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Monthly Traffic Safety Analysis

10,215 CRASHES IN
CONNECTICUT, CT
JANUARY 2018

In January 2018, Connecticut recorded 10,215 traffic crashes, resulting in 21 fatalities and 2,871 injuries. Analysis of the data reveals that Tuesdays were the most frequent day for crashes, accounting for 1,956 incidents. The most common type of collision was front-to-rear, representing 33.9% of all crashes during this period.

10,215

Total Crash Events

21

Persons Killed

2,871

Persons Injured

11.0%

Hit-and-Run Rate

Note: "Persons Killed" (21) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Aggregate counts from crash, person, and vehicle records

1,124

Hit-and-Run Crashes — January 2018

A total of 1,124 hit-and-run crashes were reported, accounting for 11% of all incidents in this period. This designation is based on the responding officer's initial determination at the scene. These incidents represent a significant portion of the total crash volume.

Vulnerable Road User Casualties

Motorists comprised the largest group of individuals killed or injured, with 15 fatalities and 2,742 injuries. Pedestrians also faced significant risk, with 6 individuals killed and 124 injured in traffic collisions. There were no cyclist fatalities reported, though 4 cyclists sustained injuries.

6

Pedestrians Killed

0

Cyclists Killed

15

Motorists Killed

0

Other Killed

124

Pedestrians Injured

4

Cyclists Injured

2,742

Motorists Injured

1

Other Injured

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency peaked on Tuesdays, with 1,956 incidents recorded, and during the 5 p.m. hour, which saw 876 crashes. A distinct pattern of morning and afternoon commute peaks is visible, with 866 crashes at 8 a.m. and 876 at 5 p.m. While a majority of crashes (6,206) occurred during daylight, a substantial number (3,564) happened in dark conditions, whether on lighted or unlighted roads.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The vast majority of crashes, 79.2% (8,095 incidents), resulted in no injuries. Injury-involved crashes, including serious, minor, and possible injuries, accounted for 20.6% of the total. There were 17 fatal crashes, which resulted in a total of 21 fatalities, indicating some incidents involved more than one death.

Severity is per crash event (most severe injury). 17 fatal crash events resulted in 21 persons killed.

Outcome by Severity (Crash Events)

Fatal17fatal crashes0.2%
Serious Injury78serious injury crashes0.8%
Minor Injury737minor injury crashes7.2%
Possible Injury1,288possible injury crashes12.6%
No Injury8,095no injury crashes79.2%

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Most severe injury per crash record

Road & Environmental Conditions

A majority of crashes occurred in ideal driving conditions, with 78.5% (8,020 crashes) happening in clear weather and 63.8% (6,513 crashes) on dry road surfaces. Similarly, 60.8% of incidents (6,206) took place in daylight. Adverse conditions were also a factor, with 669 crashes occurring in snow and 1,639 on wet roads.

Weather

Clear8,020 (78.9%)
Snow669 (6.6%)
Rain585 (5.8%)
Cloudy490 (4.8%)
Blowing Snow204 (2.0%)
Fog, Smog, Smoke106 (1.0%)
Freezing Rain or Freezing Drizzle42 (0.4%)
Other28 (0.3%)
Sleet or Hail14 (0.1%)
Severe Crosswinds2 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Weather condition at time of crash

Lighting

Daylight6,206 (61.3%)
Dark-Lighted2,718 (26.8%)
Dark-Not Lighted846 (8.4%)
Dusk179 (1.8%)
Dawn109 (1.1%)
Dark-Unknown Lighting53 (0.5%)
Other16 (0.2%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Lighting condition field

Road Surface

Dry6,513 (64.1%)
Wet1,639 (16.1%)
Snow971 (9.6%)
Ice / Frost619 (6.1%)
Slush305 (3.0%)
Sand67 (0.7%)
Other36 (0.4%)
Mud, Dirt, Gravel7 (0.1%)
Moving Water5 (0.0%)
Standing Water4 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Road surface condition field

Vehicles & Demographics

Among the 24,170 individuals involved in crashes, the 26-34 age group was the most represented, accounting for 4,222 people. The most frequently involved vehicle makes were Honda (2,140), Toyota (2,138), and Nissan (1,673). Ford (1,883) and Chevrolet (1,456) were also commonly involved in collisions during this period.

