ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ANDOVER, MA · MAY 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/andover/may-2022-report
Monthly Traffic Safety Analysis
95 CRASHES IN
ANDOVER, MA
MAY 2022
Total crashes in Andover increased by 25% from 76 in May 2021 to 95 in May 2022. While total injuries decreased by 9.5% from 21 to 19, hit-and-run crashes saw a significant increase of 83.3%, rising from 6 to 11 incidents. This indicates a notable shift in the nature of crashes reported.
95
▲ 25.0%was 76
Total Crash Events
0
Persons Killed
19
▼ -9.5%was 21
Persons Injured
11
▲ 83.3%was 6
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. 12 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Andover are trending upwards, with total crashes increasing by 25% year-over-year, from 76 crashes in May 2021 to 95 crashes in May 2022. Despite this rise in total incidents, the number of total injuries decreased slightly from 21 to 19, a 9.5% reduction.
11
Hit-and-Run Crashes — May 2022
▲ 83.3% vs prior (6)
Hit-and-run crashes increased significantly year-over-year, rising by 83.3% in count from 6 incidents in May 2021 to 11 in May 2022. Consequently, the hit-and-run rate also increased, from 7.9% of all crashes in May 2021 to 11.6% in May 2022, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
18
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted between the two periods. In May 2021, crashes peaked on Thursday with 17 incidents and at 4 PM with 9 incidents, while in May 2022, Tuesday became the peak day with 22 crashes and 8 AM was the peak hour with 12 crashes. This indicates a shift in peak activity from late afternoon to morning commute times and from Thursday to Tuesday.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Total fatalities remained at 0 in both May 2021 and May 2022. Total injuries decreased by 9.5%, from 21 to 19. Serious injuries (Severity A) decreased from 1 in May 2021 to 0 in May 2022, while minor injuries (Severity B) increased from 8 to 12, representing a 50% increase in count.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw notable changes year-over-year. Crashes attributed to 'Inattention' increased by 87.5% in count, from 8 to 15, and 'Failure to keep in proper lane or running off road' increased by 300% in count, from 2 to 8. Conversely, 'No improper driving' decreased by 23.5% in count, from 17 to 13, and 'Exceeded authorized speed limit' decreased by 50% in count, from 4 to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under 'Daylight' conditions increased by 38.2% in count, from 55 in May 2021 to 76 in May 2022. Similarly, incidents on 'Dry' road surfaces increased by 24.6% in count, from 69 to 86. There was a 75% decrease in crashes during 'Rain' conditions, from 4 to 1, and a 55.6% decrease in crashes in 'Dark - roadway not lighted' conditions, from 9 to 4.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 30.7%, from 137 in May 2021 to 179 in May 2022. Among vehicle makes, TOYOTA saw the largest increase in involvement, rising by 107.7% from 13 to 27 vehicles, while HONDA vehicles increased by 47.6% from 21 to 31. The age group '16-20' saw a 52.4% increase in persons involved, rising from 21 to 32, and the '45-54' age group increased by 68.2%, from 22 to 37.
Top Vehicle Makes (179 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
19 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (195 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events
Speed Limit Zones
There were no fatalities reported in any speed zone during either period. Crashes occurring in 65 mph zones decreased by 29.3% in count, from 41 in May 2021 to 29 in May 2022. Conversely, crashes in 30 mph zones increased by 130% in count, from 10 to 23, and those in 25 mph zones saw a 233.3% increase in count, rising from 3 to 10.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: ANDOVER, MA
- Total crash records analyzed: 95
- Total persons involved: 226
- Total vehicles involved: 179
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 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/andover/may-2022-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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-05-01 – 2022-05-31
Generated: June 21, 2026 · All rights reserved