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Yearly Traffic Safety Analysis

6,693 CRASHES IN
CONNECTICUT, CT
2015

In 2015, New London County recorded 6,693 traffic crashes, resulting in 27 fatalities and 1,962 injuries. The data indicates a significant portion of these incidents occurred during afternoon commuting hours, with the peak hour for crashes being 4 PM. Analysis of collision types shows that front-to-rear crashes were the most frequent, accounting for 32.7% of all incidents.

6,693

Total Crash Events

27

Persons Killed

1,962

Persons Injured

10.8%

Hit-and-Run Rate

Note: "Persons Killed" (27) counts individual fatalities across all crash events. "Fatal" in the severity table below (25) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Aggregate counts from crash, person, and vehicle records

723

Hit-and-Run Crashes — 2015

In 2015, 723 crashes in New London County were classified as hit-and-run incidents, representing 10.8% of all recorded crashes. This classification is based on the initial determination made by the responding law enforcement officer at the scene. The data reflects only those incidents where a driver was determined to have left the scene unlawfully.

Vulnerable Road User Casualties

Motor vehicle occupants represented the vast majority of casualties, with 25 motorists killed and 1,890 injured in 2015. Among vulnerable road users, there were 2 pedestrian fatalities and 48 pedestrians injured. No cyclists were killed during this period, but 23 sustained injuries in crashes.

2

Pedestrians Killed

0

Cyclists Killed

25

Motorists Killed

0

Other Killed

48

Pedestrians Injured

23

Cyclists Injured

1,890

Motorists Injured

1

Other Injured

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash occurrences in New London County show distinct temporal patterns, with the most frequent day for crashes being Friday with 1,096 incidents. The afternoon commute period saw the highest concentration of collisions, peaking during the 4 PM hour with 587 crashes. Overall, 69.2% of all crashes (4,635 incidents) occurred during daylight hours.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The majority of crashes in 2015 did not result in physical harm, with 78.5% (5,255 incidents) classified as involving no injury. Injury-related crashes, encompassing serious, minor, and possible injuries, accounted for 21.2% of incidents. The data recorded 25 fatal crashes, which resulted in a total of 27 fatalities, indicating some incidents involved more than one death.

Severity is per crash event (most severe injury). 25 fatal crash events resulted in 27 persons killed.

Outcome by Severity (Crash Events)

Fatal25fatal crashes0.4%
Serious Injury72serious injury crashes1.1%
Minor Injury627minor injury crashes9.4%
Possible Injury714possible injury crashes10.7%
No Injury5,255no injury crashes78.5%

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The vast majority of crashes occurred in ideal driving conditions, with 75.6% of incidents (5,057) happening in clear weather and 72.8% (4,872) on dry road surfaces. Correspondingly, 69.2% of all crashes (4,635) occurred during daylight hours. Crashes in adverse weather included 593 in rain and 490 in snow, while 913 incidents occurred on wet roads.

Weather

Clear5,057 (76.3%)
Rain593 (8.9%)
Snow490 (7.4%)
Cloudy251 (3.8%)
Blowing Snow93 (1.4%)
Freezing Rain or Freezing Drizzle64 (1.0%)
Fog, Smog, Smoke43 (0.6%)
Other17 (0.3%)
Sleet or Hail17 (0.3%)
Severe Crosswinds3 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash

Lighting

Daylight4,635 (69.8%)
Dark-Lighted1,076 (16.2%)
Dark-Not Lighted710 (10.7%)
Dusk128 (1.9%)
Dawn60 (0.9%)
Dark-Unknown Lighting25 (0.4%)
Other11 (0.2%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field

Road Surface

Dry4,872 (73.1%)
Wet913 (13.7%)
Snow524 (7.9%)
Ice / Frost173 (2.6%)
Slush134 (2.0%)
Other14 (0.2%)
Mud, Dirt, Gravel13 (0.2%)
Sand12 (0.2%)
Standing Water10 (0.1%)
Moving Water3 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Road surface condition field

Vehicles & Demographics

Analysis of persons involved in crashes shows the 26-34 age group was most frequently represented with 2,548 individuals, followed by the 45-54 age group with 2,238 individuals. Among the 11,824 vehicles involved, Ford was the most common make with 1,487 vehicles. After consolidating variations in make names, Toyota-branded vehicles were involved in 1,265 crashes, and Honda vehicles were involved in 1,122 crashes.

