Driving/Data
Baseline rates (verbatim; used directly in models)
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
Time of Day (modifier)
| 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 (modifier)
| 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 (share of miles while impaired)
| 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 visual–manual distraction (share of miles while actively interacting)
| 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 (Modifier)
| 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.
RiskModel: Driving/Data: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/Data: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/Data: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.
Initially generated by GPT-5 Thinking