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CRASH INTELLIGENCE REPORT · CONNECTICUT, CT · FEBRUARY 2018
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/connecticut/statewide/february-2018-report
Monthly Traffic Safety Analysis
8,260 CRASHES IN
CONNECTICUT, CT
FEBRUARY 2018
In February 2018, Connecticut recorded 8,260 traffic crashes, resulting in 20 fatalities and 2,647 injuries. These incidents involved 19,691 people and 15,107 vehicles across the state. The most common type of collision was front-to-rear, accounting for 33.3% of all crashes.
8,260
Total Crash Events
20
Persons Killed
2,647
Persons Injured
11.7%
Hit-and-Run Rate
Note: "Persons Killed" (20) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Aggregate counts from crash, person, and vehicle records
965
Hit-and-Run Crashes — February 2018
Of the total crashes reported, 965 were classified as hit-and-run incidents, representing 11.7% of all collisions during this period. This determination is based on the initial assessment made by the responding law enforcement officer at the scene of the crash.
Vulnerable Road User Casualties
Of the 20 fatalities, 15 were motor-vehicle occupants and 5 were pedestrians. Among the 2,647 people injured, the vast majority were motorists (2,542), while 89 pedestrians and 16 cyclists also sustained injuries. No cyclist fatalities were recorded during this period.
5
Pedestrians Killed
0
Cyclists Killed
15
Motorists Killed
89
Pedestrians Injured
16
Cyclists Injured
2,542
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crash frequency peaked on Friday, which saw 1,422 incidents, the highest of any day of the week. The single busiest hour for crashes was the 3 p.m. hour, with 626 events. Overall, more crashes occurred during daylight hours (4,959) than during all periods of darkness, dawn, and dusk combined (3,201).
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The majority of crashes, 76.6% (6,329), resulted in no injuries and were property-damage-only events. Injury-sustaining crashes, including those with possible, minor, or serious injuries, accounted for 23.1% of the total. There were 20 fatal crashes, which resulted in 20 total fatalities.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Most severe injury per crash record
Road & Environmental Conditions
A majority of crashes occurred in favorable conditions, with 65.0% (5,372) happening in clear weather and 60.0% (4,959) during daylight hours. Similarly, 59.8% of crashes (4,942) were on dry road surfaces. Adverse conditions were also a factor, with 1,256 crashes occurring during rain and 2,039 crashes on wet roadways.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Road surface condition field
Vehicles & Demographics
Among all persons involved in crashes, the 26-34 age group was the most represented, with 3,330 individuals, followed by the 35-44 age group with 2,882. An analysis of the 15,107 vehicles involved shows that the most frequent makes were Ford (1,431), Toyota (1,397), and Honda (1,371).
Top Vehicle Makes (15,107 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Vehicle unit records
1,315 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (18,456 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Person-level records linked to crash events
Speed Limit Zones
The most crashes, 2,630 (31.8% of the total), occurred in zones with a posted speed limit of 25 mph. Within this speed zone, 0.34% of crashes were fatal. In contrast, while zones with a 65 mph speed limit saw fewer crashes (433), they had a higher fatal crash rate, with 1.39% of those crashes resulting in a fatality.
Fatal crashes by zone: 25 mph: 9 of 2,630 (0.342%) · 35 mph: 2 of 970 (0.206%) · 40 mph: 2 of 455 (0.44%) · 65 mph: 6 of 433 (1.386%) · 88 mph: 1 of 541 (0.185%)
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Posted speed limit at crash location
Top Counties
Crash distribution was concentrated in three counties, which together accounted for over 80% of all incidents. Fairfield County and New Haven County each recorded 2,282 crashes (27.6% each), while Hartford County saw 2,092 crashes (25.3%). The remaining five counties each accounted for less than 7% of the statewide total.
Top Counties
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Top Towns
Connecticut's urban centers saw the highest crash volumes in February 2018. New Haven had the most incidents with 525 crashes, followed by Bridgeport with 481, Waterbury with 451, and Hartford with 448. These four cities collectively accounted for 1,905 crashes, representing 23% of the statewide total.
Top Towns
Showing top 9 of 50 reported. 41 additional (3,457 total) not shown: Manchester, New Britain, Fairfield, West Hartford, East Hartford, Bristol, Meriden, Norwich, Greenwich, Middletown, Windsor, Stratford, Wallingford, North Haven, Southington, Farmington, Orange, Milford, Trumbull, Torrington, New London, Newington, Wethersfield, Newtown, Westport, Enfield, Groton, Vernon, Windham, Mansfield, Shelton, Naugatuck, Plainville, New Milford, Berlin, Darien, Ridgefield, Glastonbury, Rocky Hill, Cheshire, Branford.
