Yearly Traffic Safety Analysis

3,939 CRASHES IN
CONNECTICUT, CT
2015

In 2015, Litchfield County recorded 3,939 total traffic crashes, which resulted in 22 fatalities and 1,108 injuries. These incidents involved 8,782 individuals and 6,632 vehicles. Notably, over three-quarters of all crashes (76.9%) resulted in no reported injuries, indicating a high volume of property-damage-only events.

3,939

Total Crash Events

22

Persons Killed

1,108

Persons Injured

8.5%

Hit-and-Run Rate

Note: "Persons Killed" (22) counts individual fatalities across all crash events. "Fatal" in the severity table below (21) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

334

Hit-and-Run Crashes — 2015

A total of 334 crashes, representing 8.5% of all incidents in Litchfield County, were classified as hit-and-run events. This classification is based on the initial determination made by the responding law enforcement officer at the scene. These incidents involved a driver leaving the scene of a crash without providing required information or rendering aid.

Vulnerable Road User Casualties

In 2015, motorists comprised the largest group of killed or seriously injured individuals, with 17 fatalities and 1,072 injuries. Vulnerable road users also suffered significant harm; four pedestrians were killed and 24 were injured in 29 separate incidents. Additionally, one cyclist was killed and 12 were injured in crashes involving bicycles.

4

Pedestrians Killed

1

Cyclists Killed

17

Motorists Killed

24

Pedestrians Injured

12

Cyclists Injured

1,072

Motorists Injured

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency in Litchfield County peaked on Fridays, which saw 605 incidents, and during the 3 p.m. hour, when 347 crashes occurred. The data shows a clear pattern of crashes occurring during daylight hours, with 2,803 incidents (71.2%) happening in daylight. In contrast, 969 crashes (24.6%) were recorded in dark conditions, whether on lighted or unlighted roadways.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The vast majority of crashes, 76.9% or 3,030 incidents, were property-damage-only events with no reported injuries. Crashes involving some level of injury (possible, minor, or serious) accounted for 22.5% of the total. In 2015, there were 21 distinct fatal crashes, which resulted in a total of 22 fatalities.

Severity is per crash event (most severe injury). 21 fatal crash events resulted in 22 persons killed.

Outcome by Severity (Crash Events)

Fatal21fatal crashes0.5%
Serious Injury50serious injury crashes1.3%
Minor Injury427minor injury crashes10.8%
Possible Injury411possible injury crashes10.4%
No Injury3,030no injury crashes76.9%

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The majority of crashes occurred in ideal driving conditions. Approximately 74.8% of crashes (2,945) happened in clear weather, 73.8% (2,906) on dry road surfaces, and 71.2% (2,803) during daylight hours. Adverse conditions were less frequent, with rain-related crashes accounting for 338 incidents and snow-related crashes for 180 incidents.

Weather

Clear2,945 (75.7%)
Rain338 (8.7%)
Cloudy248 (6.4%)
Snow180 (4.6%)
Freezing Rain or Freezing Drizzle95 (2.4%)
Fog, Smog, Smoke40 (1.0%)
Blowing Snow32 (0.8%)
Other9 (0.2%)
Sleet or Hail4 (0.1%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight2,803 (71.8%)
Dark-Not Lighted560 (14.3%)
Dark-Lighted409 (10.5%)
Dusk73 (1.9%)
Dawn38 (1.0%)
Other12 (0.3%)
Dark-Unknown Lighting10 (0.3%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry2,906 (74.2%)
Wet516 (13.2%)
Snow228 (5.8%)
Ice / Frost149 (3.8%)
Slush64 (1.6%)
Mud, Dirt, Gravel26 (0.7%)
Sand10 (0.3%)
Other8 (0.2%)
Oil3 (0.1%)
Standing Water2 (0.1%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Among all individuals involved in crashes, the 45-54 age group was the most represented, with 1,365 people. The 26-34 age group followed with 1,177 individuals. Analysis of the 6,632 vehicles involved shows that Ford was the most common make, appearing in 819 instances, followed by Chevrolet (602) and Honda (597).

