Monthly Traffic Safety Analysis

86 CRASHES IN
ANDOVER, MA
MAY 2024

All metrics benchmarked againstMay 2023

Total crashes in May 2024 were 86, a decrease of 16.5% compared to 103 crashes in May 2023. Fatalities decreased significantly from 1 in May 2023 to 0 in May 2024. However, total injuries increased by 52% from 25 to 38 year-over-year.

86

▼ -16.5%was 103

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

38

▲ 52.0%was 25

Persons Injured

8

▲ 14.3%was 7

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 · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes decreased by 16.5% from 103 in May 2023 to 86 in May 2024. Fatalities decreased from 1 to 0, while total injuries increased from 25 to 38, representing a 52% rise.

8

Hit-and-Run Crashes — May 2024

▲ 14.3% vs prior (7)

Hit-and-run crashes increased from 7 in May 2023 to 8 in May 2024. Consequently, the hit-and-run rate also increased from 6.8% to 9.3% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

38

Motorists Injured

Prior: 24↑58.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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 Wednesday with 26 crashes in May 2023 to Tuesday with 19 crashes in May 2024. The peak hour remained 3 p.m. or 4 p.m. for both periods, with 10 crashes recorded at 3 p.m. in May 2024 and 10 crashes at 4 p.m. in May 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in May 2023 to 0 in May 2024. Serious injury crashes remained consistent at 2 for both periods. Minor injury crashes increased from 12 in May 2023 to 18 in May 2024, while possible injury crashes remained at 7 for both periods.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2.3%
→0.0%prior 2
Minor Injury18minor injury crashes20.9%
↑50.0%prior 12
Possible Injury7possible injury crashes8.1%
→0.0%prior 7
No Injury58no injury crashes67.4%
↓-28.4%prior 81

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Followed too closely,' saw a slight increase in count from 21 crashes in May 2023 to 22 crashes in May 2024. 'No improper driving' decreased from 17 crashes to 12 crashes, while 'Failed to yield right of way' increased from 14 crashes to 16 crashes. 'Inattention' crashes significantly decreased from 12 to 5 year-over-year.

Officer-Reported Primary Contributing Cause

Followed too closely22 (25.6%)↑4.8%prior 21
Failed to yield right of way16 (18.6%)↑14.3%prior 14
No improper driving12 (14%)↓-29.4%prior 17
Disregarded traffic signs, signals, road markings6 (7%)
Inattention5 (5.8%)↓-58.3%prior 12
Other improper action5 (5.8%)
Driving too fast for conditions3 (3.5%)
Failure to keep in proper lane or running off road3 (3.5%)↓-62.5%prior 8
Distracted2 (2.3%)↓-60.0%prior 5
Exceeded authorized speed limit2 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 66 in May 2023 to 43 in May 2024, while 'Rain' conditions saw an increase from 4 crashes to 8 crashes. Crashes during 'Daylight' conditions decreased from 78 to 67, but crashes in 'Dark - lighted roadway' conditions increased from 3 to 7. The number of crashes on 'Wet' road surfaces increased from 12 to 15.

Weather

Clear43 (51.8%)
↓-34.8%prior 66
Clear/Clear21 (25.3%)
↑10.5%prior 19
Rain8 (9.6%)
Cloudy5 (6.0%)
↓-50.0%prior 10
Rain/Cloudy3 (3.6%)
Cloudy/Rain1 (1.2%)
Clear/Cloudy1 (1.2%)
Rain/Rain1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash

Lighting

Daylight67 (77.9%)
↓-14.1%prior 78
Dark - roadway not lighted7 (8.1%)
↓-56.3%prior 16
Dark - lighted roadway7 (8.1%)
Dark - unknown roadway lighting2 (2.3%)
Dawn1 (1.2%)
Dusk1 (1.2%)
Other1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field

Road Surface

Dry69 (82.1%)
↓-23.3%prior 90
Wet15 (17.9%)
↑25.0%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 196 in May 2023 to 180 in May 2024. Honda remained the top make involved, increasing slightly from 31 to 33 vehicles. Toyota saw a minor decrease from 29 to 28 vehicles, and Ford decreased from 22 to 13 vehicles.

Top Vehicle Makes (180 vehicles)

1
HONDA33 (18.3%)
↑6.5%prior 31
2
TOYOTA28 (15.6%)
↓-3.4%prior 29
3
CHEVROLET14 (7.8%)
↑7.7%prior 13
4
FORD13 (7.2%)
↓-40.9%prior 22
5
JEEP11 (6.1%)
↑120.0%prior 5
6
SUBARU8 (4.4%)
↑14.3%prior 7
7
VOLKSWAGEN8 (4.4%)
↑33.3%prior 6
8
ACURA7 (3.9%)
9
NISSAN7 (3.9%)
↓-30.0%prior 10
10
GMC5 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records

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

Sex Distribution (205 persons with recorded sex)

Male104 (50.7%)
↓-10.3%prior 116
Female101 (49.3%)
↑3.1%prior 98

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone decreased from 43 in May 2023 to 35 in May 2024. Crashes in the 25 mph zone decreased from 15 to 10, and crashes in the 30 mph zone also decreased from 15 to 10. No fatal crashes were reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-05-01 through 2024-05-31 (31 days)
  • Geographic scope: ANDOVER, MA
  • Total crash records analyzed: 86
  • Total persons involved: 225
  • Total vehicles involved: 180

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). "ANDOVER, MA Crash Intelligence Report: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/andover/may-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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Andover, MA Crash Report — May 2024 | ThatCarHitMe.com