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CRASH INTELLIGENCE REPORT · CONNECTICUT, CT · SEPTEMBER 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/september-2018-report
Monthly Traffic Safety Analysis
9,063 CRASHES IN
CONNECTICUT, CT
SEPTEMBER 2018
In September 2018, Connecticut recorded 9,063 motor vehicle crashes, resulting in 23 fatalities and 3,119 injuries. Analysis of the data reveals a high geographic concentration of incidents, with Fairfield, New Haven, and Hartford counties collectively accounting for over 83% of all crashes statewide. The most common collision type was front-to-rear, comprising 37.8% of all incidents.
9,063
Total Crash Events
23
Persons Killed
3,119
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 (23) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Aggregate counts from crash, person, and vehicle records
1,028
Hit-and-Run Crashes — September 2018
Based on the responding officer's initial determination, 1,028 crashes in September 2018 were classified as hit-and-run incidents. This represents 11.3% of all crashes during the period. This classification is subject to change as investigations proceed.
Vulnerable Road User Casualties
Motor vehicle occupants represented the largest group of casualties, with 18 motorists killed and 2,973 injured. Among vulnerable road users, there were 4 pedestrian fatalities and 106 pedestrian injuries recorded. Additionally, 1 cyclist was killed and 40 were injured in crashes during this period.
4
Pedestrians Killed
1
Cyclists Killed
18
Motorists Killed
106
Pedestrians Injured
40
Cyclists Injured
2,973
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Crash patterns show a distinct peak during weekday afternoons. The most frequent day for crashes was Tuesday with 1,488 incidents, and the single busiest hour was the 3 p.m. hour with 781 crashes. Overall, crashes were most common during the afternoon commute period between 3 p.m. and 5 p.m., which saw a combined total of 2,291 incidents.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Of the 9,063 crashes reported, the majority (74.2%) resulted in no injuries. Injury-involved crashes, encompassing serious, minor, and possible injuries, accounted for 25.5% of all incidents. There were 23 fatal crashes, representing 0.3% of the total, which resulted in 23 fatalities.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Most severe injury per crash record
Road & Environmental Conditions
The majority of crashes occurred in favorable conditions, with 72.1% happening in clear weather and 75.5% on dry road surfaces. Daylight conditions were present for 75.1% of all incidents. Among adverse conditions, rain was a factor in 1,676 crashes, and wet roads were reported in 2,127 incidents.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Road surface condition field
Vehicles & Demographics
Analysis of persons involved in crashes shows the 26-34 age group was the most represented, with 3,863 individuals. Among the 17,186 vehicles involved, the most frequent makes were Honda (1,996), Toyota (1,800), and Ford (1,515). These counts include variations in make names recorded in the data.
Top Vehicle Makes (17,186 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Vehicle unit records
1,483 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21,048 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Person-level records linked to crash events
Speed Limit Zones
The most crashes, 2,787 incidents or 30.7% of the total, occurred in zones with a posted speed limit of 25 mph. While lower speed zones saw more crashes, the percentage of fatal crashes within a given zone tended to increase with the speed limit. For instance, 0.215% of crashes in 25 mph zones were fatal, compared to a high of 0.94% in 45 mph zones.
Fatal crashes by zone: 1 mph: 1 of 1,072 (0.093%) · 25 mph: 6 of 2,787 (0.215%) · 30 mph: 4 of 704 (0.568%) · 35 mph: 2 of 1,003 (0.199%) · 40 mph: 3 of 497 (0.604%) · 45 mph: 3 of 319 (0.94%) · 55 mph: 2 of 884 (0.226%) · 65 mph: 1 of 460 (0.217%) · 88 mph: 1 of 567 (0.176%)
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Posted speed limit at crash location
Top Counties
Crash distribution across Connecticut shows a heavy concentration in three counties. Fairfield County had the highest volume with 2,681 crashes (29.6% of the state total), followed by New Haven County with 2,470 crashes (27.2%) and Hartford County with 2,391 crashes (26.4%). These three counties alone accounted for over 83% of all crashes statewide.
Top Counties
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Top Towns
Among Connecticut's municipalities, the highest crash volumes were recorded in the state's largest urban centers. Hartford led with 584 crashes, representing 6.4% of the statewide total. New Haven followed with 560 crashes (6.2%), and Bridgeport recorded 542 crashes (6.0%).