Top Vehicle Makes (6,632 vehicles)

1
FORD819 (12.3%)
2
CHEV366 (5.5%)
3
HOND354 (5.3%)
4
JEEP312 (4.7%)
5
SUBA284 (4.3%)
6
TOYT257 (3.9%)
7
HONDA243 (3.7%)
8
CHEVROLET236 (3.6%)
9
TOYOTA231 (3.5%)
10
SUBARU204 (3.1%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

465 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (7,908 persons with recorded sex)

Male4,463 (56.4%)
Female3,445 (43.6%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Speed Limit Zones

The most crashes, 1,063 incidents, occurred in zones with a posted speed limit of 25 mph. While crashes were widespread across various speed limits, the fatality rate within zones varied significantly. For instance, while only 19 crashes occurred in 55 mph zones, 10.5% of those were fatal. Similarly, 1.55% of crashes in 65 mph zones were fatal, compared to just 0.38% in 25 mph zones.

Fatal crashes by zone: 1 mph: 1 of 197 (0.508%) · 25 mph: 4 of 1,063 (0.376%) · 30 mph: 5 of 518 (0.965%) · 40 mph: 1 of 439 (0.228%) · 45 mph: 4 of 323 (1.238%) · 55 mph: 2 of 19 (10.526%) · 65 mph: 3 of 193 (1.554%) · 99 mph: 1 of 46 (2.174%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Posted speed limit at crash location

Top Towns

The distribution of crashes across Litchfield County was concentrated in its more populated areas. The city of Torrington recorded the highest number of incidents with 836 crashes, accounting for 21.2% of the county's total. New Milford followed with 593 crashes (15.1%), and Watertown had 406 crashes (10.3%).

Top Towns

1
Torrington836 (21.2%)
2
New Milford593 (15.1%)
3
Watertown406 (10.3%)
4
Winchester327 (8.3%)
5
Litchfield215 (5.5%)
6
Plymouth213 (5.4%)
7
Thomaston200 (5.1%)
8
Woodbury177 (4.5%)
9
Harwinton133 (3.4%)

Showing top 9 of 26 reported. 17 additional (839 total) not shown: New Hartford, Barkhamsted, Washington, Salisbury, Kent, North Canaan, Sharon, Goshen, Roxbury, Morris, Bethlehem, Norfolk, Cornwall, Canaan, Colebrook, Bridgewater, Warren.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Road Class

Analysis of roadway classification shows that Collector roads saw the highest number of crashes, with 403 incidents recorded. Minor Arterial roads accounted for 253 crashes, and Principal Arterial roads for 232. Limited-access highways, including Freeways and Expressways, were the site of 153 crashes.

Road Class

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Route System

Crashes were distributed across different roadway jurisdictions, with state-maintained routes (State and US Routes) accounting for a combined 2,496 incidents. Local roads under municipal jurisdiction were the location for 1,245 crashes. This indicates that the majority of crashes occurred on roads maintained by the state.

Route System

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Public vs Private Road

Of the crashes where roadway ownership was documented, the vast majority occurred on public roads. A total of 3,646 crashes took place on public thoroughfares. In contrast, 134 crashes, or 3.5% of the total, occurred on private roads, such as those in parking lots or private developments.

Rural vs Urban

From the crashes where a rural or urban designation was recorded, a slight majority occurred in rural settings. Rural areas accounted for 762 crashes, representing 55.1% of these classified incidents. Urban areas were the location for the remaining 620 crashes.

Rural vs Urban

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Junction Type

The majority of crashes did not occur at an intersection. A total of 2,877 incidents, or 73% of all crashes, happened at non-junction locations. For crashes that did occur at intersections, T-intersections were the most common site with 582 incidents, followed by four-way intersections with 380 incidents.

Junction Type

1
Not at Intersection2,877 (73.2%)
2
T-Intersection582 (14.8%)
3
Four-Way Intersection380 (9.7%)
4
Y-Intersection68 (1.7%)
5
L-Intersection16 (0.4%)
6
Five-Point, or More6 (0.2%)
7
Roundabout3 (0.1%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Run-off-Road / Fixed-Object Strikes

Among crashes where the first harmful event was a collision with a fixed object, the most frequently struck object was a guardrail face, which was hit 223 times. Utility poles and trees were also common hazards, with vehicles striking utility poles 122 times and trees 118 times. Together, poles and trees accounted for 240 of these single-vehicle, run-off-road crashes.