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Road Class
Arterial roads were the site of the most crashes, with 2,008 on Minor Arterials and 1,621 on Principal Arterials. Combined, these two classes accounted for 44% of all crashes. Limited-access highways, including Interstates (1,060) and Freeways/Expressways (627), comprised 20.4% of the total crash locations.
Road Class
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Route System
An analysis of roadway jurisdiction shows a split between state-maintained and local roads. Crashes on state-maintained routes (including State, Interstate, and US Routes) totaled 4,350, while crashes on local roads totaled 3,456. This indicates that state-maintained systems were the location for approximately 55.7% of crashes where the route system was known.
Route System
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Public vs Private Road
Of the crashes where roadway ownership was documented, the vast majority (7,718) occurred on public roads. A smaller but notable number of incidents, 370 crashes or 4.6% of the known total, took place on private property such as parking lots or private drives.
Rural vs Urban
The data indicates a significant majority of crashes occurred in urban settings. Of the 7,302 crashes with a specified location type, 6,877 were in urban areas. Crashes in rural areas accounted for 425 incidents, or 5.8% of the total.
Rural vs Urban
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Junction Type
The majority of crashes, 5,546 incidents, did not occur at an intersection. However, a significant number of collisions, 2,687 or 32.6% of the total where junction type was specified, happened at or were related to an intersection. The most common intersection types for crashes were four-way intersections (1,354) and T-intersections (1,173).
Junction Type
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Run-off-Road / Fixed-Object Strikes
Among crashes involving a collision with a fixed object, the most commonly struck objects were guardrail faces (306), other fixed objects like walls or buildings (266), and utility poles or light supports (218). Collisions with utility poles (218) and trees (176) together accounted for 394 incidents, representing 23.1% of all fixed-object crashes.
Run-off-Road / Fixed-Object Strikes
Showing top 9 of 22 reported. 13 additional (287 total) not shown: Fence, Mailbox, Ditch, Guardrail End, Cable Barrier, Impact Attenuator/Crash Cushion, Other Traffic Barrier, Bridge Rail, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Bridge Overhead Structure, Traffic Signal Support, Culvert, Bridge Pier or Support.
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Vehicle Type
Passenger cars were the most common vehicle type involved in crashes, accounting for 9,094 of the 15,107 vehicles. Sport Utility Vehicles were the second most common with 3,194 involved. Medium and heavy trucks, a category with higher potential severity, were involved in 321 crashes, making up 2.1% of all vehicles.
Vehicle Type
Showing top 9 of 17 reported. 8 additional (101 total) not shown: Transit Bus, Other Bus, Motorcycle, Motor Home, Moped, All Terrain Vehicle (ATV), Motor Coach, Low Speed Vehicle.
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Vehicle unit records
Traffic Control Device
For a majority of vehicles involved in crashes (66.3%), no traffic control device was present at the location. Approximately 25.4% of vehicles were involved in crashes at locations with a traffic control signal. Crashes at intersections with stop signs involved 1,136 vehicles.
Traffic Control Device
"Other" combines 4 smaller categories (21 records): Person (including flagger, law enforcement, crossing guard, etc.) (11), Marked Uncontrolled Crosswalk (6), School Zone Sign/Device (2), Pedestrian Button (2).
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Vehicle unit records
Vulnerable Road Users & Motorcycles
During this period, there were 140 crashes involving pedestrians, bicyclists, or motorcyclists. Pedestrians were involved in 107 of these incidents and bicyclists in 23. Combined, these two vulnerable user groups accounted for 130 crashes, or 92.9% of all crashes in this category.
Driver Contributing Action
Among drivers for whom a contributing action was cited, the most common error was following too closely, attributed to 2,145 drivers. The next most frequent actions were failure to keep in the proper lane (1,512 drivers) and failure to yield the right-of-way (829 drivers). These actions represent common driver behaviors leading to collisions.
Driver Contributing Action
Showing top 9 of 19 reported. 10 additional (851 total) not shown: Ran Stop Sign, Improper Passing, Ran Red Light, Swerved or Avoided Due to Wind, Slippery Surface, Motor Vehicle, Object, Non-Motorist in Roadway, etc., Operated Motor Vehicle in Reckless or Aggressive Manner, Over-Correcting/Over-Steering, Wrong Side or Wrong Way, Disregarded Other Traffic Sign, Disregarded Other Road Markings, Overtaking Cyclist.