Top Towns
Showing top 9 of 50 reported. 41 additional (3,797 total) not shown: Fairfield, Stratford, Manchester, West Haven, Hamden, Greenwich, New Britain, Bristol, Milford, East Hartford, Middletown, Norwich, Wallingford, Westport, North Haven, Southington, Windsor, Trumbull, Wethersfield, New London, Orange, Farmington, Newington, Shelton, Torrington, Enfield, Berlin, Newtown, Darien, Waterford, Bloomfield, Plainville, Groton, Branford, Watertown, Mansfield, Rocky Hill, New Milford, East Haven, Vernon, Guilford.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Road Class
Analysis by roadway functional class shows that Minor Arterials were the site of the most crashes, with 2,392 incidents, followed by Principal Arterials with 1,952 crashes. Combined, limited-access highways such as Interstates and Freeways/Expressways accounted for 2,029 crashes, or approximately 23.8% of crashes where the road class was identified.
Road Class
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Route System
Crashes were split between state-maintained and local roadways. State-maintained routes, including State, Interstate, and US Routes, accounted for 4,978 incidents. This represents 57.9% of crashes where the route system was known, while local roads were the location for the remaining 3,615 crashes (42.1%).
Route System
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Public vs Private Road
Of the crashes where roadway ownership was recorded, the vast majority occurred on public roads (8,536 incidents). A smaller number, 349 crashes, took place on private property such as parking lots or private drives. This accounts for 3.9% of crashes with known ownership.
Rural vs Urban
The data indicates a significant majority of crashes occurred in urban areas, totaling 8,163 incidents. Crashes in designated rural areas accounted for 351 incidents. This represents 4.1% of the total where the geographic context was specified.
Rural vs Urban
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Junction Type
A majority of crashes, 6,076 incidents, occurred at locations not classified as intersections. The remaining 2,966 crashes happened at or were related to a junction. Among these, four-way intersections were the most common site with 1,520 crashes, followed by T-intersections with 1,273 crashes.
Junction Type
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Run-off-Road / Fixed-Object Strikes
Among crashes where the first harmful event was striking a fixed object, the most frequently hit object was a guardrail face, involved in 252 incidents. This was followed by other fixed objects like walls or buildings (188), utility poles or light supports (145), and curbs (111). Collisions with utility poles and trees combined accounted for 244 of these run-off-road crashes.
Run-off-Road / Fixed-Object Strikes
Showing top 9 of 22 reported. 13 additional (243 total) not shown: Embankment, Cable Barrier, Fence, Ditch, Other Traffic Barrier, Bridge Overhead Structure, Guardrail End, Traffic Signal Support, Bridge Pier or Support, Bridge Rail, Impact Attenuator/Crash Cushion, Culvert, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Vehicle Type
Passenger cars were the most common vehicle type involved in crashes, accounting for 10,066 vehicles, followed by Sport Utility Vehicles with 3,703. Medium or heavy trucks were involved in 400 incidents, representing 2.3% of all vehicles. Motorcycles were involved in 156 crashes, and various types of buses were involved in 175.
Vehicle Type
Showing top 9 of 17 reported. 8 additional (220 total) not shown: School Bus, Transit Bus, Moped, Other Bus, Low Speed Vehicle, All Terrain Vehicle (ATV), Motor Coach, Motor Home.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Vehicle unit records
Traffic Control Device
Data on traffic controls present at crash locations shows that a majority of vehicles, 11,391 or 66.3%, were involved in crashes where no traffic control device was present. Locations with a traffic signal accounted for 4,110 vehicles (23.9% of the total). An additional 1,293 vehicles were involved in crashes at locations controlled by a stop sign.
Traffic Control Device
"Other" combines 6 smaller categories (44 records): Warning Sign (16), School Zone Sign/Device (10), Railway Crossing Device (8), Marked Uncontrolled Crosswalk (8), Bicycle Detection (1), Pedestrian Button (1).
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Vehicle unit records
Vulnerable Road Users & Motorcycles
In crashes involving vulnerable road users or motorcyclists, motorcyclists were the largest group with 152 incidents. Pedestrians were involved in 118 crashes and bicyclists in 46. Combined, pedestrians and bicyclists accounted for 164 crashes, representing 51.9% of these specific incident types.
Driver Contributing Action
Among drivers for whom a contributing action was cited, 'Followed Too Closely' was the most common factor, attributed to 2,747 drivers (16.9% of all drivers). 'Failed to Keep in Proper Lane' was the second most frequent action, noted for 1,673 drivers (10.3%). Other common actions included 'Failed to Yield Right-of-Way' (955 drivers) and 'Improper Backing' (501 drivers).
Driver Contributing Action
Showing top 9 of 19 reported. 10 additional (898 total) not shown: Improper Passing, 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, Disregarded Other Traffic Sign, Wrong Side or Wrong Way, Disregarded Other Road Markings, Overtaking Cyclist.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Person-level records linked to crash events
Driver Condition
Beyond drivers noted as 'Apparently Normal,' the most cited condition was driving 'Under the Influence of Medications/Drugs/Alcohol,' reported for 227 drivers, or 1.4% of all drivers. Driver fatigue was also a factor, with 115 drivers identified as 'Asleep or Fatigued.' Additionally, 70 drivers were noted as being in an emotional state, such as angry or disturbed.