Top Vehicle Makes (11,824 vehicles)

1
FORD1,487 (12.6%)
2
HOND811 (6.9%)
3
CHEV786 (6.6%)
4
TOYT762 (6.4%)
5
NISS608 (5.1%)
6
JEEP447 (3.8%)
7
HYUN414 (3.5%)
8
DODG396 (3.3%)
9
SUBA348 (2.9%)
10
TOYOTA283 (2.4%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

953 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (15,221 persons with recorded sex)

Male8,471 (55.7%)
Female6,750 (44.3%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Speed Limit Zones

Roadways with a posted speed limit of 25 mph saw the highest number of crashes, accounting for 2,258 incidents or 33.7% of the total. While lower speed zones had more crashes, the percentage of those crashes that were fatal increased in higher speed zones. For instance, 0.266% of crashes in 25 mph zones were fatal, compared to 0.665% in 35 mph zones and 0.686% in 65 mph zones.

Fatal crashes by zone: 25 mph: 6 of 2,258 (0.266%) · 35 mph: 7 of 1,052 (0.665%) · 40 mph: 1 of 328 (0.305%) · 45 mph: 2 of 649 (0.308%) · 50 mph: 1 of 151 (0.662%) · 55 mph: 1 of 164 (0.61%) · 65 mph: 6 of 874 (0.686%) · 88 mph: 1 of 184 (0.543%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Posted speed limit at crash location

Top Towns

The geographic distribution of crashes across New London County was concentrated in its larger municipalities. The city of Norwich recorded the highest volume with 1,297 crashes, representing 19.4% of the county's total. Following Norwich were Groton with 904 crashes (13.5%) and the city of New London with 694 crashes (10.4%).

Top Towns

1
Norwich1,297 (19.4%)
2
Groton904 (13.5%)
3
New London694 (10.4%)
4
Waterford629 (9.4%)
5
Montville498 (7.4%)
6
Stonington485 (7.2%)
7
East Lyme372 (5.6%)
8
Ledyard330 (4.9%)
9
Colchester291 (4.3%)

Showing top 9 of 21 reported. 12 additional (1,193 total) not shown: Old Lyme, Preston, Griswold, North Stonington, Lisbon, Salem, Franklin, Lebanon, Bozrah, Voluntown, Sprague, Lyme.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Road Class

Among crashes where the roadway's functional class was recorded, incidents were most frequent on Interstates (460 crashes) and Local roads (457 crashes). Limited-access highways, combining Interstates and Freeways/Expressways, accounted for 612 crashes. Collector roads and Minor Arterials also saw significant crash volumes, with 426 and 250 incidents, respectively.

Road Class

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Route System

Analysis of the route system indicates that a majority of crashes occurred on roads maintained by the state. State routes accounted for 2,850 crashes, followed by local roads (1,985), Interstates (1,131), and US Routes (437). Combined, state-maintained roadways (State, Interstate, and US Routes) were the location for 69.0% of the crashes where route system was identified.

Route System

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Public vs Private Road

Of the crashes where roadway ownership was documented, the vast majority occurred on public roads, totaling 6,283 incidents. A smaller but notable number of crashes, 195 incidents or 3.0% of the recorded total, took place on private property such as parking lots or private drives. These incidents fall under a distinct category of traffic safety.

Rural vs Urban

Based on crashes with a specified rural or urban designation, 19.6% (366 incidents) occurred in rural areas. The remaining 80.4% (1,504 incidents) took place in urban settings. This distinction is significant as crash dynamics and severity often differ between these environments.

Rural vs Urban

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Junction Type

The majority of crashes, 4,809 incidents, occurred at locations not classified as intersections. Of the crashes that did happen at junctions, T-intersections were the most common site with 907 crashes, followed by four-way intersections with 791. In total, 28.1% of all crashes with a recorded location type occurred at an intersection.

Junction Type

1
Not at Intersection4,809 (71.9%)
2
T-Intersection907 (13.6%)
3
Four-Way Intersection791 (11.8%)
4
Y-Intersection97 (1.5%)
5
L-Intersection33 (0.5%)
6
Five-Point, or More30 (0.4%)
7
Roundabout15 (0.2%)
8
Traffic Circle3

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Run-off-Road / Fixed-Object Strikes

Among crashes involving a collision with a fixed object, the most frequently struck object was a guardrail face, involved in 363 incidents. This was followed by other fixed objects like walls or buildings (234 crashes) and utility or light poles (225 crashes). Collisions with poles and trees combined accounted for 354 incidents, representing 21.7% of all recorded fixed-object crashes.

Run-off-Road / Fixed-Object Strikes

1
Guardrail Face363 (22.1%)
2
Other Fixed Object (wall, building, tunnel, etc.)234 (14.2%)
3
Utility Pole/Light Support225 (13.7%)
4
Tree (standing)129 (7.8%)
5
Embankment105 (6.4%)
6
Curb101 (6.1%)
7
Other Post, Pole or Support95 (5.8%)
8
Cable Barrier74 (4.5%)
9
Concrete Traffic Barrier58 (3.5%)

Showing top 9 of 22 reported. 13 additional (260 total) not shown: Traffic Sign Support, Mailbox, Guardrail End, Fence, Ditch, Bridge Rail, Culvert, Other Traffic Barrier, Struck by Falling, Shifting Cargo or Anything Set in Motion by Motor Vehicle, Bridge Overhead Structure, Impact Attenuator/Crash Cushion, Bridge Pier or Support, Traffic Signal Support.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, accounting for 7,382 vehicles, or 62.4% of the total. Sport utility vehicles (1,712) and pickup trucks (1,155) were the next most frequent. Notably, medium or heavy trucks were involved in 326 incidents (2.8%), while motorcycles were involved in 134 crashes (1.1%).