Run-off-Road / Fixed-Object Strikes

1
Guardrail Face223 (18.5%)
2
Other Fixed Object (wall, building, tunnel, etc.)160 (13.2%)
3
Utility Pole/Light Support122 (10.1%)
4
Tree (standing)118 (9.8%)
5
Other Post, Pole or Support102 (8.4%)
6
Cable Barrier97 (8%)
7
Embankment90 (7.5%)
8
Curb57 (4.7%)
9
Mailbox44 (3.6%)

Showing top 9 of 21 reported. 12 additional (195 total) not shown: Guardrail End, Ditch, Traffic Sign Support, Fence, Other Traffic Barrier, Bridge Rail, Culvert, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Concrete Traffic Barrier, Bridge Overhead Structure, Traffic Signal Support, Bridge Pier or Support.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 3,795 of all vehicles. Sport Utility Vehicles (1,272) and Pickups (717) were the next most frequent. Notably, 159 medium or heavy trucks and 95 motorcycles were also involved in crashes during this period.

Vehicle Type

1
Passenger Car3,795 (58.3%)
2
(Sport) Utility Vehicle1,272 (19.5%)
3
Pick Up717 (11%)
4
Passenger Van190 (2.9%)
5
Medium / Heavy Trucks (more than 10,000 lbs (4,536 kg))159 (2.4%)
6
Motorcycle95 (1.5%)
7
Other Light Trucks (10,000 lbs (4,536 kg) or less)93 (1.4%)
8
Other76 (1.2%)
9
Cargo Van (10,000 lbs/4,536 kg or less)70 (1.1%)

Showing top 9 of 16 reported. 7 additional (47 total) not shown: School Bus, Moped, Low Speed Vehicle, Transit Bus, Other Bus, Motor Coach, All Terrain Vehicle (ATV).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

Among vehicles involved in crashes where traffic control was noted, the majority (4,868 vehicles) were at locations with no control device. At intersections with controls, 1,029 vehicles were involved in crashes at locations with a traffic signal, while 491 were at intersections controlled by a stop sign.

Traffic Control Device

"Other" combines 4 smaller categories (36 records): Marked Uncontrolled Crosswalk (21), Warning Sign (13), Pedestrian Button (1), School Zone Sign/Device (1).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Vulnerable Road Users & Motorcycles

In crashes involving vulnerable road users, motorcyclists were the most frequently involved group, with 92 incidents. There were also 29 crashes involving pedestrians and 13 involving bicyclists. Combined, pedestrians and bicyclists were involved in 42 crashes, representing 31.3% of these specific incidents.

Driver Contributing Action

Analysis of contributing driver actions reveals that following too closely was the most cited behavior, attributed to 885 drivers. Failing to keep in the proper lane was the second most common action, noted for 577 drivers, followed by running off the roadway, which was a factor for 359 drivers.

Driver Contributing Action

1
No Contributing Action2,519 (41.6%)
2
Followed Too Closely885 (14.6%)
3
Failed to Keep in Proper Lane577 (9.5%)
4
Ran Off Roadway359 (5.9%)
5
Failed to Yield Right-of-Way327 (5.4%)
6
Other Contributing Action251 (4.1%)
7
Improper Backing220 (3.6%)
8
Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner196 (3.2%)
9
Improper Turn186 (3.1%)

Showing top 9 of 19 reported. 10 additional (535 total) not shown: Swerved or Avoided Due to Wind, Slippery Surface, Motor Vehicle, Object, Non-Motorist in Roadway, etc., Ran Stop Sign, Improper Passing, Over-Correcting/Over-Steering, Ran Red Light, Operated Motor Vehicle in Reckless or Aggressive Manner, Wrong Side or Wrong Way, Disregarded Other Traffic Sign, Disregarded Other Road Markings, Overtaking Cyclist.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Driver Condition

While most drivers were recorded as 'Apparently Normal', several impairing conditions were noted. A total of 158 drivers were identified as being under the influence of medications, drugs, or alcohol. Additionally, 115 drivers were reported as being asleep or fatigued at the time of their crash.

Driver Condition

1
Apparently Normal5,549 (93.2%)
2
Under the Influence of Medications/Drugs/Alcohol158 (2.7%)
3
Asleep or Fatigued115 (1.9%)
4
Emotional (depressed, angry, disturbed, etc.)41 (0.7%)
5
Other40 (0.7%)
6
Physically Impaired31 (0.5%)
7
Ill (sick), Fainted20 (0.3%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Pre-Crash Driver Action

The most common pre-crash action for vehicles was driving straight ahead, which was the case for 2,850 vehicles. A significant number of vehicles were stationary just before impact, with 637 stopped in traffic. Another common pre-crash maneuver was negotiating a curve, reported for 614 vehicles.