Driver Condition
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Person-level records linked to crash events
Pre-Crash Driver Action
The most common pre-crash action for vehicles was 'Straight Ahead,' recorded for 7,636 vehicles, or 44.4% of the total. The second most frequent situation was being 'Stopped in Traffic,' which applied to 2,014 vehicles (11.7%). Other notable pre-crash movements included 'Turning Left' (1,310 vehicles) and 'Slowing' (1,241 vehicles).
Pre-Crash Driver Action
Showing top 9 of 17 reported. 8 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, Traveling in Bike Lane.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Vehicle unit records
Point of Impact
The most frequent point of impact was the front of the vehicle, described as 'Sector 12 (North),' which was recorded for 4,883 vehicles, or 28.4% of all vehicles involved. The second most common impact point was the rear ('Sector 6 (South)'), accounting for 3,509 vehicles (20.4%). These two impact types are consistent with the prevalence of front-to-rear collisions.
Point of Impact
"Other" combines 9 smaller categories (2,682 records): Sector 5 (South by SouthEast) in the 12-point Clock Diagram (578), Sector 9 (West) in the 12-point Clock Diagram (502), Sector 8 (SouthWest) in the 12-point Clock Diagram (482), Sector 3 (East) in the 12-point Clock Diagram (442), Sector 4 (SouthEast) in the 12-point Clock Diagram (416), Top (123), Non-Collision (97), Undercarriage (32), Cargo loss (10).
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Vehicle unit records
Pedestrian/Cyclist Action
For the 148 pedestrians involved in crashes, the most common recorded action was 'No Improper Action,' attributed to 60 individuals. Among improper actions cited, 'Failure to Yield Right-Of-Way' was the most frequent, with 23 cases. This was followed by 'In Roadway Improperly' (16 cases) and 'Dart/Dash' (15 cases).
Pedestrian/Cyclist Action
Showing top 9 of 12 reported. 3 additional (5 total) not shown: Entering/Exiting Parked/Standing Vehicle, Inattentive (Talking, Eating, etc.), Improper Passing.
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Non-motorist records linked to crash events
Manner of Collision
The most common type of crash was a 'Front to rear' collision, which accounted for 3,422 incidents, or 37.8% of all crashes with a known collision manner. The second most frequent type was an 'Angle' collision, with 1,747 incidents (19.3%). Sideswipes in the same direction were also common, representing 13.7% of crashes.
Manner of Collision
"Other" combines 1 smaller categories (74 records): Rear to rear (74).
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Person Type
Of the 22,434 people involved in crashes, the vast majority were drivers, accounting for 16,253 individuals (72.5%). Passengers made up the next largest group with 5,086 individuals (22.7%). Vulnerable road users, including 148 pedestrians and 48 bicyclists, constituted approximately 0.9% of all persons involved.
Person Type
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Person Injury Severity
Among all 22,434 individuals involved in crashes, a total of 3,142 people sustained some level of injury, representing 14.0% of all participants. This includes 103 serious injuries, 1,199 minor injuries, and 1,817 possible injuries. Fatal injuries were recorded for 23 individuals, accounting for 0.1% of all persons involved.
Person Injury Severity
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Crash-level records
Occupant Safety Equipment
The data shows that 'Shoulder and Lap Belt Used' was the most common restraint status, reported for 15,703 vehicle occupants. Among occupants where restraint use was specified, 416 individuals were recorded as using no restraint system. This represents 2.3% of occupants with known safety equipment status.
Occupant Safety Equipment
"Other" combines 3 smaller categories (161 records): Other (73), Child Restraint, Type Unknown (50), Booster Seat (38).
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · Person-level records linked to crash events
Vehicles Per Crash
The vast majority of crashes, 6,884 incidents or 75.9% of the total, involved two vehicles. Single-vehicle crashes accounted for 1,625 incidents, representing 17.9% of the total. Crashes involving three or more vehicles were less common, with one incident involving as many as 10 vehicles.
Vehicles Per Crash
Source: Connecticut Crash Data · Csv Open Data · 2018-09-01 to 2018-09-30 · 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: 2018-09-01 through 2018-09-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2018-09-01 through 2018-09-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,063
- Total persons involved: 22,434
- Total vehicles involved: 17,186
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: September 2018." Published August 20, 2026. Reporting period: 2018-09-01 to 2018-09-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/september-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: 2018-09-01 – 2018-09-30
Generated: August 20, 2026 · All rights reserved
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