Top Vehicle Makes (18,859 vehicles)

1
FORD1,883 (10%)
2
HONDA1,724 (9.1%)
3
TOYOTA1,717 (9.1%)
4
NISSAN1,291 (6.8%)
5
CHEVROLET964 (5.1%)
6
JEEP721 (3.8%)
7
SUBARU629 (3.3%)
8
HYUNDAI562 (3%)
9
DODGE443 (2.3%)
10
HOND416 (2.2%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Vehicle unit records

1,573 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (22,790 persons with recorded sex)

Male12,867 (56.5%)
Female9,923 (43.5%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Person-level records linked to crash events

Speed Limit Zones

The 25 mph speed zone saw the highest number of crashes, with 3,176 incidents, representing 31.1% of all crashes. While crash volume was highest in lower speed zones, the percentage of crashes that were fatal increased in higher speed zones. For instance, 0.19% of crashes in 25 mph zones were fatal, compared to 0.43% of crashes in 65 mph zones.

Fatal crashes by zone: 25 mph: 6 of 3,176 (0.189%) · 30 mph: 4 of 955 (0.419%) · 35 mph: 1 of 1,170 (0.085%) · 40 mph: 1 of 650 (0.154%) · 45 mph: 1 of 405 (0.247%) · 65 mph: 2 of 470 (0.426%) · 88 mph: 1 of 651 (0.154%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Posted speed limit at crash location

Top Counties

Crash distribution was heavily concentrated in three counties, which together accounted for 81.1% of all incidents statewide. New Haven County recorded the most crashes with 2,869, followed closely by Fairfield County with 2,844 and Hartford County with 2,574. The remaining five counties each accounted for less than 7% of the state's total crashes.

Top Counties

1
New Haven2,869 (28.1%)
2
Fairfield2,844 (27.8%)
3
Hartford2,574 (25.2%)
4
New London657 (6.4%)
5
Litchfield425 (4.2%)
6
Middlesex346 (3.4%)
7
Tolland271 (2.7%)
8
Windham228 (2.2%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Top Towns

New Haven and Waterbury were the municipalities with the highest number of crashes, recording 643 and 642 incidents, respectively. They were followed by Bridgeport (555 crashes), Hartford (518 crashes), and Stamford (454 crashes). These five cities collectively accounted for 27.5% of all crashes in the state for the month.

Top Towns

1
New Haven643 (7.9%)
2
Waterbury642 (7.9%)
3
Bridgeport555 (6.9%)
4
Hartford518 (6.4%)
5
Stamford454 (5.6%)
6
Norwalk304 (3.8%)
7
Danbury303 (3.7%)
8
West Haven192 (2.4%)
9
New Britain190 (2.3%)

Showing top 9 of 50 reported. 41 additional (4,288 total) not shown: Stratford, West Hartford, Fairfield, Hamden, Manchester, Meriden, East Hartford, Bristol, Norwich, Wallingford, Greenwich, Middletown, North Haven, Southington, Windsor, Westport, Orange, Trumbull, Farmington, New London, Wethersfield, Torrington, Newtown, Shelton, Enfield, Groton, Milford, Naugatuck, Berlin, New Milford, Cheshire, Newington, Glastonbury, Vernon, Montville, Darien, Cromwell, Rocky Hill, Plainville, Bloomfield, Windham.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Road Class

Arterial roads were the site of the most crashes, with minor arterials accounting for 2,583 incidents and principal arterials for 1,950. Limited-access highways, including Interstates and Freeways/Expressways, collectively accounted for 1,906 crashes, or 18.7% of the total. Local roads saw 1,256 crashes.