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Person-level records linked to crash events
Driver Condition
While most drivers were recorded as 'Apparently Normal,' a number of crashes involved drivers with other reported conditions. Being under the influence of medications, drugs, or alcohol was noted for 244 drivers. Additionally, 96 drivers were reported as asleep or fatigued, and 57 were noted as being emotional.
Driver Condition
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Person-level records linked to crash events
Pre-Crash Driver Action
The most common pre-crash action for drivers was moving straight ahead, which was the case for 6,799 drivers. A significant number of drivers were stopped in traffic (1,561) or in the process of turning left (1,148) just prior to their collision. These actions represent the most common traffic situations leading to a crash.
Pre-Crash Driver Action
Showing top 9 of 17 reported. 8 additional (963 total) not shown: Entering Traffic Lane, Overtaking/Passing, Other, Leaving Traffic Lane, Making U-Turn, Wrong way (or Wrong Side), Overtaking/Passing Cyclist, Traveling in Bike Lane.
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Vehicle unit records
Point of Impact
Analysis of vehicle impact points shows that frontal impacts were the most common, with 4,442 vehicles struck in the front ('Sector 12'). The second most frequent point of impact was the rear of the vehicle ('Sector 6'), which was recorded for 2,753 vehicles. These two locations account for nearly half of all impacts recorded.
Point of Impact
"Other" combines 9 smaller categories (2,199 records): Sector 5 (South by SouthEast) in the 12-point Clock Diagram (554), Sector 9 (West) in the 12-point Clock Diagram (389), Sector 8 (SouthWest) in the 12-point Clock Diagram (366), Sector 3 (East) in the 12-point Clock Diagram (344), Sector 4 (SouthEast) in the 12-point Clock Diagram (343), Top (88), Non-Collision (71), Undercarriage (41), Cargo loss (3).
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Vehicle unit records
Pedestrian/Cyclist Action
In 60 of the 125 instances where pedestrian action was recorded, it was determined that the pedestrian committed no improper action. For those where an improper action was noted, the most common were being in the roadway improperly (15 instances), failure to yield right-of-way (12 instances), and darting or dashing into the road (10 instances).
Pedestrian/Cyclist Action
Showing top 9 of 10 reported. 1 additional (1 total) not shown: Use of Electronic Device.
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Non-motorist records linked to crash events
Manner of Collision
The most prevalent type of crash was a front-to-rear collision, which accounted for 2,751 incidents, or 33.3% of all crashes. The second most common crash type was an angle collision, with 1,574 occurrences (19.1%). Together, these two types represent over half of all crashes during the period.
Manner of Collision
"Other" combines 1 smaller categories (78 records): Rear to rear (78).
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Person Type
Of the 19,691 individuals involved in crashes, the majority were drivers (14,337), accounting for 72.8% of all persons. Passengers made up the next largest group with 4,415 individuals (22.4%). Vulnerable road users were also present, including 114 pedestrians and 23 bicyclists.
Person Type
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Person Injury Severity
Out of 19,691 people involved in crashes, 2,667 sustained some level of injury or were killed. This includes 20 fatalities (0.1%), 86 serious injuries, 940 minor injuries, and 1,621 possible injuries. The vast majority of individuals, 16,333 or 83.0%, were not injured.
Person Injury Severity
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Crash-level records
Occupant Safety Equipment
Safety equipment usage was high among vehicle occupants, with 13,855 individuals reported as using both a shoulder and lap belt. However, 462 occupants were recorded as using no restraint system at all, representing approximately 3.0% of occupants for whom safety equipment use was documented.
Occupant Safety Equipment
"Other" combines 3 smaller categories (128 records): Other (60), Booster Seat (42), Child Restraint, Type Unknown (26).
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · Person-level records linked to crash events
Vehicles Per Crash
The most common type of crash involved two vehicles, accounting for 5,833 incidents or 70.6% of the total. Single-vehicle crashes were the next most frequent, with 1,973 incidents (23.9%). Multi-vehicle pile-ups were less common, though one crash involved as many as 7 vehicles.
Vehicles Per Crash
"Other" combines 1 smaller categories (1 records): 7 (1).
Source: Connecticut Crash Data · Csv Open Data · 2018-02-01 to 2018-02-28 · 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: 2018-02-01 through 2018-02-28
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2018-02-01 through 2018-02-28 (28 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,260
- Total persons involved: 19,691
- Total vehicles involved: 15,107
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: February 2018." Published August 20, 2026. Reporting period: 2018-02-01 to 2018-02-28. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/february-2018-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Connecticut Crash Data · Csv
Period: 2018-02-01 – 2018-02-28
Generated: August 20, 2026 · All rights reserved
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