NHTSA’s FARS database tracks five data categories that directly affect bicycle accident case outcomes. Crash location, vehicle type, time of day, alcohol involvement, and rider demographics each point to a specific liability argument or settlement position. Firms that pull this data before building case strategy consistently outperform those that treat every cycling collision the same way.
In 2024, 1,103 pedalcyclists were killed in U.S. traffic crashes and an estimated 52,887 were injured, according to NHTSA’s FARS and CRSS databases. Deaths fell 6% from the record 1,173 in 2023, but injuries rose 6% to a ten-year high. The fatality dip does not signal a safer landscape when the injury count is climbing in the opposite direction.
How Crash Location Data Strengthens Liability Arguments
NHTSA’s 2024 data shows that 81% of pedalcyclist fatalities occurred in urban areas, up from 69% in 2011. Sixty percent happened at non-intersection locations. Only 30% occurred at intersections.
These numbers reshape how liability gets argued. A cyclist killed mid-block on an urban arterial presents a different negligence case than one killed at a signalized intersection. Mid-block fatalities often involve inadequate bike lane protection, drivers overtaking with insufficient clearance, or missing road infrastructure. The liability question shifts from signal compliance to road design and municipal obligations.
“When we pull FARS location data for a specific county, the case theory often changes before we write the first demand letter,” says Robert Goldwater, bicycle accident attorney at Bicycle Accident Lawyers Group, a firm that publishes annual bicycle accident statistics in the U.S. segmented by state and crash type. “A non-intersection fatality on an unprotected urban arterial opens a municipal liability argument that a standard driver-negligence framing would miss entirely.”
The location breakdown gives practitioners three distinct liability paths from a single crash.
- Driver negligence when the road had adequate infrastructure and the driver failed to yield, passed too closely, or was distracted
- Municipal liability when the crash location lacked protected bike lanes, adequate lighting, or safe design despite documented traffic volume
- Shared liability when both infrastructure failure and driver conduct contributed, affecting comparative fault allocation
Which Vehicles Cause the Most Cyclist Fatalities and Why It Matters in Court
NHTSA data shows that collisions with light trucks (SUVs, pickups, and vans) caused 46% of bicyclist fatalities. This is the highest share of any vehicle category and reflects the U.S. fleet’s shift toward larger vehicles with higher front-end profiles.
The higher impact point on light trucks increases the probability of thoracic and head injuries rather than lower-extremity fractures. That pattern changes the damages calculation across every line item.
- Medical expenses increase due to ICU stays, surgery, and neurological rehabilitation
- Lost wages and earning capacity extend further because brain injuries and thoracic damage carry longer recovery windows and higher disability rates
- Pain and suffering valuations rise because injury severity documented in medical records supports larger non-economic awards
- Wrongful death claims carry enhanced injury arguments when the vehicle class involved is statistically the most lethal to cyclists
Practitioners can reference FARS vehicle classification as liability evidence to establish the causal link between vehicle design and outcome severity. In wrongful death cases, this data also supports design defect arguments tied to front-end height and cyclist impact geometry.
How Time-of-Day Patterns Affect Negligence and Comparative Fault
Roughly half of pedalcyclist fatalities occur between 6 p.m. and midnight, with peak concentration between 8 p.m. and midnight. This pattern holds across multiple data years and is not seasonal.
The time-of-day distribution affects litigation in two ways. First, it shapes comparative fault arguments. A cyclist riding without legally required lighting at 9 p.m. faces a fault allocation challenge that a midday crash does not. Defense teams will use this data to argue shared liability. Plaintiff counsel needs to build the rebuttal early.
Key evidence questions for nighttime cases include the following.
- Was the road segment adequately lit according to municipal standards
- Did the driver have functioning headlights at the time of the crash
- Was the cyclist in a marked bike lane regardless of personal lighting
- Does surveillance footage or dashcam footage capture visibility conditions at the crash site
- Did the driver’s speed leave adequate stopping distance for available sight lines
Second, nighttime crashes correlate with alcohol involvement. FARS data shows alcohol was a factor in 33% of fatal cyclist crashes in 2024. Among cyclists killed, 21% had a BAC of .01 g/dL or higher. On the driver side, impaired driving at night strengthens gross negligence and punitive damages arguments. On the cyclist side, any BAC reading becomes a comparative fault weapon in settlement negotiations.
How Cyclist Age and Demographics Shape Settlement Valuations
The average age of pedalcyclists killed in 2024 was 48. Riders aged 60 to 64 died at a higher rate than any other group. Males accounted for 87% of fatalities.
These demographics directly affect claim valuation. A 48-year-old killed in a wrongful death case presents different economic loss calculations than a 25-year-old. Work-life expectancy, earning capacity, pension losses, and household service value all shift with age. Settlement data benchmarked against age-specific case outcomes produces more precise demand figures than generic multiplier approaches.
The 60-to-64 age group’s disproportionate fatality rate also raises questions about road design. Infrastructure built around younger cyclists’ reaction times may not account for the actual population on the road, opening an additional municipal negligence angle.
How to Apply FARS Data at Each Stage of a Bicycle Injury Case
Evidence-based lawyering with FARS data follows a consistent workflow.
At Case Intake
Pull county-level and state-level crash data for the accident location. The intake review should cover the following.
- Location type to determine whether municipal liability applies
- Vehicle type to identify enhanced injury or design defect arguments
- Time of day to assess comparative fault exposure and alcohol-related liability
- Jurisdiction fatality trends to frame the case within the documented crash pattern for that area
During Settlement Negotiation
FARS data serves as an external benchmark. When an adjuster offers a figure, jurisdiction-specific fatality and injury trends show whether the offer reflects the actual risk profile of the crash. A nighttime, non-intersection collision with an SUV in an unprotected urban area matches the highest-fatality crash profile in the national data. That profile should be reflected in the valuation.
At Trial
FARS data supports expert testimony from accident reconstruction specialists. Jurisdiction-specific crash trends show a jury that the incident was part of a documented pattern, not an isolated event. Under the Daubert standard, FARS meets the threshold for reliable methodology because it draws from a federally maintained census of all fatal traffic crashes, with data integrity and chain of custody maintained by NHTSA. Heatmaps and data visualizations translate raw numbers into courtroom evidence jurors understand without statistical training.
Why Bicycle Crash Litigation Is Growing
Bicyclist fatalities have risen 73% since 2010. The Consumer Product Safety Commission reports 454,008 emergency department-treated bicycle injuries in 2024. E-bike deaths surged from 6 in 2018 to 97 in 2024, creating a new vehicle classification problem for regulators and litigators alike.
These trends point to sustained growth in bicycle injury litigation. Firms that build case strategy on granular crash data rather than general negligence principles will value claims more accurately, negotiate from stronger evidence, and present more compelling arguments at trial. The data is public. The advantage lies in knowing how to use it.
