Yearly Traffic Safety Analysis

706 CRASHES IN
MILTON, MA
2022

All metrics benchmarked against2021

In 2022, Milton recorded 706 total crashes, a 5.1% decrease from the 744 crashes reported in 2021. While the overall number of collisions declined, the outcomes were more severe, with total fatalities increasing from two in the prior year to three in 2022. The number of reported injuries also rose from 295 to 316.

706

-5.1%was 744

Total Crash Events

3

50.0%was 2

Persons Killed

316

7.1%was 295

Persons Injured

53

23.3%was 43

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 30 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Milton saw a downward trend, decreasing by 5.1% from 744 in 2021 to 706 in 2022. However, the severity of these incidents worsened, with total injuries rising by 7.1% (from 295 to 316) and fatalities increasing from two to three year-over-year.

53

Hit-and-Run Crashes — 2022

23.3% vs prior (43)

Hit-and-run incidents increased in 2022 compared to the previous year. The total count of hit-and-run crashes rose by 23.3%, from 43 in 2021 to 53 in 2022. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also trended upward, increasing from 5.8% in 2021 to 7.5% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

3

Motorists Killed

Prior: 250.0%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 4-50.0%

3

Cyclists Injured

Prior: 8-62.5%

309

Motorists Injured

Prior: 2829.6%

2

Other Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two years. In 2022, the peak day for crashes was Monday with 119 incidents, a change from 2021 when Thursday was the peak day with 122 incidents. The busiest hour for collisions also shifted slightly earlier, moving from 4 p.m. in 2021 (56 crashes) to 3 p.m. in 2022 (57 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased in 2022 compared to the prior year. The number of fatal crashes rose from two to three, and the proportion of crashes resulting in serious injuries increased from 0.8% (6 crashes) in 2021 to 1.3% (9 crashes) in 2022. Correspondingly, the share of crashes with no reported injuries decreased from 66.5% of all crashes in 2021 to 63.5% in 2022.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.4%
50.0%prior 2
Serious Injury9serious injury crashes1.3%
50.0%prior 6
Minor Injury147minor injury crashes20.8%
4.3%prior 141
Possible Injury69possible injury crashes9.8%
-16.9%prior 83
No Injury448no injury crashes63.5%
-9.5%prior 495

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

While 'No improper driving' remained the most cited factor in both periods, its count dropped by 23.2% from 271 incidents in 2021 to 208 in 2022. Crashes attributed to 'Followed too closely' increased in count by 26.7%, rising from 86 to 109 incidents and becoming the second-most frequent factor. Additionally, crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased in count by 57.9%, from 19 to 30 incidents.

Officer-Reported Primary Contributing Cause

No improper driving208 (29.5%)-23.2%prior 271
Followed too closely109 (15.4%)26.7%prior 86
Inattention61 (8.6%)-6.2%prior 65
Failed to yield right of way50 (7.1%)-23.1%prior 65
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner30 (4.2%)57.9%prior 19
Failure to keep in proper lane or running off road26 (3.7%)-21.2%prior 33
Disregarded traffic signs, signals, road markings20 (2.8%)81.8%prior 11
Fatigued/asleep17 (2.4%)70.0%prior 10
Other improper action16 (2.3%)33.3%prior 12
Distracted15 (2.1%)-16.7%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring during daylight on dry roads. In 2022, 80.2% of crashes happened on dry surfaces, a slight increase in share from 78.5% in 2021. Crashes on wet roads decreased from 136 incidents in 2021 to 107 in 2022, while crashes in rainy conditions also saw a notable drop from 99 to 59 incidents.

Weather

Clear361 (51.5%)
4.6%prior 345
Clear/Clear178 (25.4%)
-5.8%prior 189
Cloudy58 (8.3%)
26.1%prior 46
Rain29 (4.1%)
-51.7%prior 60
Rain/Cloudy13 (1.9%)
-7.1%prior 14
Snow11 (1.6%)
57.1%prior 7
Cloudy/Rain9 (1.3%)
-35.7%prior 14
Clear/Cloudy8 (1.1%)
Rain/Rain5 (0.7%)
-66.7%prior 15
Cloudy/Cloudy4 (0.6%)
-80.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight433 (61.7%)
-3.1%prior 447
Dark - lighted roadway199 (28.3%)
-16.0%prior 237
Dark - roadway not lighted33 (4.7%)
-10.8%prior 37
Dusk26 (3.7%)
136.4%prior 11
Dawn10 (1.4%)
25.0%prior 8
Dark - unknown roadway lighting1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry566 (80.5%)
-3.1%prior 584
Wet107 (15.2%)
-21.3%prior 136
Snow14 (2.0%)
0.0%prior 14
Ice13 (1.8%)
Slush2 (0.3%)
Sand, mud, dirt, oil, gravel1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Toyota, Honda, and Ford being the top three most frequent makes in both 2021 and 2022. The age demographics of persons involved in crashes showed a slight shift, as the proportion of individuals in the 16-20 age group decreased from representing 11.1% of all persons in 2021 to 8.7% in 2022. The 26-34 age group remained the largest cohort, accounting for approximately 19% of individuals in both years.

Top Vehicle Makes (1,387 vehicles)

1
TOYOTA246 (17.7%)
6.0%prior 232
2
HONDA191 (13.8%)
-6.8%prior 205
3
FORD151 (10.9%)
13.5%prior 133
4
CHEVROLET97 (7%)
15.5%prior 84
5
NISSAN94 (6.8%)
-16.8%prior 113
6
JEEP69 (5%)
13.1%prior 61
7
HYUNDAI49 (3.5%)
16.7%prior 42
8
SUBARU33 (2.4%)
-26.7%prior 45
9
DODGE31 (2.2%)
-16.2%prior 37
10
VOLKSWAGEN30 (2.2%)
-16.7%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (1,582 persons with recorded sex)

Male915 (57.8%)
-9.1%prior 1,007
Female667 (42.2%)
-6.7%prior 715

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 55 mph speed zone accounted for the highest number of crashes in both periods, with 205 incidents in 2022 and 201 in 2021. There was a notable decrease in crashes within 30 mph zones, which fell from 199 in 2021 to 148 in 2022. In 2022, one fatal crash was recorded in a 35 mph zone, whereas in 2021, fatal crashes were recorded in both 35 mph and 40 mph zones.

Fatal crashes by zone: 35 mph: 1 of 113 (0.885%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: MILTON, MA
  • Total crash records analyzed: 706
  • Total persons involved: 1,762
  • Total vehicles involved: 1,387

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). "MILTON, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/milton/2022-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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Milton, MA Crash Report — 2022 | ThatCarHitMe.com