Monthly Traffic Safety Analysis

24 CRASHES IN
AMHERST, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, Amherst experienced 24 total crashes, a notable decrease from the 38 crashes recorded in March 2022, representing a 36.8% reduction. The most significant year-over-year shift was an 81.2% decrease in total injuries, falling from 16 in the prior period to 3 in the current period.

24

▼ -36.8%was 38

Total Crash Events

0

Persons Killed

3

▼ -81.3%was 16

Persons Injured

1

▼ -50.0%was 2

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Amherst showed a downward trend year-over-year, with total crashes decreasing from 38 in March 2022 to 24 in March 2023. This represents a 36.8% reduction in the total number of crashes.

1

Hit-and-Run Crashes — March 2023

▼ -50.0% vs prior (2)

Hit-and-run crashes decreased from 2 incidents in March 2022 to 1 incident in March 2023. Consequently, the hit-and-run rate also saw a slight decrease, falling from 5.3% to 4.2% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

2

Motorists Injured

Prior: 16↓-87.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Saturday in both periods, though the count decreased from 11 crashes in March 2022 to 7 crashes in March 2023. The peak crash hour shifted from 7 p.m. (4 crashes) in the prior period to 7 a.m. (3 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either March 2022 or March 2023. Total injuries saw a substantial decrease from 16 in the prior period to 3 in the current period. Minor injury crashes decreased from 9 to 2, and possible injury crashes, which accounted for 3 incidents in the prior period, were not reported in the current period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.2%
→0.0%prior 1
Minor Injury2minor injury crashes8.3%
↓-77.8%prior 9
No Injury20no injury crashes83.3%
↓-16.7%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor shifted from 'No improper driving' (10 crashes) in March 2022 to 'Inattention' (6 crashes) in March 2023. 'Inattention' crashes increased by 50% (from 4 to 6), while 'No improper driving' crashes decreased by 60% (from 10 to 4). 'Failed to yield right of way' decreased from 6 crashes to 5 crashes, a 16.7% reduction in count.

Officer-Reported Primary Contributing Cause

Inattention6 (25%)
Failed to yield right of way5 (20.8%)↓-16.7%prior 6
No improper driving4 (16.7%)↓-60.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (8.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.2%)
Distracted1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on dry road surfaces decreased from 29 incidents in March 2022 to 11 in March 2023, while crashes on wet surfaces slightly increased from 6 to 7. The proportion of crashes occurring under clear weather conditions decreased from 68.4% to 50% year-over-year. Crashes on icy roads increased from 1 to 3 incidents, and those occurring at 'Dark - lighted roadway' decreased from 12 to 5.

Weather

Clear12 (50.0%)
↓-53.8%prior 26
Rain2 (8.3%)
Snow2 (8.3%)
Snow/Rain2 (8.3%)
Cloudy2 (8.3%)
↓-66.7%prior 6
Snow/Sleet, hail (freezing rain or drizzle)1 (4.2%)
Clear/Cloudy1 (4.2%)
Cloudy/Rain1 (4.2%)
Fog, smog, smoke1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight17 (70.8%)
↓-19.0%prior 21
Dark - lighted roadway5 (20.8%)
↓-58.3%prior 12
Dawn2 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry11 (45.8%)
↓-62.1%prior 29
Wet7 (29.2%)
↑16.7%prior 6
Ice3 (12.5%)
Snow2 (8.3%)
Slush1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (42 vehicles)

1
TOYOTA9 (21.4%)
↓-18.2%prior 11
2
SUBARU6 (14.3%)
3
HONDA5 (11.9%)
↓-54.5%prior 11
4
JEEP2 (4.8%)
5
NISSAN2 (4.8%)
6
FORD2 (4.8%)
↓-71.4%prior 7
7
CHEVROLET2 (4.8%)
8
VOLKSWAGEN2 (4.8%)
9
VOLVO2 (4.8%)
10
MERCEDES-BENZ1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (50 persons with recorded sex)

Male27 (54.0%)
↓-40.0%prior 45
Female23 (46.0%)
↓-28.1%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 35 mph speed zone saw a significant decrease from 14 incidents in March 2022 to 3 in March 2023. The 30 mph zone experienced an increase in crashes from 4 to 7, while the 25 mph zone decreased from 11 to 7 crashes. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: AMHERST, MA
  • Total crash records analyzed: 24
  • Total persons involved: 53
  • Total vehicles involved: 42

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). "AMHERST, MA Crash Intelligence Report: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/amherst/march-2023-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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Amherst, MA Crash Report — March 2023 | ThatCarHitMe.com