|---|---|
|
None / no special mitigation |
0 |
Reference |
|
Wildlife fencing + crossing structures |
80 |
Synthesis; ungulates incl. deer |
|
Wildlife fencing (typical median) |
54 |
Global meta-analysis median |
|
All mitigation types (overall average) |
40 |
Global meta-analysis average |
Observed reductions from corridor mitigations; apply as a percent reduction to expected collisions.
Risk Models
RiskModel: Deer–Vehicle Collisions/Data:DVC_Annual_Per_Driver
Content:
Your '''deer–vehicle collision''' risk is {{One_In_X|{{#expr: 1 / {DVC_State_Odds_Denominator} }} }} per '''year'''.
''What this shows'': Per-driver annual odds for the selected state/region.
RiskModel: Deer–Vehicle Collisions/Data:DVC_Monthly_Per_Driver
Content:
Your '''deer–vehicle collision''' risk is {{One_In_X|{{#expr:
(1 / {DVC_State_Odds_Denominator}) * ({DVC_WI_Monthly_Count_2023} / 16153)
}} }} per '''month'''.
''How computed'': Annual probability scaled by the selected month’s share of annual deer crashes (Wisconsin-2023 proxy).
RiskModel: Deer–Vehicle Collisions/Data:DVC_TripLevel_Per_Drive
Content:
Your '''deer–vehicle collision''' risk is {{One_In_X|{{#expr:
({DVC_Rate_per100M_VehicleMiles} / 100000000)
* {Trip_Miles}
* (({DVC_WI_Monthly_Count_2023} * 12) / 16153)
* {TimeOfDay_Relative_Multiplier}
* (1 - ({DVC_Reduction_Percent} / 100))
}} }} per '''drive'''.
''Explanation'':
# Per-mile baseline from selected road context: ''{DVC_Rate_per100M_VehicleMiles} ÷ 100,000,000''.
# Scale by trip length (''× {Trip_Miles}'').
# Seasonal factor: month’s share relative to an average month (''× ({DVC_WI_Monthly_Count_2023} × 12 ÷ 16153)'').
# Time-of-day multiplier (''× {TimeOfDay_Relative_Multiplier}'').
# Mitigation reduction (''× (1 − {DVC_Reduction_Percent}/100)'').
''Caveat'': Baseline rates are historic and illustrative; local calibration improves accuracy.
Data and risk models are used on the main page.
Initially created by GPT-5 Thinking