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An Injuria.ai Company
CRASH INTELLIGENCE REPORT · CONNECTICUT, CT · DECEMBER 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/december-2018-report
Monthly Traffic Safety Analysis
9,976 CRASHES IN
CONNECTICUT, CT
DECEMBER 2018
In December 2018, Connecticut recorded 9,976 motor vehicle crashes, resulting in 23 fatalities and 3,226 injuries. A significant portion of these incidents were rear-end collisions, which corresponds with the most frequently cited contributing driver action being 'Followed Too Closely,' attributed to 2,876 drivers. These statistics highlight common patterns in traffic incidents across the state during this period.
9,976
Total Crash Events
23
Persons Killed
3,226
Persons Injured
11.3%
Hit-and-Run Rate
Note: "Persons Killed" (23) 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 · 2018-12-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records
1,129
Hit-and-Run Crashes — December 2018
There were 1,129 crashes classified as hit-and-run incidents, accounting for 11.3% of all crashes during this period. This determination is based on the responding officer's assessment at the scene of the crash. The data reflects incidents where at least one driver involved left the scene without providing required information.
Vulnerable Road User Casualties
Motor vehicle occupants constituted the largest group of casualties, with 18 motorists killed and 3,067 injured. Pedestrians were also a significant group, with 5 individuals killed and 149 injured in collisions. While no bicyclists were killed, 10 sustained injuries during this period.
5
Pedestrians Killed
0
Cyclists Killed
18
Motorists Killed
149
Pedestrians Injured
10
Cyclists Injured
3,067
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crash frequency peaked on Friday with 1,697 incidents, and the most common time for a crash was the 5 p.m. hour, which saw 1,137 events, indicating a strong correlation with the evening commute. Crashes were split between daytime and nighttime, with 5,164 incidents occurring in daylight and 4,709 happening in dark, dusk, or dawn conditions.
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The majority of crashes, 7,613 incidents or 76.3%, resulted in no injuries. Injury-related crashes accounted for 23.7% of the total, encompassing serious, minor, and possible injuries. There were 21 distinct fatal crashes, which led to a total of 23 fatalities, as a single crash can result in more than one death.
Severity is per crash event (most severe injury). 21 fatal crash events resulted in 23 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Most severe injury per crash record
Road & Environmental Conditions
A substantial majority of crashes occurred in favorable conditions, with 76.5% of incidents happening in clear weather and 74.9% on dry road surfaces. Over half of all crashes (51.8%) took place in daylight. Nevertheless, adverse conditions were a factor in many incidents, as 1,612 crashes occurred during rain and 2,266 took place on wet roads.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Road surface condition field
Vehicles & Demographics
Among the vehicles involved in crashes, the most frequent makes were Honda (2,036), Toyota (1,849), and Ford (1,703). Analyzing the demographics of all persons involved, the 26-34 age group was the most represented, with 4,100 individuals. The next most common age groups were 35-44 (3,543 people) and 45-54 (3,295 people).
Top Vehicle Makes (18,817 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Vehicle unit records
1,550 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (22,890 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Person-level records linked to crash events
Speed Limit Zones
Roads with a posted speed limit of 25 mph had the highest number of crashes, with 2,892 incidents. While lower-speed zones saw more crashes, the percentage of crashes that were fatal was higher in faster zones. For example, 0.691% of crashes in 40 mph zones and 0.586% in 65 mph zones were fatal, compared to just 0.069% in 25 mph zones.
Fatal crashes by zone: 25 mph: 2 of 2,892 (0.069%) · 30 mph: 4 of 854 (0.468%) · 35 mph: 3 of 1,208 (0.248%) · 40 mph: 4 of 579 (0.691%) · 45 mph: 1 of 390 (0.256%) · 50 mph: 1 of 249 (0.402%) · 55 mph: 2 of 948 (0.211%) · 65 mph: 3 of 512 (0.586%)
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Posted speed limit at crash location
Top Counties
Crash incidents were geographically concentrated, with three counties accounting for over 83% of the statewide total. Fairfield County reported the highest number with 2,964 crashes (29.7% of total), followed by New Haven County with 2,816 crashes (28.2%), and Hartford County with 2,530 crashes (25.4%).
Top Counties
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Top Towns
The state's most populous cities experienced the highest number of traffic crashes. New Haven led with 613 incidents, followed very closely by Hartford with 608 crashes. Other cities with high volumes included Bridgeport (513 crashes), Waterbury (509 crashes), and Stamford (418 crashes).