Road Class

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Route System

The data indicates a near-even split in crash locations between state-maintained and local road systems. State-maintained routes (Interstate, US, and State routes) were the location for 5,290 crashes. Meanwhile, local roads accounted for 4,413 crashes during this period.

Route System

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Public vs Private Road

Of the crashes where roadway ownership was documented, 394 incidents occurred on private property, such as in parking lots or on private drives. The vast majority of crashes, 9,629, took place on public roads. This distinction is relevant for determining roadway maintenance responsibility and premises liability.

Rural vs Urban

The overwhelming majority of crashes, 8,306, occurred in areas classified as urban. In contrast, 485 crashes, or approximately 5.5% of those with a known classification, were recorded in rural areas. This highlights the concentration of crash incidents within more densely populated regions of the state.

Rural vs Urban

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Junction Type

Most crashes did not occur at an intersection, with 6,841 incidents classified as non-junction related. However, a significant number of collisions, 3,341 or 32.7% of the total, happened at or near an intersection. Among these, four-way intersections (1,672 crashes) and T-intersections (1,450 crashes) were the most common locations.

Junction Type

1
Not at Intersection6,841 (67.2%)
2
Four-Way Intersection1,672 (16.4%)
3
T-Intersection1,450 (14.2%)
4
Y-Intersection125 (1.2%)
5
Five-Point, or More39 (0.4%)
6
L-Intersection34 (0.3%)
7
Roundabout16 (0.2%)
8
Traffic Circle5

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Run-off-Road / Fixed-Object Strikes

In crashes involving a collision with a fixed object, the most frequently struck objects were guardrail faces (312 incidents) and other fixed objects like walls or buildings (303 incidents). Utility poles and trees were also common hazards, with a combined 434 crashes involving collisions with one of these two object types. These run-off-road crashes often indicate a loss of vehicle control.

Run-off-Road / Fixed-Object Strikes

1
Guardrail Face312 (16.7%)
2
Other Fixed Object (wall, building, tunnel, etc.)303 (16.2%)
3
Utility Pole/Light Support258 (13.8%)
4
Tree (standing)176 (9.4%)
5
Other Post, Pole or Support132 (7.1%)
6
Curb109 (5.8%)
7
Embankment92 (4.9%)
8
Concrete Traffic Barrier87 (4.7%)
9
Traffic Sign Support73 (3.9%)

Showing top 9 of 22 reported. 13 additional (327 total) not shown: Mailbox, Cable Barrier, Fence, Guardrail End, Other Traffic Barrier, Ditch, Bridge Overhead Structure, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Bridge Rail, Bridge Pier or Support, Traffic Signal Support, Impact Attenuator/Crash Cushion, Culvert.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 11,343 involvements, followed by sport utility vehicles with 3,954. Medium and heavy trucks were involved in 478 incidents, while buses, including school and transit buses, were involved in 205. Motorcycles were involved in 7 crashes during this period.

Vehicle Type

1
Passenger Car11,343 (61.3%)
2
(Sport) Utility Vehicle3,954 (21.4%)
3
Pick Up1,345 (7.3%)
4
Passenger Van532 (2.9%)
5
Medium / Heavy Trucks (more than 10,000 lbs (4,536 kg))478 (2.6%)
6
Other Light Trucks (10,000 lbs (4,536 kg) or less)245 (1.3%)
7
Cargo Van (10,000 lbs/4,536 kg or less)226 (1.2%)
8
Other171 (0.9%)
9
School Bus111 (0.6%)

Showing top 9 of 17 reported. 8 additional (110 total) not shown: Transit Bus, Other Bus, Motorcycle, Low Speed Vehicle, Motor Coach, Moped, All Terrain Vehicle (ATV), Motor Home.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Vehicle unit records

Traffic Control Device

Analysis of vehicle involvements shows that most occurred where no traffic control device was present (12,676 involvements). Locations with a traffic control signal saw 4,470 vehicle involvements, while those with a stop sign had 1,402. This indicates that a majority of crash involvements happened on uncontrolled road segments.