Vehicle Type

1
Passenger Car7,382 (63.7%)
2
(Sport) Utility Vehicle1,712 (14.8%)
3
Pick Up1,155 (10%)
4
Passenger Van335 (2.9%)
5
Medium / Heavy Trucks (more than 10,000 lbs (4,536 kg))326 (2.8%)
6
Other Light Trucks (10,000 lbs (4,536 kg) or less)155 (1.3%)
7
Other146 (1.3%)
8
Motorcycle134 (1.2%)
9
Cargo Van (10,000 lbs/4,536 kg or less)129 (1.1%)

Showing top 9 of 17 reported. 8 additional (120 total) not shown: School Bus, Moped, Transit Bus, Other Bus, Motor Home, Low Speed Vehicle, Motor Coach, All Terrain Vehicle (ATV).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Traffic Control Device

Analysis of traffic controls at crash locations indicates that 69.2% of involved vehicles (8,178) were in areas with no traffic control device. Crashes at locations with traffic signals accounted for 23.0% of vehicle involvements (2,719). Stop signs were present for 4.6% of vehicle involvements, representing 547 incidents.

Traffic Control Device

"Other" combines 3 smaller categories (26 records): Person (including flagger, law enforcement, crossing guard, etc.) (20), Marked Uncontrolled Crosswalk (5), Pedestrian Button (1).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Vulnerable Road Users & Motorcycles

In crashes involving vulnerable road users or motorcyclists, motorcyclists were the most frequently involved group with 128 incidents. Pedestrians were involved in 59 crashes and bicyclists in 29. Combined, pedestrians and bicyclists accounted for 88 incidents, representing 40.7% of crashes in this specific group.

Driver Contributing Action

Among contributing actions cited for drivers, 'Followed Too Closely' was the most common, attributed to 1,779 drivers, or 16.1% of all drivers with an action recorded. The second most frequent action was 'Failed to Keep in Proper Lane,' noted for 1,047 drivers (9.4%). 'Failed to Yield Right-of-Way' was the third most common contributing factor, cited for 597 drivers.

Driver Contributing Action

1
No Contributing Action4,747 (44.5%)
2
Followed Too Closely1,779 (16.7%)
3
Failed to Keep in Proper Lane1,047 (9.8%)
4
Failed to Yield Right-of-Way597 (5.6%)
5
Ran Off Roadway512 (4.8%)
6
Other Contributing Action435 (4.1%)
7
Improper Backing261 (2.4%)
8
Improper Turn238 (2.2%)
9
Swerved or Avoided Due to Wind, Slippery Surface, Motor Vehicle, Object, Non-Motorist in Roadway, etc.232 (2.2%)

Showing top 9 of 19 reported. 10 additional (813 total) not shown: Operated Motor Vehicle in Inattentive, Careless, Negligent, or Erratic Manner, Improper Passing, Ran Red Light, Ran Stop Sign, 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 · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Driver Condition

Beyond drivers noted as 'Apparently Normal,' the most frequently cited condition was being 'Under the Influence of Medications/Drugs/Alcohol,' which was recorded for 300 drivers (2.7% of total drivers). Driver fatigue was also a notable factor, with 160 drivers identified as 'Asleep or Fatigued.' Other recorded conditions included emotional distress (55 drivers) and illness (43 drivers).

Driver Condition

1
Apparently Normal9,796 (93.8%)
2
Under the Influence of Medications/Drugs/Alcohol300 (2.9%)
3
Asleep or Fatigued160 (1.5%)
4
Emotional (depressed, angry, disturbed, etc.)55 (0.5%)
5
Other53 (0.5%)
6
Ill (sick), Fainted43 (0.4%)
7
Physically Impaired31 (0.3%)

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Pre-Crash Driver Action

The most common pre-crash action for vehicles was 'Straight Ahead,' accounting for 48.1% of vehicle movements (5,689 incidents). A significant number of vehicles were 'Stopped in Traffic' (981 vehicles) or 'Turning Left' (910 vehicles) immediately prior to a collision. These actions represent the most common scenarios leading up to a crash.