Top Towns
Showing top 9 of 50 reported. 41 additional (4,269 total) not shown: Fairfield, Hamden, West Hartford, Stratford, New Britain, Greenwich, West Haven, North Haven, Milford, Middletown, Bristol, Trumbull, Southington, East Hartford, Westport, Wallingford, Norwich, Shelton, Windsor, Wethersfield, Orange, Torrington, Newtown, Newington, Berlin, Vernon, Farmington, Groton, New London, Bloomfield, Branford, Cheshire, Enfield, Naugatuck, Darien, East Haven, Rocky Hill, Waterford, Glastonbury, Plainville, Cromwell.
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Road Class
Arterial roadways were the site of the most crashes, with 2,682 on Minor Arterials and 2,220 on Principal Arterials. Limited-access highways, including Interstates and other Freeways or Expressways, collectively accounted for 2,222 crashes. This represents 23.6% of crashes where the road classification was known.
Road Class
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Route System
Of the crashes with a known route system, 58.9% (5,603 incidents) occurred on state-maintained roadways, including State, Interstate, and US Routes. The remaining 41.1% of crashes (3,911 incidents) took place on local roads. This distinction is relevant for determining roadway ownership and maintenance responsibility.
Route System
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Public vs Private Road
The vast majority of collisions, 9,368 incidents, occurred on public roads. A smaller but distinct category of 432 crashes, representing 4.4% of the classified total, happened on private property. These incidents include crashes in commercial parking lots, private driveways, and other non-public areas.
Rural vs Urban
The data shows a strong urban concentration for crashes, with 9,077 incidents occurring in urban areas. In contrast, 343 crashes were recorded in rural settings. This means that crashes in rural areas accounted for just 3.6% of the total where the geographic context was identified.
Rural vs Urban
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Junction Type
A majority of crashes, 6,667 incidents, did not occur at an intersection. However, intersections were the location for 3,284 crashes, or 33.0% of the total. The most common crash locations among junctions were four-way intersections (1,643 crashes) and T-intersections (1,419 crashes).
Junction Type
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Run-off-Road / Fixed-Object Strikes
In crashes where the first harmful event was striking a fixed object, the most common objects hit were guardrail faces (236 incidents) and other fixed objects like walls or buildings (220 incidents). Collisions with poles and trees were also frequent, with utility poles struck 176 times and trees 108 times.
Run-off-Road / Fixed-Object Strikes
Showing top 9 of 22 reported. 13 additional (238 total) not shown: Embankment, Cable Barrier, Fence, Ditch, Guardrail End, Other Traffic Barrier, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Bridge Overhead Structure, Impact Attenuator/Crash Cushion, Bridge Rail, Traffic Signal Support, Culvert, Bridge Pier or Support.
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Vehicle Type
Passenger cars were the most prevalent vehicle type in collisions, with 11,160 involved, followed by 4,332 (Sport) Utility Vehicles. Medium and heavy trucks, a category with higher liability, were involved in 389 incidents, making up 2.1% of all vehicles. Additionally, 189 buses and 24 motorcycles were involved in crashes.
Vehicle Type
Showing top 9 of 16 reported. 7 additional (124 total) not shown: Transit Bus, Other Bus, Motorcycle, Moped, Motor Coach, Motor Home, All Terrain Vehicle (ATV).
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Vehicle unit records
Traffic Control Device
Analysis of traffic controls at crash sites shows that a majority of vehicles, 12,404, were involved in crashes where no control device was present. For crashes at controlled locations, traffic signals were the most common device, present for 4,557 vehicles involved in collisions. Stop signs were present for another 1,475 vehicles.
Traffic Control Device
"Other" combines 3 smaller categories (35 records): Person (including flagger, law enforcement, crossing guard, etc.) (20), Marked Uncontrolled Crosswalk (13), School Zone Sign/Device (2).
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Vehicle unit records
Vulnerable Road Users & Motorcycles
Among incidents specifically involving vulnerable road users and motorcyclists, pedestrians were the most frequent group, with 159 crashes. When combined with the 17 crashes involving bicyclists, these vulnerable road users accounted for 176 incidents, or 88.4% of this specific crash subset. Motorcyclists were involved in 23 crashes.
Driver Contributing Action
The most common contributing factor attributed to drivers was 'Followed Too Closely,' cited in 2,876 instances. This was followed by 'Failed to Keep in Proper Lane' for 1,834 drivers and 'Failed to Yield Right-of-Way' for 1,089 drivers. These actions represent the top driver errors identified in the crash data.