Traffic Control Device

"Other" combines 5 smaller categories (34 records): Person (including flagger, law enforcement, crossing guard, etc.) (19), Marked Uncontrolled Crosswalk (6), Railway Crossing Device (4), School Zone Sign/Device (3), Pedestrian Button (2).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Vehicle unit records

Vulnerable Road Users & Motorcycles

During this period, there were 156 crashes involving vulnerable road users or motorcyclists. Pedestrians were involved in 144 of these incidents, highlighting their significant risk. Bicyclists were involved in 5 crashes, and motorcyclists in 7 crashes.

Driver Contributing Action

Among driver actions cited as contributing factors, following too closely was the most common, noted in 2,738 instances. This was followed by failing to keep in the proper lane (1,836 instances) and failing to yield the right-of-way (1,016 instances). These three actions represent the most frequent driver errors leading to collisions.

Driver Contributing Action

1
No Contributing Action7,980 (46.9%)
2
Followed Too Closely2,738 (16.1%)
3
Failed to Keep in Proper Lane1,836 (10.8%)
4
Failed to Yield Right-of-Way1,016 (6%)
5
Other Contributing Action590 (3.5%)
6
Improper Backing581 (3.4%)
7
Ran Off Roadway522 (3.1%)
8
Improper Turn360 (2.1%)
9
Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner291 (1.7%)

Showing top 9 of 19 reported. 10 additional (1,086 total) not shown: Improper Passing, Ran Stop Sign, Ran Red Light, Swerved or Avoided Due to Wind, Slippery Surface, Motor Vehicle, Object, Non-Motorist in Roadway, etc., Over-Correcting/Over-Steering, 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 · 2018-01-01 to 2018-01-31 · Person-level records linked to crash events

Driver Condition

While most drivers were recorded as 'Apparently Normal,' several hundred were noted to have conditions that may have contributed to the crash. Being under the influence of medications, drugs, or alcohol was cited for 227 drivers. Additionally, 120 drivers were identified as asleep or fatigued, and 68 were noted as being emotional.

Driver Condition

1
Apparently Normal16,151 (96.7%)
2
Under the Influence of Medications/Drugs/Alcohol227 (1.4%)
3
Asleep or Fatigued120 (0.7%)
4
Emotional (depressed, angry, disturbed, etc.)68 (0.4%)
5
Other65 (0.4%)
6
Ill (sick), Fainted42 (0.3%)
7
Physically Impaired32 (0.2%)

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Person-level records linked to crash events

Pre-Crash Driver Action

The most common pre-crash action for vehicles involved was driving straight ahead, which was reported for 8,500 vehicles. A significant number of vehicles were stopped in traffic (1,983) or in the process of turning left (1,402) immediately before the collision. These actions represent the most common driving situations leading to a crash.

Pre-Crash Driver Action

1
Straight Ahead8,500 (46.2%)
2
Stopped in Traffic1,983 (10.8%)
3
Turning Left1,402 (7.6%)
4
Slowing1,329 (7.2%)
5
Parked1,179 (6.4%)
6
Negotiating a Curve879 (4.8%)
7
Backing729 (4%)
8
Turning Right708 (3.8%)
9
Changing Lanes523 (2.8%)

Showing top 9 of 16 reported. 7 additional (1,173 total) not shown: Entering Traffic Lane, Overtaking/Passing, Other, Leaving Traffic Lane, Making U-Turn, Wrong way (or Wrong Side), Overtaking/Passing Cyclist.

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Vehicle unit records

Point of Impact

The front of the vehicle was the most common point of impact, recorded in 5,460 instances (as 'Sector 12'). The second most frequent impact point was the rear of the vehicle, noted in 3,486 cases (as 'Sector 6'). This aligns with the high number of front-to-rear collisions observed in the data.

