Monthly Traffic Safety Analysis

170 CRASHES IN
CHICOPEE, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

In January 2024, CHICOPEE recorded 170 crashes, a significant increase from the 123 crashes reported in January 2023, representing a 38.21% rise. This period also saw a substantial increase in speeding-related crashes, which rose from 5 in January 2023 to 24 in January 2024.

170

38.2%was 123

Total Crash Events

0

Persons Killed

47

34.3%was 35

Persons Injured

24

14.3%was 21

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in CHICOPEE showed an upward trend year-over-year, increasing from 123 crashes in January 2023 to 170 crashes in January 2024. This represents a 38.21% rise in total crashes for the month.

24

Hit-and-Run Crashes — January 2024

14.3% vs prior (21)

The number of hit-and-run crashes increased from 21 in January 2023 to 24 in January 2024. However, the hit-and-run rate decreased from 17.1% of total crashes in January 2023 to 14.1% in January 2024.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

47

Motorists Injured

Prior: 3246.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Both January 2023 and January 2024 periods identified Tuesday as the peak day for crashes, with counts increasing from 27 to 37. The peak hour for crashes shifted from 5 PM with 14 crashes in January 2023 to 4 PM with 23 crashes in January 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both January 2023 and January 2024, while total injuries increased from 35 to 47. The proportion of minor injuries rose from 13.8% (17 crashes) in January 2023 to 14.7% (25 crashes) in January 2024, and serious injuries reported in January 2023 (2 crashes, 1.6%) were not recorded in January 2024.

Outcome by Severity (Crash Events)

Minor Injury25minor injury crashes14.7%
47.1%prior 17
Possible Injury9possible injury crashes5.3%
28.6%prior 7
No Injury127no injury crashes74.7%
36.6%prior 93

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Most severe injury per crash record

Top Contributing Factors

"No improper driving" increased from 32 crashes in January 2023 to 52 crashes in January 2024. "Driving too fast for conditions" saw a notable increase in count from 2 crashes in January 2023 to 21 crashes in January 2024, significantly impacting its ranking. Conversely, "Inattention" decreased from 23 crashes in January 2023 to 13 crashes in January 2024.

Officer-Reported Primary Contributing Cause

No improper driving52 (30.6%)62.5%prior 32
Driving too fast for conditions21 (12.4%)
Failed to yield right of way18 (10.6%)28.6%prior 14
Failure to keep in proper lane or running off road13 (7.6%)160.0%prior 5
Inattention13 (7.6%)-43.5%prior 23
Followed too closely11 (6.5%)37.5%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner6 (3.5%)20.0%prior 5
Other improper action5 (2.9%)
Disregarded traffic signs, signals, road markings4 (2.4%)
Over-correcting/over-steering4 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather increased from 58 in January 2023 to 70 in January 2024, and crashes in snowy conditions rose from 5 to 19. Crashes on dry road surfaces increased from 74 to 77, while those on snowy surfaces saw a significant rise from 7 to 36. Crashes during daylight hours increased from 68 to 108, but crashes in dark-lighted roadway conditions remained stable at 46 for both periods.

Weather

Clear70 (41.7%)
20.7%prior 58
Cloudy40 (23.8%)
81.8%prior 22
Snow19 (11.3%)
280.0%prior 5
Rain10 (6.0%)
11.1%prior 9
Cloudy/Snow5 (3.0%)
Snow/Sleet, hail (freezing rain or drizzle)5 (3.0%)
Cloudy/Rain3 (1.8%)
-50.0%prior 6
Clear/Other2 (1.2%)
Clear/Unknown2 (1.2%)
Cloudy/Other2 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Weather condition at time of crash

Lighting

Daylight108 (64.3%)
58.8%prior 68
Dark - lighted roadway46 (27.4%)
0.0%prior 46
Dark - roadway not lighted5 (3.0%)
-16.7%prior 6
Dusk5 (3.0%)
Dawn3 (1.8%)
Dark - unknown roadway lighting1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Lighting condition field

Road Surface

Dry77 (45.6%)
4.1%prior 74
Wet45 (26.6%)
9.8%prior 41
Snow36 (21.3%)
414.3%prior 7
Slush6 (3.6%)
Ice5 (3.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes increased from 299 in January 2023 to 362 in January 2024. The 65+ age group saw a notable increase in involvement, from 17 persons in January 2023 to 34 persons in January 2024. Toyota became the top vehicle make involved in crashes in January 2024 with 52 vehicles, surpassing Honda which was the top make in January 2023 with 37 vehicles.

Top Vehicle Makes (305 vehicles)

1
TOYOTA52 (17%)
108.0%prior 25
2
HONDA38 (12.5%)
2.7%prior 37
3
NISSAN35 (11.5%)
59.1%prior 22
4
HYUNDAI23 (7.5%)
109.1%prior 11
5
FORD20 (6.6%)
-13.0%prior 23
6
CHEVROLET18 (5.9%)
28.6%prior 14
7
SUBARU9 (3%)
8
JEEP9 (3%)
50.0%prior 6
9
INFI7 (2.3%)
10
CHRYSLER6 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Vehicle unit records

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

Sex Distribution (307 persons with recorded sex)

Male179 (58.3%)
30.7%prior 137
Female128 (41.7%)
7.6%prior 119

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed limit zone increased from 44 in January 2023 to 59 in January 2024. Similarly, crashes in the 30 mph zone rose from 36 to 47, and crashes in the 55 mph zone also saw an increase from 7 to 17. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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: 2024-01-01 through 2024-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: CHICOPEE, MA
  • Total crash records analyzed: 170
  • Total persons involved: 362
  • Total vehicles involved: 305

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: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/january-2024-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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Chicopee, MA Crash Report — January 2024 | ThatCarHitMe.com