Yearly Traffic Safety Analysis

12 CRASHES IN
CHESTERFIELD, MA
2024

All metrics benchmarked against2023

In 2024, Chesterfield experienced 12 total crashes, a 29.4% decrease from the 17 crashes recorded in 2023. Despite the overall decline in collisions, the most significant change was the occurrence of one fatal crash in 2024, which resulted in one fatality, whereas no fatal crashes were reported in the prior year.

12

-29.4%was 17

Total Crash Events

1

Persons Killed

3

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes in Chesterfield decreased by 29.4% year-over-year, falling from 17 in 2023 to 12 in 2024. While the total number of injuries remained constant at 3 for both periods, the year was marked by an increase in crash severity, with fatalities rising from zero to one.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

3

Motorists Injured

Prior: 30.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. In 2024, Thursday and Saturday were the peak days for crashes with 3 incidents each, compared to 2023 when Thursday was the sole peak day with 4 crashes. The peak hour for collisions in 2024 was 3 p.m. with 2 crashes, whereas in 2023, the peak was less concentrated, with four different hours each recording 2 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased in 2024, with one fatal crash accounting for 8.3% of all incidents, compared to zero fatal crashes in 2023. The proportion of crashes resulting in minor injuries also increased, making up 25% of crashes in 2024 versus 5.9% in the prior year. In 2023, 11.8% of crashes were categorized with 'Possible Injury', a severity level not recorded for any crash in 2024.

Outcome by Severity (Crash Events)

Fatal1fatal crashes8.3%
Minor Injury3minor injury crashes25%
200.0%prior 1
No Injury8no injury crashes66.7%
-27.3%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted notably year-over-year. In 2024, 'Driving too fast for conditions' became the most cited factor, with the count of incidents increasing from 1 to 4. 'Failure to keep in proper lane or running off road' was a factor in 3 crashes in 2024, a category not present in the 2023 data. Conversely, crashes attributed to 'No improper driving' saw a significant decrease, falling from 6 incidents in 2023 to just 1 in 2024.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions4 (33.3%)
Failure to keep in proper lane or running off road3 (25%)
Failed to yield right of way1 (8.3%)
Exceeded authorized speed limit1 (8.3%)
Fatigued/asleep1 (8.3%)
No improper driving1 (8.3%)-83.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In 2024, a larger proportion of crashes occurred during daylight hours (66.7%) compared to 2023 (52.9%). However, there was a notable increase in the share of crashes on adverse road surfaces, with 41.7% of incidents in 2024 occurring on snow or slush, compared to 29.4% on wet or icy roads in the prior year. Crashes in clear weather conditions accounted for 8 incidents in both years, representing a larger share (66.7%) of the smaller crash total in 2024.

Weather

Clear8 (66.7%)
0.0%prior 8
Cloudy2 (16.7%)
Clear/Snow1 (8.3%)
Snow/Blowing sand, snow1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight8 (66.7%)
-11.1%prior 9
Dark - roadway not lighted3 (25.0%)
-57.1%prior 7
Dark - lighted roadway1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry7 (58.3%)
-41.7%prior 12
Snow3 (25.0%)
Other1 (8.3%)
Slush1 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (17 vehicles)

1
HONDA3 (17.6%)
2
FORD2 (11.8%)
3
CHEVROLET2 (11.8%)
4
SUBARU2 (11.8%)
5
JEEP1 (5.9%)
6
KIA1 (5.9%)
7
MAZDA1 (5.9%)
8
SKIDOO1 (5.9%)
9
INTERNATIONAL H1 (5.9%)
10
FRHT1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

Sex Distribution (19 persons with recorded sex)

Male9 (47.4%)
-30.8%prior 13
Female8 (42.1%)
-20.0%prior 10
X / Unspecified2 (10.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in posted speed zones decreased from 17 in 2023 to 11 in 2024. The 30 mph zone was the most frequent location for crashes in both years, though the count fell from 6 to 4. Collisions in the 35 mph zone also saw a decrease from 5 to 2. The single fatal crash reported in 2024 did not have a posted speed limit recorded in the data, while no fatal crashes occurred in any speed zone in 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: CHESTERFIELD, MA
  • Total crash records analyzed: 12
  • Total persons involved: 20
  • Total vehicles involved: 17

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). "CHESTERFIELD, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chesterfield/2024-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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Chesterfield, MA Crash Report — 2024 | ThatCarHitMe.com