If you're a data point in this report, call us.
We'll evaluate whether you have a case. Free, and no pressure.
ThatCarHitMe.com
An Injuria.ai Company
CRASH INTELLIGENCE REPORT · CONNECTICUT, CT · 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/2018-annual-report
Yearly Traffic Safety Analysis
33,653 CRASHES IN
CONNECTICUT, CT
2018
In 2018, Fairfield County recorded 33,653 motor vehicle crashes, resulting in 47 fatalities and 9,892 injuries. These incidents involved 82,397 people and 65,017 vehicles. A notable characteristic of these crashes is the prevalence of rear-end collisions, with front-to-rear impacts accounting for 37.7% of all incidents where the manner of collision was recorded.
33,653
Total Crash Events
47
Persons Killed
9,892
Persons Injured
10.5%
Hit-and-Run Rate
Note: "Persons Killed" (47) counts individual fatalities across all crash events. "Fatal" in the severity table below (44) 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 2018-12-31 · Aggregate counts from crash, person, and vehicle records
3,526
Hit-and-Run Crashes — 2018
Based on the initial determination of responding officers, 3,526 crashes involved a hit-and-run. This represents 10.5% of all reported traffic crashes in the county for the period.
Vulnerable Road User Casualties
Of the 47 total fatalities, 32 were motorists, and 15 were pedestrians; no cyclists were killed. Among the 9,892 people injured, the vast majority were motorists (9,412), while 403 pedestrians and 77 cyclists sustained injuries. These figures highlight that while motorists account for the largest number of casualties, pedestrians represent a significant portion of fatalities.
15
Pedestrians Killed
0
Cyclists Killed
32
Motorists Killed
403
Pedestrians Injured
77
Cyclists Injured
9,412
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crash frequencies peaked during the work week, with Friday being the most common day for incidents, recording 5,616 crashes. The evening commute was the most hazardous time of day, with a peak of 2,980 crashes occurring during the 5 p.m. hour. Overall, 70.1% of crashes occurred during daylight hours.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The vast majority of crashes, 78.6% or 26,447 incidents, resulted in no reported injuries. Crashes involving some level of injury accounted for 21.3% of the total. A total of 44 crashes were classified as fatal, which resulted in 47 individual fatalities, indicating some crashes involved more than one death.
Severity is per crash event (most severe injury). 44 fatal crash events resulted in 47 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The majority of crashes occurred in ideal driving conditions, with 77.7% happening in clear weather and 77.6% on dry road surfaces. Over 70% of all incidents took place in daylight. Adverse conditions were less frequent, with 3,946 crashes occurring during rain and 5,867 on wet roadways.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Road surface condition field
Vehicles & Demographics
Among all persons involved in crashes, the 26-34 age group was the most represented, with 13,707 individuals. Analysis of the 65,017 vehicles involved shows that Honda, Toyota, and Ford were the most frequent makes, with 7,226, 6,748, and 5,844 vehicles respectively.
Top Vehicle Makes (65,017 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
5,435 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (77,663 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events
Speed Limit Zones
The most crashes, 11,716 or 34.8% of the total, occurred in zones with a posted speed limit of 25 mph. Within this speed zone, 0.12% of crashes were fatal. While lower speed zones saw more total crashes, the rate of fatal crashes within a zone was sometimes higher at increased speeds; for instance, 0.69% of crashes in 45 mph zones were fatal.
Fatal crashes by zone: 1 mph: 2 of 6,273 (0.032%) · 25 mph: 14 of 11,716 (0.119%) · 30 mph: 7 of 2,485 (0.282%) · 35 mph: 3 of 2,493 (0.12%) · 40 mph: 2 of 1,256 (0.159%) · 45 mph: 2 of 291 (0.687%) · 55 mph: 12 of 5,241 (0.229%) · 65 mph: 1 of 337 (0.297%) · 88 mph: 1 of 2,474 (0.04%)
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Posted speed limit at crash location
Top Towns
The geographic distribution of crashes is concentrated in the county's urban centers. The city of Bridgeport accounted for the largest share with 6,276 incidents, or 18.6% of the county total. Stamford followed with 5,169 crashes (15.4%), and Norwalk had 3,749 crashes (11.1%). Together, these three cities represented 45.1% of all crashes in Fairfield County.
