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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
6,797 CRASHES IN
CONNECTICUT, CT
2018
In 2018, New London County recorded 6,797 traffic crashes, resulting in 24 fatalities and 1,838 injuries. The most common type of collision was front-to-rear, accounting for 31.9% of all incidents. A majority of crashes occurred in clear weather and daylight conditions.
6,797
Total Crash Events
24
Persons Killed
1,838
Persons Injured
12.3%
Hit-and-Run Rate
Note: "Persons Killed" (24) 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 · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records
838
Hit-and-Run Crashes — 2018
Based on the responding officer's initial determination, 838 crashes in 2018 were classified as hit-and-run incidents. This represents 12.3% of all crashes in New London County during this period.
Vulnerable Road User Casualties
In 2018, motorists constituted the largest group of individuals killed or injured, with 23 fatalities and 1,769 injuries. Among vulnerable road users, one pedestrian was killed and 46 were injured. No cyclists were killed, but 23 sustained injuries in traffic crashes.
1
Pedestrians Killed
0
Cyclists Killed
23
Motorists Killed
46
Pedestrians Injured
23
Cyclists Injured
1,769
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 frequency in New London County peaked on Fridays, with 1,106 incidents recorded, and the single busiest hour for crashes was 3 p.m., with 561 events. A significant majority of crashes, 4,719 in total, occurred during daylight hours. A notable spike in crashes occurred during the afternoon commute period from 3 p.m. to 5 p.m.
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, 79.2%, resulted in no injuries and were classified as property-damage-only. Injury-related crashes, including serious, minor, and possible injuries, collectively accounted for 20.5% of incidents. In 2018, there were 23 fatal crashes, which resulted in a total of 24 fatalities.
Severity is per crash event (most severe injury). 23 fatal crash events resulted in 24 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 75.1% happening in clear weather and 73.9% on dry road surfaces. Similarly, 69.4% of all crashes took place during daylight hours. Crashes in adverse weather included 844 in rain and 268 in snow, while 1,220 incidents occurred on wet roads.
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
Analysis of the 15,818 persons involved in crashes shows the 26-34 age group was the most represented, with 2,594 individuals. Among the 12,102 vehicles involved, the most frequent make recorded was Ford with 1,441 vehicles. Other commonly involved makes included Toyota, Honda, and Jeep.
Top Vehicle Makes (12,102 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
1,103 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (14,891 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 speed limit zone with the highest number of crashes was 25 mph, accounting for 2,487 incidents or 36.6% of all crashes. While lower speed zones had more total crashes, the percentage of crashes within a zone that were fatal generally increased with higher speed limits. For instance, 0.6% of crashes in 45 mph zones were fatal, and this figure rose to 1.212% for crashes in 50 mph zones.
Fatal crashes by zone: 30 mph: 2 of 540 (0.37%) · 35 mph: 5 of 1,104 (0.453%) · 45 mph: 4 of 667 (0.6%) · 50 mph: 2 of 165 (1.212%) · 55 mph: 2 of 183 (1.093%) · 65 mph: 6 of 696 (0.862%) · 88 mph: 2 of 310 (0.645%)
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Posted speed limit at crash location
Top Towns
The highest concentration of crashes occurred in Norwich, which recorded 1,375 incidents, representing 20.2% of the county's total. New London followed with 1,044 crashes (15.4%), and Groton had 842 crashes (12.4%). These three municipalities collectively accounted for nearly half of all crashes in the county.
Top Towns
Showing top 9 of 21 reported. 12 additional (1,128 total) not shown: Griswold, Preston, Old Lyme, North Stonington, Lisbon, Lebanon, Franklin, Salem, Bozrah, Voluntown, Sprague, Lyme.
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 1,664 incidents, followed by Principal Arterials with 1,157 crashes. Combined, limited-access highways, including Interstates (1,127) and Freeways/Expressways (267), accounted for 20.5% of all crashes in the county.
Road Class
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Route System
Crashes were most prevalent on state-maintained routes, which include State routes (2,955 crashes), Interstates (1,093), and US Routes (478). These roadways collectively accounted for 4,526 crashes. In contrast, local roads were the location for 1,982 crashes.
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 specified, the vast majority (6,462) occurred on public roads. A total of 213 crashes, representing 3.2% of the recorded total, took place on private property such as parking lots or private drives.
Rural vs Urban
The data indicates a significant split between urban and rural crash locations, with 5,588 crashes occurring in urban areas. Crashes in rural areas accounted for 732 incidents, or 11.6% of the total where this classification was recorded.
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, with 4,844 incidents occurring at such mid-block or open road segments. Crashes at junctions accounted for 1,945 incidents, with T-intersections (985 crashes) and four-way intersections (816 crashes) being the most frequent types.
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 where the first harmful event was striking a fixed object, the most common objects hit were guardrail faces (329 times), other fixed objects like walls or buildings (256), and utility poles or light supports (203). Collisions with utility poles and trees combined accounted for 349 of these run-off-road incidents.
Run-off-Road / Fixed-Object Strikes
Showing top 9 of 22 reported. 13 additional (290 total) not shown: Mailbox, Ditch, Concrete Traffic Barrier, Fence, Guardrail End, Bridge Rail, Other Traffic Barrier, Traffic Signal Support, Bridge Overhead Structure, Impact Attenuator/Crash Cushion, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Culvert, Bridge Pier or Support.
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 7,279 vehicles. Sport utility vehicles (2,113) and pickup trucks (1,132) were the next most frequent. The data also includes 256 medium or heavy trucks, 111 motorcycles, and 80 buses of various types.