Driver Contributing Action
Showing top 9 of 19 reported. 10 additional (957 total) not shown: Ran Stop Sign, Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner, 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 · 2018-12-01 to 2018-12-31 · Person-level records linked to crash events
Driver Condition
While most drivers were listed as 'Apparently Normal,' several adverse conditions were recorded. A total of 270 drivers were identified as being under the influence of medications, drugs, or alcohol. Driver fatigue was also a factor, with 127 drivers reported as asleep or fatigued at the time of the crash.
Driver Condition
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Person-level records linked to crash events
Pre-Crash Driver Action
The most common action of vehicles immediately prior to a collision was 'Straight Ahead,' which was reported for 8,440 vehicles, or 44.8% of the total. The next most frequent pre-crash movements were vehicles being 'Stopped in Traffic' (2,065 vehicles) and vehicles 'Turning Left' (1,552 vehicles).
Pre-Crash Driver Action
Showing top 9 of 16 reported. 7 additional (1,154 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 · 2018-12-01 to 2018-12-31 · Vehicle unit records
Point of Impact
Frontal impacts were the most common, with 5,415 vehicles (28.8%) struck in the front ('Sector 12'). Rear impacts were the second most frequent point of contact, affecting 3,679 vehicles ('Sector 6'). This data aligns with the high prevalence of front-to-rear collisions reported.
Point of Impact
"Other" combines 9 smaller categories (2,736 records): Sector 5 (South by SouthEast) in the 12-point Clock Diagram (631), Sector 8 (SouthWest) in the 12-point Clock Diagram (511), Sector 9 (West) in the 12-point Clock Diagram (485), Sector 3 (East) in the 12-point Clock Diagram (452), Sector 4 (SouthEast) in the 12-point Clock Diagram (437), Non-Collision (93), Top (82), Undercarriage (35), Cargo loss (10).
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Vehicle unit records
Pedestrian/Cyclist Action
In crashes involving pedestrians, 78 individuals were determined to have been acting properly with no contributing action. Among cases where a pedestrian action was cited, the most common were 'In Roadway Improperly' and 'Failure to Yield Right-Of-Way,' each cited for 18 pedestrians. An additional 13 pedestrians were reported to have darted into the road.
Pedestrian/Cyclist Action
Showing top 9 of 13 reported. 4 additional (5 total) not shown: Entering/Exiting Parked/Standing Vehicle, Improper Turn/Merge, Use of Electronic Device, Inattentive (Talking, Eating, etc.).
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Non-motorist records linked to crash events
Manner of Collision
Front-to-rear collisions were the most common crash type, accounting for 3,609 incidents, or 36.2% of all crashes. Angle collisions were the second most frequent type, with 1,973 incidents (19.8% of the total). Sideswipes in the same direction of travel were the third most common, occurring 1,381 times.
Manner of Collision
"Other" combines 1 smaller categories (75 records): Rear to rear (75).
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Person Type
Of the 24,409 individuals involved in crashes, the majority were drivers (17,923 people). Passengers made up the second-largest group, with 5,456 individuals. The data also captured non-occupants, including 170 pedestrians and 17 bicyclists who were involved in traffic collisions.
Person Type
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Person Injury Severity
Among all 24,409 people involved in crashes, 83.7% (20,428) were not injured. A total of 3,226 people sustained some level of injury, ranging from possible to serious. The incidents during this period resulted in 23 fatalities, which is 0.09% of all persons involved.
Person Injury Severity
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Crash-level records
Occupant Safety Equipment
The data on safety equipment use shows that 16,483 motor vehicle occupants were using both a shoulder and lap belt. In contrast, 447 occupants were recorded as using no restraint system at all. Additionally, child safety restraints were used for 637 children, including 419 in forward-facing seats.
Occupant Safety Equipment
"Other" combines 3 smaller categories (156 records): Other (68), Booster Seat (60), Child Restraint, Type Unknown (28).
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · Person-level records linked to crash events
Vehicles Per Crash
Two-vehicle crashes were the most common type of incident, accounting for 7,484 cases, or 75.0% of all crashes. Single-vehicle crashes, which often involve running off the road or striking an object, occurred 1,866 times (18.7% of the total). Multi-vehicle pile-ups were less common, with 550 crashes involving three vehicles.
Vehicles Per Crash
Source: Connecticut Crash Data · Csv Open Data · 2018-12-01 to 2018-12-31 · 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: 2018-12-01 through 2018-12-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2018-12-01 through 2018-12-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,976
- Total persons involved: 24,409
- Total vehicles involved: 18,817
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: December 2018." Published August 20, 2026. Reporting period: 2018-12-01 to 2018-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/december-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: 2018-12-01 – 2018-12-31
Generated: August 20, 2026 · All rights reserved
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