Top Towns
Showing top 9 of 23 reported. 14 additional (6,104 total) not shown: Newtown, Shelton, Darien, Ridgefield, New Canaan, Bethel, Wilton, Brookfield, Monroe, Redding, Easton, New Fairfield, Weston, Sherman.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Road Class
Minor Arterial roads saw the highest number of crashes, with 8,827 incidents. Roadways classified as Principal Arterials were next with 6,607 crashes. Combined, limited-access highways, including Interstates (4,231) and Freeways/Expressways (3,018), accounted for 7,249 crashes, or approximately 21.5% of the total.
Road Class
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Route System
Analysis by route system shows a split between state-maintained and local roadways. Crashes on state-maintained routes, including Interstate, US Route, and State routes, totaled 16,882. This compares to 14,159 crashes that occurred on local roads.
Route System
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Public vs Private Road
Of the crashes where roadway ownership was documented, the vast majority (30,800) occurred on public roads. A total of 1,949 crashes, representing approximately 6.0% of this subset, took place on private property such as parking lots or private drives.
Rural vs Urban
The overwhelming majority of crashes occurred in urban settings, with 30,195 incidents classified as urban. In contrast, 486 crashes, or about 1.6% of those with a defined location type, were recorded in rural areas.
Rural vs Urban
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Junction Type
The most common crash location was not at an intersection, accounting for 22,594 incidents. However, a significant number of crashes, 10,854 or 32.4% of those with junction data, occurred at or were related to an intersection. The most frequent intersection types involved were T-intersections (5,043) and four-way intersections (4,982).
Junction Type
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Run-off-Road / Fixed-Object Strikes
Among crashes involving a collision with a fixed object, the most frequently struck item was categorized as 'Other Fixed Object' (737), followed by guardrail faces (490) and utility poles or light supports (479). Combined, collisions with utility poles (479) and trees (366) accounted for 845 incidents of this type.
Run-off-Road / Fixed-Object Strikes
Showing top 9 of 22 reported. 13 additional (662 total) not shown: Fence, Traffic Sign Support, Bridge Overhead Structure, Other Traffic Barrier, Guardrail End, Cable Barrier, Ditch, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Impact Attenuator/Crash Cushion, Bridge Rail, Bridge Pier or Support, Traffic Signal Support, Culvert.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Vehicle Type
Passenger cars were the most common vehicle type involved in crashes, accounting for 37,238 vehicles, followed by Sport Utility Vehicles at 15,839. Medium and heavy trucks were involved in 1,672 incidents, while motorcycles were involved in 251 crashes.
Vehicle Type
Showing top 9 of 18 reported. 9 additional (610 total) not shown: Motorcycle, Transit Bus, Other Bus, Moped, Low Speed Vehicle, Motor Coach, Motor Home, All Terrain Vehicle (ATV), Golf Cart.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
Vulnerable Road Users & Motorcycles
In crashes involving pedestrians, bicyclists, or motorcyclists, pedestrians were the most frequent group, with 442 incidents. There were 248 crashes involving motorcyclists and 94 involving bicyclists. Combined, pedestrians and bicyclists were involved in 536 crashes, representing 68.4% of these specific incident types.
Driver Contributing Action
Among contributing actions cited for drivers, 'Followed Too Closely' was the most common, noted for 10,166 drivers. This was followed by 'Failed to Keep in Proper Lane' with 5,478 instances and 'Failed to Yield Right-of-Way' with 3,568 instances.
Driver Contributing Action
Showing top 9 of 19 reported. 10 additional (3,027 total) not shown: Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner, 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, Disregarded Other Traffic Sign, Over-Correcting/Over-Steering, Wrong Side or Wrong Way, Disregarded Other Road Markings, Overtaking Cyclist.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events
Driver Condition
While most drivers were recorded as 'Apparently Normal,' several other conditions were noted. A total of 577 drivers were determined to be under the influence of medications, drugs, or alcohol. Additionally, 378 drivers were identified as asleep or fatigued, and 216 were noted as being in an emotional state.
