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ThatCarHitMe.com
An Injuria.ai Company
CRASH INTELLIGENCE REPORT · CONNECTICUT, CT · 2015
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/2015-annual-report
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)
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
Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2015-01-01 to 2015-12-31 · Lighting condition field
Road Surface
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)
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)
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
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
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
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
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
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
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
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
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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Connecticut Crash Data · Csv
Period: 2015-01-01 – 2015-12-31
Generated: August 21, 2026 · All rights reserved
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