Driving
Driving in the United States Risk Calculator
The average adult in the US drives about 14,000 miles per year. But driving carries real risks of fatality and serious injury.
This calculator estimates expected risk over a year, assuming 14,000 miles of driving, under different scenarios: time of day, seat-belt use, alcohol impairment, distraction, and speeding. It is based on national crash data.
Your Inputs
Choose your driving conditions below:
distance_miles=14000
Driving at night increases risk because more crashes happen in fewer miles:
Wearing a seat belt greatly reduces the risk of death or serious injury:
Higher speeds increase both crash likelihood and severity:
How often does the driver drive after drinking too much (frequency of impaired driving):
How often does the driver interact with a phone (dialing/texting/etc.) while driving:
Your Results
Note: "Injuries" reflect police-reported injuries.Baseline Rates
The following U.S. national rates are taken verbatim from authoritative sources and are **not** converted here. Conversions to per-miles exposure are performed only inside the RiskModel calculations below.
- Fatalities: **1.26 deaths per 100 million vehicle miles traveled (VMT)** in 2023 (national average, state/roadtype/year differences can be large).
* NHTSA 2023 Traffic Fatalities Estimates * IIHS: Fatality statistics
- Injuries: **75 injuries per 100 million VMT** in 2022 (police-reported injuries, national average, state/roadtype/year differences can be large).
* NHTSA: Traffic Safety Facts 2022
Risk Factors
Time of Day
| time_period | time_fatality_multiplier | time_injury_multiplier |
|---|---|---|
|
Day |
1.0 |
1.0 |
|
Night |
3.56 |
1.47 |
Based on NHTSA 2022 "Traffic Safety Facts Annual Report Tables," combining "Dark (not lighted)" and "Dark (lighted)" conditions (18,254 of 33,870 fatalities; 824,000 of 2.47 million injuries = 53.9% and 32.9%).
Using the statistic that 25% of VMT occurs at night (FHWA Highway Statistics Table VM-202), relative per-mile risk is ≈3.56× for fatalities and 1.47× for injuries compared with daytime.
- Night/day crash distribution and injuries: NHTSA 2022
- Background on time-of-day involvement: NHTSA
- Exposure assumption (≈25% of VMT at night): FHWA Lighting Guidance
- Supplemental analysis: University of Michigan per-mile risk
Seat-belt Usage
| belt_status | belt_fatality_multiplier | belt_injury_multiplier |
|---|---|---|
|
Worn (car) |
1.0 |
1.0 |
|
Not worn (car) |
1.82 |
2.0 |
|
Worn (SUV/van/truck) |
1.0 |
1.0 |
|
Not worn (SUV/van/truck) |
2.5 |
2.857 |
Seat belts reduce fatal injury risk by ~45% in cars and ~60% in light trucks; moderate-to-critical injury by ~50% in cars and ~65% in light trucks. The multipliers above are the inverse of those reductions (i.e., increased risk when not wearing a belt).
- Effectiveness summary: IIHS: Seat belts
- Technical background: NHTSA: Seat belt effectiveness
Alcohol-impaired Driving Frequency
| alcohol_frequency_label | alcohol_frequency_share |
|---|---|
|
Never |
0 |
|
A few times per year |
0.001 |
|
About once a month |
0.005 |
|
About once a week |
0.02 |
|
Several times a week |
0.05 |
These shares approximate the fraction of total miles driven while impaired (not the fraction of people). They translate intuitive frequencies ("a few times per year", "once a month", etc.) into small exposure shares so the multiplier applies only to that portion of miles.
Calibration notes (assumptions; adjust as needed):
- "A few times per year" ≈ 0.1% of miles (e.g., ~10–20 impaired miles in ~10,000 annual miles).
- "About once a month" ≈ 0.5% of miles.
- "About once a week" ≈ 2% of miles.
- "Several times a week" ≈ 5% of miles.
Note that intoxication risk is based on a blood alcohol level (BAC) of 0.08. Risk increases exponentially with increasing BAC.
Background/prevalence:
- CDC summary: self-reported alcohol-impaired driving episodes occur at a non-zero rate in the population.
Phone-based Distraction Frequency
| distraction_frequency_label | distraction_frequency_share |
|---|---|
|
None |
0 |
|
One interaction per trip |
0.005 |
|
Several interactions per trip |
0.02 |
|
Lots of interactions per trip |
0.05 |
These options reflect self-reported patterns of phone use while driving, translated into approximate shares of total miles driven while actively interacting with the phone (visual–manual tasks). The RiskModels apply a higher crash risk **only** to that fraction of miles, using a multiplier of ~6.0× for active distraction (consistent with naturalistic driving studies).
Evidence background:
- Visual–manual phone use (dialing, texting) is strongly associated with crash risk, with multipliers between ~6× and 12× depending on task.
- Talking (handheld or hands-free) is not consistently linked to higher crash risk, so it is not modeled here.
Speeding
| speeding_status | speeding_multiplier |
|---|---|
|
At or below limit |
1.0 |
|
Above limit |
2.0 |
Speeding increases crash severity and overall risk—doubling speed quadruples kinetic energy, and speeding was involved in ~29% of U.S. traffic fatalities. Using a simplified 2× severity multiplier as a proxy.
Risk Models
RiskModel: Driving:fatality_model
Content:
Your estimated chance of being in a fatal crash is {{One_In_X|{{#expr: 1 - (2.718281828 ^ ( - ( (1.26 / 100000000) * {distance_miles} * {time_fatality_multiplier} * {belt_fatality_multiplier} * ( (1 - {alcohol_frequency_share}) + ({alcohol_frequency_share} * 4.0) ) * ( (1 - {distraction_frequency_share}) + ({distraction_frequency_share} * 6.0) ) * {speeding_multiplier} ) ))}} }} per year.
RiskModel: Driving:injury_model
Content:
Your estimated chance of being injured in a crash is {{One_In_X|{{#expr:1 - (2.718281828 ^ ( - ( (75 / 100000000) * {distance_miles} * {time_injury_multiplier} * {belt_injury_multiplier} * ( (1 - {alcohol_frequency_share}) + ({alcohol_frequency_share} * 4.0) ) * ( (1 - {distraction_frequency_share}) + ({distraction_frequency_share} * 6.0) ) * {speeding_multiplier} ) ))}} }} per year.
RiskModel: Driving:any_crash_model
Content:
Your estimated chance of being in a police-reported crash is {{One_In_X|{{#expr:1 - (2.718281828 ^ ( - ( (185.54886112876233 / 100000000) * {distance_miles} * {time_injury_multiplier} * ( (1 - {alcohol_frequency_share}) + ({alcohol_frequency_share} * 4.0) ) * ( (1 - {distraction_frequency_share}) + ({distraction_frequency_share} * 6.0) ) * {speeding_multiplier} ) ))}} }} per year.
Calculation note: Each model computes an expected count λ from the verbatim base rates (per 100 million vehicle miles traveled), scaled by distance and modifiers, then converts to a probability \(p = 1 - e^{-λ}\) using \(2.718281828^{-\lambda}\). Alcohol and phone-based visual–manual distraction are applied via exposure shares: the model blends \((1 - \text{share})\times 1 + \text{share}\times 4.0\) for alcohol and \((1 - \text{share})\times 1 + \text{share}\times 6.0\) for distraction so elevated risk applies only to those fractions of miles.
Note on uncertainty: These are national averages and approximate modifiers. Actual risks vary by state, roadway type (urban/rural), weather, vehicle, driver demographics, and year-to-year changes. Modifiers are population-level and not individual predictions.
Generated by ChatGPT-5