Yearly Traffic Safety Analysis

553 CRASHES IN
LUDLOW, MA
2022

All metrics benchmarked against2021

In 2022, Ludlow recorded 553 total traffic crashes, a 2.6% increase from the 539 crashes in 2021. While total fatalities decreased from three to one, the number of people injured rose by 21.2%. The most notable year-over-year shift was a 71.4% increase in hit-and-run crashes, which grew from 21 incidents in 2021 to 36 in 2022.

553

2.6%was 539

Total Crash Events

1

-66.7%was 3

Persons Killed

137

21.2%was 113

Persons Injured

36

71.4%was 21

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 42 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

The overall trend in Ludlow shows a modest increase in total crashes, rising 2.6% from 539 in 2021 to 553 in 2022. This increase in crash volume was accompanied by a more significant 21.2% rise in the number of people injured, from 113 to 137. Conversely, the number of fatalities resulting from crashes decreased from three in the prior year to one in the current year.

36

Hit-and-Run Crashes — 2022

71.4% vs prior (21)

Hit-and-run incidents increased substantially in 2022 compared to the previous year. The total count of hit-and-run crashes rose by 71.4%, from 21 in 2021 to 36 in 2022. Consequently, the hit-and-run rate as a percentage of all crashes also trended upward, increasing from 3.9% to 6.5%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 3-66.7%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

6

Cyclists Injured

Prior: 1500.0%

128

Motorists Injured

Prior: 11214.3%

1

Other Injured

Prior: 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 periods. The peak day for crashes moved from Friday (99 crashes) in 2021 to Tuesday (97 crashes) in 2022. Similarly, the peak hour for incidents shifted slightly later in the afternoon, from 2 PM (50 crashes) in the prior period to 3 PM (57 crashes) in the current period.

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 showed a mixed trend. The number of fatal crashes decreased from three in 2021 to one in 2022, with the fatal crash rate falling from 0.56% to 0.18%. However, the number of crashes resulting in serious injuries increased from seven to 11, and the total number of people injured in all crashes rose from 113 to 137.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
-66.7%prior 3
Serious Injury11serious injury crashes2%
57.1%prior 7
Minor Injury62minor injury crashes11.2%
1.6%prior 61
Possible Injury28possible injury crashes5.1%
0.0%prior 28
No Injury409no injury crashes74%
1.0%prior 405

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

In 2022, "Inattention" became the leading contributing factor with 126 crashes, surpassing "No improper driving" which was the top factor in 2021. The count of crashes attributed to "Failed to yield right of way" increased by 58.3%, rising from 24 incidents in 2021 to 38 in 2022. Crashes involving an "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" also saw a notable 42.9% increase in count, from 21 to 30.

Officer-Reported Primary Contributing Cause

Inattention126 (22.8%)0.8%prior 125
No improper driving123 (22.2%)-8.2%prior 134
Failed to yield right of way38 (6.9%)58.3%prior 24
Followed too closely32 (5.8%)23.1%prior 26
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner30 (5.4%)42.9%prior 21
Other improper action28 (5.1%)40.0%prior 20
Failure to keep in proper lane or running off road18 (3.3%)-21.7%prior 23
Distracted13 (2.4%)-31.6%prior 19
Visibility obstructed12 (2.2%)-14.3%prior 14
Disregarded traffic signs, signals, road markings10 (1.8%)100.0%prior 5

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 largely consistent year-over-year, with the majority of incidents in both periods occurring in daylight on dry roads. The number of crashes on dry surfaces was 438 in 2022 compared to 430 in 2021. One notable shift was an increase in crashes during dusk, which rose from 17 incidents in 2021 to 30 in 2022.

Weather

Clear360 (65.8%)
5.9%prior 340
Clear/Cloudy46 (8.4%)
53.3%prior 30
Cloudy41 (7.5%)
0.0%prior 41
Cloudy/Rain26 (4.8%)
18.2%prior 22
Rain24 (4.4%)
-20.0%prior 30
Clear/Other18 (3.3%)
-43.8%prior 32
Snow11 (2.0%)
10.0%prior 10
Rain/Cloudy3 (0.5%)
Snow/Sleet, hail (freezing rain or drizzle)2 (0.4%)
Clear/Rain2 (0.4%)

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

Lighting

Daylight375 (68.3%)
-1.3%prior 380
Dark - lighted roadway114 (20.8%)
-2.6%prior 117
Dusk30 (5.5%)
76.5%prior 17
Dark - roadway not lighted22 (4.0%)
57.1%prior 14
Dawn4 (0.7%)
-42.9%prior 7
Dark - unknown roadway lighting2 (0.4%)
Other2 (0.4%)

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

Road Surface

Dry438 (80.2%)
1.9%prior 430
Wet79 (14.5%)
1.3%prior 78
Snow12 (2.2%)
-20.0%prior 15
Ice8 (1.5%)
-11.1%prior 9
Slush6 (1.1%)
Other2 (0.4%)
Water (standing, moving)1 (0.2%)

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 saw a shift in rankings, with Honda becoming the most common make in 2022 with 127 vehicles, up from 97 in 2021. The demographic data shows an increased involvement for persons in the 16-20 age group (150 vs. 129) and those aged 45 and older. In contrast, the number of people aged 21-34 involved in crashes decreased from 323 to 261.

Top Vehicle Makes (987 vehicles)

1
HONDA127 (12.9%)
30.9%prior 97
2
TOYOTA120 (12.2%)
2.6%prior 117
3
FORD108 (10.9%)
2.9%prior 105
4
NISSAN87 (8.8%)
17.6%prior 74
5
CHEVROLET64 (6.5%)
-25.6%prior 86
6
HYUNDAI40 (4.1%)
-34.4%prior 61
7
SUBARU40 (4.1%)
0.0%prior 40
8
DODGE38 (3.9%)
11.8%prior 34
9
JEEP37 (3.7%)
-5.1%prior 39
10
VOLKSWAGEN25 (2.5%)
47.1%prior 17

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

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

Sex Distribution (1,074 persons with recorded sex)

Male613 (57.1%)
0.5%prior 610
Female460 (42.8%)
-1.9%prior 469
X / Unspecified1 (0.1%)

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

There was a significant shift in the speed zones where crashes occurred. The number of crashes in 25 mph zones doubled from 52 in 2021 to 104 in 2022. Crashes also increased in 35 mph zones (159 to 182), while decreasing in 30 mph zones (170 to 138) and 65 mph zones (68 to 48). The single fatal crash in 2022 occurred in a 30 mph zone.

Fatal crashes by zone: 30 mph: 1 of 138 (0.725%)

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: LUDLOW, MA
  • Total crash records analyzed: 553
  • Total persons involved: 1,222
  • Total vehicles involved: 987

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). "LUDLOW, 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/ludlow/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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Ludlow, MA Crash Report — 2022 | ThatCarHitMe.com