Pre-Crash Driver Action

1
Straight Ahead2,850 (43.7%)
2
Stopped in Traffic637 (9.8%)
3
Negotiating a Curve614 (9.4%)
4
Turning Left549 (8.4%)
5
Parked388 (5.9%)
6
Backing297 (4.5%)
7
Slowing278 (4.3%)
8
Turning Right246 (3.8%)
9
Other190 (2.9%)

Showing top 9 of 15 reported. 6 additional (480 total) not shown: Overtaking/Passing, Entering Traffic Lane, Changing Lanes, Leaving Traffic Lane, Wrong way (or Wrong Side), Making U-Turn.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Point of Impact

The front of the vehicle was the most common point of impact, recorded as the 'Sector 12' or north impact for 1,828 vehicles. The second most frequent impact point was the rear of the vehicle, or 'Sector 6', which occurred in 1,165 instances. These two locations represent the majority of initial vehicle impacts.

Point of Impact

"Other" combines 9 smaller categories (964 records): Sector 2 (NorthEast) in the 12-point Clock Diagram (205), Sector 9 (West) in the 12-point Clock Diagram (203), Sector 3 (East) in the 12-point Clock Diagram (167), Sector 8 (SouthWest) in the 12-point Clock Diagram (147), Sector 4 (SouthEast) in the 12-point Clock Diagram (96), Non-Collision (69), Top (38), Undercarriage (29), Cargo loss (10).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Pedestrian/Cyclist Action

In incidents involving pedestrians, the most common recorded action was 'No Improper Action,' attributed to 15 individuals. However, several improper actions were also noted, including 5 instances of pedestrians being in the roadway improperly and 3 instances of a 'Dart/Dash' maneuver into traffic.

Pedestrian/Cyclist Action

1
No Improper Action15 (36.6%)
2
In Roadway Improperly (Standing, Lying, Working, Playing)5 (12.2%)
3
Dart/Dash3 (7.3%)
4
Failure to Obey Traffic Signs, Signals, or Officer3 (7.3%)
5
Failure to Yield Right-Of-Way3 (7.3%)
6
Other3 (7.3%)
7
Inattentive (Talking, Eating, etc.)2 (4.9%)
8
Improper Turn/Merge2 (4.9%)
9
Not Visible (Dark Clothing, No Lighting, etc.)2 (4.9%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Disabled Vehicle Related (Working on, Pushing, Leaving/Approaching), Entering/Exiting Parked/Standing Vehicle, Wrong-Way Riding or Walking.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Non-motorist records linked to crash events

Manner of Collision

The most frequent type of crash was a front-to-rear collision, which accounted for 1,125 incidents, or 28.6% of the total. Angle collisions were the second most common type, with 575 incidents (14.6%). Sideswipes in the same direction occurred in 272 crashes.

Manner of Collision

"Other" combines 1 smaller categories (37 records): Rear to rear (37).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Type

Of the 8,782 people involved in crashes, the majority were drivers, with 6,322 individuals recorded in this role. Passengers constituted the next largest group, with 1,796 people. The data also includes 30 pedestrians and 13 bicyclists involved in these traffic incidents.

Person Type

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Across all 8,399 persons with a recorded injury status, 22 individuals sustained fatal injuries. A total of 1,108 persons were injured, with severities ranging from possible (549 persons) and minor (500 persons) to serious (59 persons). The vast majority, 7,269 individuals, were not injured.

Person Injury Severity

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

While most vehicle occupants (6,197) used both a shoulder and lap belt, a notable number did not. The data indicates that 538 occupants used no safety equipment at the time of the crash. Additionally, various forms of child restraints were in use, including 125 forward-facing systems and 34 rear-facing systems.

Occupant Safety Equipment

"Other" combines 3 smaller categories (62 records): Other (26), Booster Seat (24), Child Restraint, Type Unknown (12).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

The most common type of crash involved two vehicles, with 2,354 such incidents occurring. Single-vehicle crashes were also frequent, accounting for 1,434 incidents, or 36.4% of all crashes. Multi-vehicle pile-ups were rare, though there were 134 crashes involving three vehicles and one incident involving seven vehicles.

Vehicles Per Crash

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Connecticut Crash Data, accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: Csv Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2015-01-01 through 2015-12-31
  • Report generated: September 10, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: connecticut, CT
  • Total crash records analyzed: 3,939
  • Total persons involved: 8,782
  • Total vehicles involved: 6,632

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "connecticut, CT Crash Intelligence Report: 2015." Published September 10, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2015-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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