Vehicle Type
Showing top 9 of 17 reported. 8 additional (115 total) not shown: School Bus, Moped, Transit Bus, Other Bus, Motor Home, Motor Coach, All Terrain Vehicle (ATV), Golf Cart.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
Traffic Control Device
Analysis of traffic controls for vehicles involved in crashes shows that the majority, 8,633, were at locations with no control device. Vehicles at locations with traffic signals were involved in 2,509 instances, while those at stop signs were involved in 635. This indicates a higher prevalence of crashes at uncontrolled locations compared to signalized intersections.
Traffic Control Device
"Other" combines 4 smaller categories (28 records): Marked Uncontrolled Crosswalk (12), Warning Sign (10), School Zone Sign/Device (3), Railway Crossing Device (3).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
Vulnerable Road Users & Motorcycles
Crashes in 2018 involved 199 motorcyclists, pedestrians, or bicyclists. Of these, motorcyclists were the most frequent group with 107 incidents. Combined, pedestrians (61) and bicyclists (31) accounted for 92 crashes, representing 46.2% of these specific incident types.
Driver Contributing Action
The most frequently cited driver action contributing to a crash was 'Followed Too Closely,' recorded for 1,773 drivers. The second most common action was 'Failed to Keep in Proper Lane,' noted for 1,291 drivers. Other significant actions included 'Failed to Yield Right-of-Way' (598 drivers) and 'Ran Off Roadway' (539 drivers).
Driver Contributing Action
Showing top 9 of 18 reported. 9 additional (680 total) not shown: Ran Red Light, Ran Stop Sign, Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner, 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.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events
Driver Condition
Among driver conditions noted as contributing factors, 298 drivers were identified as being under the influence of medications, drugs, or alcohol. An additional 145 drivers were noted as asleep or fatigued. Other recorded conditions included being ill or fainting (41 drivers) and emotional distress (37).
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 was 'Straight Ahead,' which was recorded for 5,988 vehicles, representing nearly half of all vehicles with a recorded action. Other frequent actions included 'Turning Left' (975 vehicles) and being 'Stopped in Traffic' (897 vehicles).
Pre-Crash Driver Action
Showing top 9 of 17 reported. 8 additional (676 total) not shown: Overtaking/Passing, Entering Traffic Lane, Other, Leaving Traffic Lane, Making U-Turn, Wrong way (or Wrong Side), Traveling in Bike Lane, Overtaking/Passing Cyclist.
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
Point of Impact
The most common point of impact on vehicles was the front, described as 'Sector 12 (North) in the 12-point Clock Diagram,' which occurred in 3,261 instances. The second most frequent impact point was the rear ('Sector 6 (South)'), recorded for 2,178 vehicles.
Point of Impact
"Other" combines 9 smaller categories (1,856 records): Sector 5 (South by SouthEast) in the 12-point Clock Diagram (432), Sector 9 (West) in the 12-point Clock Diagram (389), Sector 3 (East) in the 12-point Clock Diagram (344), Sector 8 (SouthWest) in the 12-point Clock Diagram (289), Sector 4 (SouthEast) in the 12-point Clock Diagram (235), Non-Collision (71), Top (48), Undercarriage (38), Cargo loss (10).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Vehicle unit records
Pedestrian/Cyclist Action
Among pedestrians for whom an action was recorded, 41 were determined to have taken 'No Improper Action'. For those with contributing actions, 'Failure to Yield Right-Of-Way' was noted for 10 pedestrians, while 'Dart/Dash' and 'Failure to Obey Traffic Signs' were each recorded for 9 pedestrians.
Pedestrian/Cyclist Action
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Non-motorist records linked to crash events
Manner of Collision
The most prevalent manner of collision was 'Front to rear,' accounting for 2,170 crashes, or 31.9% of the total. Angle collisions were the second most common type, with 1,102 incidents, representing 16.2% of all crashes.
Manner of Collision
"Other" combines 1 smaller categories (46 records): Rear to rear (46).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Person Type
Of the 15,818 individuals involved in crashes, the majority were drivers (11,424). Passengers made up the next largest group with 3,636 individuals, or 23% of all persons involved. The records also include 64 pedestrians and 31 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 15,818 people involved in crashes, 1,838 sustained some level of injury, representing 11.6% of all persons. This includes 75 serious injuries, 881 minor injuries, and 882 possible injuries. A total of 24 individuals suffered fatal injuries.
Person Injury Severity
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Crash-level records
Occupant Safety Equipment
The majority of vehicle occupants, 12,386 individuals, were recorded as using both a shoulder and lap belt. For 351 occupants, it was determined that no restraint was used, accounting for 2.5% of individuals where safety equipment use was noted. An additional 294 occupants were secured in a forward-facing child restraint system.
Occupant Safety Equipment
"Other" combines 3 smaller categories (114 records): Other (52), Lap Belt Only Used (46), Child Restraint, Type Unknown (16).
Source: Connecticut Crash Data · Csv Open Data · 2018-01-01 to 2018-12-31 · Person-level records linked to crash events
Vehicles Per Crash
Two-vehicle collisions were the most common scenario, accounting for 4,525 crashes, or 66.6% of the total. Single-vehicle crashes represented 28.5% of incidents, with 1,935 recorded. Crashes involving three or more vehicles were less frequent, with one incident involving as many as seven vehicles.
Vehicles Per Crash
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 21, 2026
Data Coverage
- Reporting period: 2018-01-01 through 2018-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 6,797
- Total persons involved: 15,818
- Total vehicles involved: 12,102
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 21, 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 21, 2026 · All rights reserved
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