Point of Impact

"Other" combines 9 smaller categories (2,764 records): Sector 2 (NorthEast) in the 12-point Clock Diagram (645), Sector 9 (West) in the 12-point Clock Diagram (524), Sector 4 (SouthEast) in the 12-point Clock Diagram (458), Sector 3 (East) in the 12-point Clock Diagram (435), Sector 8 (SouthWest) in the 12-point Clock Diagram (433), Top (123), Non-Collision (88), Undercarriage (48), Cargo loss (10).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Vehicle unit records

Pedestrian/Cyclist Action

Of the 130 pedestrians whose actions were documented, 69 were determined to have taken no improper action. For those with contributing actions, failure to yield the right-of-way was cited for 15 pedestrians, and darting or dashing into the roadway was noted for 13. An additional 9 pedestrians were improperly in the roadway.

Pedestrian/Cyclist Action

1
No Improper Action69 (49.6%)
2
Failure to Yield Right-Of-Way15 (10.8%)
3
Dart/Dash13 (9.4%)
4
Other12 (8.6%)
5
In Roadway Improperly (Standing, Lying, Working, Playing)9 (6.5%)
6
Not Visible (Dark Clothing, No Lighting, etc.)7 (5%)
7
Failure to Obey Traffic Signs, Signals, or Officer6 (4.3%)
8
Entering/Exiting Parked/Standing Vehicle3 (2.2%)
9
Wrong-Way Riding or Walking2 (1.4%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: Inattentive (Talking, Eating, etc.), Improper Turn/Merge, Disabled Vehicle Related (Working on, Pushing, Leaving/Approaching).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Non-motorist records linked to crash events

Manner of Collision

Front-to-rear collisions were the most prevalent crash type, accounting for 3,460 incidents or 33.9% of all crashes. Angle collisions were the second most common, with 2,048 incidents (20.0%). Together, these two types of collisions represent more than half of all crashes recorded during this period.

Manner of Collision

"Other" combines 1 smaller categories (80 records): Rear to rear (80).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Person Type

Of the 24,170 people involved in crashes, the vast majority were either drivers (17,941 individuals, or 74.2%) or passengers (5,213 individuals, or 21.6%). A smaller but notable number of pedestrians (156) and bicyclists (5) were also involved in these traffic incidents.

Person Type

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Person Injury Severity

Among the 24,170 people involved in crashes, 2,871 sustained some level of injury, and 21 suffered fatal injuries. This means that approximately 11.9% of all individuals involved in a crash were injured. The majority of people, 20,537, were not injured.

Person Injury Severity

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Crash-level records

Occupant Safety Equipment

Shoulder and lap belts were the most commonly used form of safety equipment, reported for 17,181 vehicle occupants. However, 496 occupants were recorded as not using any restraint system at the time of the crash. This group represents approximately 2.5% of occupants for whom safety equipment use was documented.

Occupant Safety Equipment

"Other" combines 3 smaller categories (134 records): Booster Seat (60), Other (55), Child Restraint, Type Unknown (19).

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · Person-level records linked to crash events

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 7,440 crashes, or 72.8% of the total. Single-vehicle crashes, often involving a collision with a fixed object or running off the road, made up 21.7% of incidents (2,220 crashes). Multi-vehicle pile-ups involving three or more vehicles were less common, representing about 5.5% of all crashes.

Vehicles Per Crash

Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-01-31 · 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: 2018-01-01 through 2018-01-31
  • Report generated: August 20, 2026

Data Coverage

  • Reporting period: 2018-01-01 through 2018-01-31 (31 days)
  • Geographic scope: connecticut, CT
  • Total crash records analyzed: 10,215
  • Total persons involved: 24,170
  • Total vehicles involved: 18,859

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: January 2018." Published August 20, 2026. Reporting period: 2018-01-01 to 2018-01-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/january-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

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