Driver Condition
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events
Pre-Crash Driver Action
The most common pre-crash action for vehicles involved was 'Straight Ahead,' recorded for 28,266 vehicles. The next most frequent actions were 'Stopped in Traffic' (7,455 vehicles) and 'Slowing' (5,166 vehicles).
Pre-Crash Driver Action
Showing top 9 of 17 reported. 8 additional (3,702 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 · 2018-01-01 to 2018-12-31 · Vehicle unit records
Point of Impact
The front of the vehicle was the most common point of impact, recorded as 'Sector 12 (North)' for 17,660 vehicles, representing 27.2% of all vehicles with impact data. The rear of the vehicle, 'Sector 6 (South)', was the second most common impact point, involved in 13,555 collisions.
Point of Impact
"Other" combines 9 smaller categories (9,868 records): Sector 2 (NorthEast) in the 12-point Clock Diagram (2,376), Sector 8 (SouthWest) in the 12-point Clock Diagram (1,821), Sector 9 (West) in the 12-point Clock Diagram (1,773), Sector 4 (SouthEast) in the 12-point Clock Diagram (1,683), Sector 3 (East) in the 12-point Clock Diagram (1,527), Non-Collision (314), Top (254), Undercarriage (93), Cargo loss (27).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
Pedestrian/Cyclist Action
Among pedestrians involved in crashes where an action was recorded, 57 were cited for 'Failure to Yield Right-Of-Way'. Other noted actions included 'In Roadway Improperly' (41 pedestrians) and 'Dart/Dash' (30 pedestrians). A large portion, 245 pedestrians, were recorded as having taken no improper action.
Pedestrian/Cyclist Action
Showing top 9 of 14 reported. 5 additional (18 total) not shown: Improper Turn/Merge, Disabled Vehicle Related (Working on, Pushing, Leaving/Approaching), Wrong-Way Riding or Walking, Use of Electronic Device, Improper Passing.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Non-motorist records linked to crash events
Manner of Collision
Rear-end collisions were the most prevalent type of crash, with 'Front to rear' impacts accounting for 12,680 incidents, or 37.7% of all multi-vehicle collisions. Angle collisions were the second most common type, representing 19.9% of crashes with 6,710 occurrences.
Manner of Collision
"Other" combines 1 smaller categories (420 records): Rear to rear (420).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Person Type
Of the 82,397 individuals involved in crashes, the majority (61,090 or 74.1%) were drivers. Passengers constituted the next largest group with 18,350 individuals. The data also includes 461 pedestrians and 94 bicyclists.
Person Type
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Person Injury Severity
Out of 82,397 people involved in crashes, 9,892 individuals, or 12.0%, sustained some level of injury. A total of 47 people suffered fatal injuries, accounting for approximately 0.06% of all persons involved. The majority of individuals, 70,179 people, were not injured.
Person Injury Severity
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Occupant Safety Equipment
Among vehicle occupants where safety equipment use was recorded, the majority utilized some form of restraint. However, 1,053 occupants were noted as having used no restraint system at the time of the crash.
Occupant Safety Equipment
"Other" combines 3 smaller categories (396 records): Other (210), Booster Seat (137), Child Restraint, Type Unknown (49).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events
Vehicles Per Crash
The majority of incidents were two-vehicle crashes, accounting for 26,453, or 78.6% of the total. Single-vehicle crashes were the next most common, with 4,992 incidents, representing 14.8% of all crashes. The data includes multi-vehicle pile-ups, with one crash involving as many as 8 vehicles.
Vehicles Per Crash
"Other" combines 2 smaller categories (3 records): 7 (2), 8 (1).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 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: 2018-01-01 through 2018-12-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2018-01-01 through 2018-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 33,653
- Total persons involved: 82,397
- Total vehicles involved: 65,017
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: 2018." Published August 20, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2018-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Connecticut Crash Data · Csv
Period: 2018-01-01 – 2018-12-31
Generated: August 20, 2026 · All rights reserved
The data is step one. Get a Connecticut attorney on the line.
Call our intake team. We connect you to a vetted Connecticut personal injury attorney who calls you back within minutes. No phone tag. No voicemails.
Always free for accident victims.