ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · DECEMBER 2022
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/massachusetts/chicopee/december-2022-report
Monthly Traffic Safety Analysis
193 CRASHES IN
CHICOPEE, MA
DECEMBER 2022
Total crashes in CHICOPEE decreased slightly from 196 in December 2021 to 193 in December 2022, a 1.53% reduction. However, total fatalities doubled from 1 to 2 during the same period, marking the most notable year-over-year shift. Total injuries saw a minor decrease from 46 to 45.
193
▼ -1.5%was 196
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
45
▼ -2.2%was 46
Persons Injured
23
▼ -32.4%was 34
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in CHICOPEE remained relatively stable with a slight downward trend, decreasing by 1.53% year-over-year from 196 to 193. Despite this, the number of fatal crashes and total fatalities both doubled during this period.
23
Hit-and-Run Crashes — December 2022
▼ -32.4% vs prior (34)
Hit-and-run crashes decreased from 34 in December 2021 to 23 in December 2022. This represents a decrease in the hit-and-run rate from 17.3% to 11.9% of total crashes. The trend for hit-and-run incidents is downward year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Cyclists Killed
1
Motorists Killed
0
Other Killed
2
Pedestrians Injured
0
Cyclists Injured
42
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Friday with 39 crashes in the prior period to Thursday with 35 crashes in the current period. The peak hour also shifted, moving from 4 p.m. with 17 crashes in the prior period to 5 p.m. with 26 crashes in the current period. Notably, Sunday crashes increased significantly from 9 to 27.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes increased from 1 in the prior period to 2 in the current period, raising the fatal crash rate from 0.5% to 1.0% of total crashes. Crashes resulting in serious injury (Severity A) rose from 1 to 3, while minor injury crashes (Severity B) decreased from 19 to 18. Overall, crashes with any injury (Severity A, B, or C) increased from 31 (15.8% of total crashes) to 39 (20.2% of total crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to "No improper driving" decreased from 54 to 51, and "Inattention" decreased from 26 to 24. Crashes due to "Followed too closely" saw a notable decrease from 22 to 15, while "Other improper action" increased from 6 to 13 crashes. "Failed to yield right of way" remained stable at 18 crashes for both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under "Clear" weather conditions decreased from 108 to 93, while those in "Cloudy/Rain" conditions increased substantially from 4 to 16. On road surfaces, crashes on "Wet" roads increased from 43 to 48, and on "Snow" from 14 to 20. Crashes on "Ice" decreased from 9 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
Toyota became the most frequent vehicle make involved in crashes, increasing from 48 to 49, while Honda decreased from 50 to 46. Among persons involved, the 21-25 age group saw an increase from 48 to 55, and the 55-64 age group increased from 37 to 48. Conversely, the 26-34 age group experienced a decrease from 74 to 68 persons.
Top Vehicle Makes (351 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records
62 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (377 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone decreased from 64 to 58, with no fatal crashes in the current period compared to one in the prior period. The 30 mph zone saw a decrease in crashes from 62 to 55, but recorded one fatal crash in the current period where there were none previously. Crashes in the 55 mph zone increased from 12 to 15, also with one fatal crash in the current period.
Fatal crashes by zone: 30 mph: 1 of 55 (1.818%) · 55 mph: 1 of 15 (6.667%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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: Arcgis_yearly 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: 2022-12-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-12-01 through 2022-12-31 (31 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 193
- Total persons involved: 443
- Total vehicles involved: 351
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). "CHICOPEE, MA Crash Intelligence Report: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/december-2022-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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-12-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved