Monthly Traffic Safety Analysis

31 CRASHES IN
AMHERST, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

In January 2024, Amherst experienced 31 crashes, a substantial increase from the 17 crashes reported in January 2023, marking an 82.35% rise year-over-year. Total injuries also saw a significant increase, climbing from 2 to 10. The most notable year-over-year shift was the 275% increase in crashes where 'No improper driving' was cited as a contributing factor, rising from 4 to 15.

31

82.4%was 17

Total Crash Events

0

Persons Killed

10

400.0%was 2

Persons Injured

0

Fatal Crash Events

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.

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

The overall trend indicates a significant increase in crash activity, with total crashes rising from 17 in January 2023 to 31 in January 2024, representing an 82.35% increase. This period also saw a five-fold increase in total injuries, from 2 to 10, while fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

10

Motorists Injured

Prior: 2400.0%

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

The peak day for crashes shifted from Monday with 6 crashes in January 2023 to Wednesday with 8 crashes in January 2024. The peak hour also changed, moving from 3 PM with 4 crashes in the prior period to 8 PM with 5 crashes in the current period. Notably, weekend crashes (Saturday and Sunday) saw a significant increase from 3 in the prior period to 10 in the current period.

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

There were no fatal crashes in either January 2023 or January 2024. However, the number of total injuries increased from 2 in the prior period to 10 in the current period. Minor injury crashes rose from 2 to 4, and possible injury crashes increased from 0 to 1, while crashes with no injuries increased from 14 to 26.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes12.9%
100.0%prior 2
Possible Injury1possible injury crashes3.2%
No Injury26no injury crashes83.9%
85.7%prior 14

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

Crashes attributed to 'No improper driving' saw a substantial increase, rising from 4 in January 2023 to 15 in January 2024, a 275% increase in count. Inattention-related crashes also increased from 4 to 6, a 50% rise in count. Conversely, crashes due to 'Driving too fast for conditions' decreased from 3 to 1, a 66.7% reduction in count, and 'Failed to yield right of way' crashes decreased from 2 to 1, a 50% reduction in count.

Officer-Reported Primary Contributing Cause

No improper driving15 (48.4%)
Inattention6 (19.4%)
Distracted2 (6.5%)
Followed too closely2 (6.5%)
Failed to yield right of way1 (3.2%)
Driving too fast for conditions1 (3.2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.2%)
Over-correcting/over-steering1 (3.2%)
Failure to keep in proper lane or running off road1 (3.2%)

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 occurring in 'Clear' weather increased from 7 to 10, while 'Cloudy' weather crashes quadrupled from 2 to 6. Crashes on 'Wet' road surfaces increased from 2 to 6, and 'Ice' related crashes increased from 1 to 4. Furthermore, crashes occurring in 'Dark - lighted roadway' conditions increased from 1 to 5.

Weather

Clear10 (32.3%)
42.9%prior 7
Cloudy6 (19.4%)
Snow5 (16.1%)
Snow/Sleet, hail (freezing rain or drizzle)4 (12.9%)
Rain2 (6.5%)
Rain/Snow1 (3.2%)
Cloudy/Snow1 (3.2%)
Snow/Rain1 (3.2%)
Clear/Cloudy1 (3.2%)

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

Lighting

Daylight16 (51.6%)
6.7%prior 15
Dark - roadway not lighted7 (22.6%)
Dark - lighted roadway5 (16.1%)
Dusk2 (6.5%)
Dark - unknown roadway lighting1 (3.2%)

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

Road Surface

Dry13 (41.9%)
44.4%prior 9
Wet6 (19.4%)
Snow5 (16.1%)
Ice4 (12.9%)
Slush3 (9.7%)

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

Vehicles & Demographics

Top Vehicle Makes (48 vehicles)

1
FORD7 (14.6%)
2
CHEVROLET6 (12.5%)
3
TOYOTA6 (12.5%)
20.0%prior 5
4
NISSAN5 (10.4%)
5
HONDA4 (8.3%)
-42.9%prior 7
6
HYUNDAI3 (6.3%)
7
SUBARU2 (4.2%)
8
BMW2 (4.2%)
9
MAZDA2 (4.2%)
10
BUIC2 (4.2%)

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

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

Sex Distribution (50 persons with recorded sex)

Male29 (58.0%)
61.1%prior 18
Female21 (42.0%)
23.5%prior 17

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 40 mph zones experienced the largest numerical increase, rising from 2 in the prior period to 7 in the current period, a 250% increase. Crashes in 30 mph zones also increased from 4 to 6, and 35 mph zones saw an increase from 6 to 7. Additionally, crashes were recorded in 5 mph, 15 mph, and 45 mph zones in the current period, which had no recorded crashes in the prior period, while 55 mph zones had 1 crash in the prior period but none in the current.

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: AMHERST, MA
  • Total crash records analyzed: 31
  • Total persons involved: 52
  • Total vehicles involved: 48

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: 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/amherst/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

ThatCarHitMe.com · An Injuria.ai Company

Amherst, MA Crash Report — January 2024 | ThatCarHitMe.com