Pre-Crash Driver Action

1
Straight Ahead5,689 (49%)
2
Stopped in Traffic981 (8.4%)
3
Turning Left910 (7.8%)
4
Parked773 (6.7%)
5
Negotiating a Curve719 (6.2%)
6
Slowing669 (5.8%)
7
Turning Right465 (4%)
8
Backing358 (3.1%)
9
Changing Lanes266 (2.3%)

Showing top 9 of 17 reported. 8 additional (788 total) not shown: Overtaking/Passing, Other, Entering Traffic Lane, Leaving Traffic Lane, Wrong way (or Wrong Side), Making U-Turn, Traveling in Bike Lane, Overtaking/Passing Cyclist.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Point of Impact

The front of the vehicle, designated as Sector 12, was the most common point of impact, recorded in 3,372 instances or 28.5% of all vehicle impacts. The rear of the vehicle (Sector 6) was the second most frequent impact point, involved in 2,168 cases (18.3%). These two areas represent the primary points of contact in vehicle collisions.

Point of Impact

"Other" combines 9 smaller categories (1,896 records): Sector 5 (South by SouthEast) in the 12-point Clock Diagram (421), Sector 2 (NorthEast) in the 12-point Clock Diagram (415), Sector 3 (East) in the 12-point Clock Diagram (344), Sector 8 (SouthWest) in the 12-point Clock Diagram (268), Sector 4 (SouthEast) in the 12-point Clock Diagram (207), Non-Collision (111), Top (71), Undercarriage (43), Cargo loss (16).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Vehicle unit records

Pedestrian/Cyclist Action

For crashes involving pedestrians where an action was recorded, 40 individuals (41.2%) were determined to have taken 'No Improper Action'. Among improper actions cited, 'In Roadway Improperly' was the most frequent with 11 instances, followed by 'Dart/Dash' into the road with 8 instances. Failure to obey traffic signals was also noted in 6 cases.

Pedestrian/Cyclist Action

1
No Improper Action40 (46%)
2
In Roadway Improperly (Standing, Lying, Working, Playing)11 (12.6%)
3
Dart/Dash8 (9.2%)
4
Failure to Obey Traffic Signs, Signals, or Officer6 (6.9%)
5
Failure to Yield Right-Of-Way5 (5.7%)
6
Other4 (4.6%)
7
Entering/Exiting Parked/Standing Vehicle4 (4.6%)
8
Not Visible (Dark Clothing, No Lighting, etc.)4 (4.6%)
9
Inattentive (Talking, Eating, etc.)3 (3.4%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: Wrong-Way Riding or Walking, Improper Turn/Merge.

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Non-motorist records linked to crash events

Manner of Collision

The most prevalent type of collision was 'Front to rear,' which accounted for 2,188 incidents, or 32.7% of all crashes with a recorded collision manner. Angle collisions were the second most common type, with 1,093 incidents (16.3%). Sideswipes in the same direction of travel constituted another 10.5% of the total.

Manner of Collision

"Other" combines 1 smaller categories (53 records): Front to front (53).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Type

A total of 16,001 individuals were involved in crashes, with drivers being the most numerous group at 11,083 people, or 69.3% of the total. Passengers constituted the second-largest group, with 4,080 individuals (25.5%). Vulnerable road users were also involved, including 65 pedestrians and 30 bicyclists.

Person Type

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Person Injury Severity

Out of all 16,001 people involved in crashes, 1,962 individuals sustained some level of injury, representing 12.3% of the total. A smaller fraction, 27 people (0.17%), suffered fatal injuries. The vast majority of individuals, 13,411 people or 83.8%, were recorded as having no injuries.

Person Injury Severity

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Crash-level records

Occupant Safety Equipment

Among 14,069 vehicle occupants with safety equipment usage recorded, 89.0% (12,517 individuals) were using both a shoulder and lap belt. However, 364 occupants, or 2.6% of the total, were recorded as using no restraint system at all. Child restraint systems were used by 445 children, including forward-facing, rear-facing, and booster seats.

Occupant Safety Equipment

"Other" combines 3 smaller categories (142 records): Other (57), Booster Seat (56), Child Restraint, Type Unknown (29).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Person-level records linked to crash events

Vehicles Per Crash

The most common incident involved two vehicles, accounting for 65.6% of all crashes (4,389 incidents). Single-vehicle crashes were the next most frequent category, with 1,981 incidents making up 29.6% of the total. While less common, several multi-vehicle pile-ups were recorded, including one crash involving 9 vehicles and another involving 8.

Vehicles Per Crash

"Other" combines 2 smaller categories (2 records): 8 (1), 9 (1).

Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · 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: 2015-01-01 through 2015-12-31
  • Report generated: August 21, 2026

Data Coverage

  • Reporting period: 2015-01-01 through 2015-12-31 (365 days)
  • Geographic scope: connecticut, CT
  • Total crash records analyzed: 6,693
  • Total persons involved: 16,001
  • Total vehicles involved: 11,824

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: 2015." Published August 21, 2026. Reporting period: 2015-01-01 to 2015-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2015-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

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