Yearly Traffic Safety Analysis

254 CRASHES IN
LANCASTER, MA
2024

All metrics benchmarked against2023

In 2024, Lancaster recorded 254 total vehicle crashes, a 7.0% decrease from the 273 crashes documented in 2023. Despite the overall reduction in collisions, the number of people injured increased by 22.2%, rising from 90 to 110. Fatalities also doubled, with two individuals killed in 2024 compared to one in the prior year, marking the most notable shift in outcomes.

254

-7.0%was 273

Total Crash Events

2

100.0%was 1

Persons Killed

110

22.2%was 90

Persons Injured

11

22.2%was 9

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall number of crashes in Lancaster decreased by 7.0% year-over-year, falling from 273 in 2023 to 254 in 2024. However, this downward trend in crash volume was accompanied by a rise in crash severity. The total number of injuries grew by 22.2% (from 90 to 110), and fatalities increased from one to two during the same period.

11

Hit-and-Run Crashes — 2024

22.2% vs prior (9)

Hit-and-run incidents in Lancaster trended upward year-over-year. The total count of hit-and-run crashes increased by 22.2%, rising from 9 incidents in 2023 to 11 in 2024. The hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, also increased from 3.3% to 4.3% during this period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 1100.0%

2

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 10.0%

107

Motorists Injured

Prior: 8920.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two years. In 2024, the peak day for crashes was Friday with 50 incidents, a change from 2023 when Thursday was the peak day with 56 incidents. The most frequent time for crashes also shifted, moving from the 3 p.m. hour in 2023 (23 crashes) to the 5 p.m. hour in 2024 (22 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased in 2024 compared to the previous year. The number of fatal crashes doubled from one to two, and the fatal crash rate rose from 0.37 to 0.79 per 100 crashes. The proportion of crashes resulting in any level of injury (serious, minor, or possible) increased from 26.4% in 2023 to 29.9% in 2024. This was driven by a rise in serious injury crashes (from 4 to 6) and possible injury crashes (from 23 to 28).

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.8%
100.0%prior 1
Serious Injury6serious injury crashes2.4%
50.0%prior 4
Minor Injury42minor injury crashes16.5%
-6.7%prior 45
Possible Injury28possible injury crashes11%
21.7%prior 23
No Injury173no injury crashes68.1%
-13.1%prior 199

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors cited in crashes remained consistent year-over-year, with "No improper driving," "Followed too closely," and "Failed to yield right of way" as the top three in both periods. However, the count for each of these top factors decreased in 2024, with "No improper driving" falling from 65 to 44 incidents. One notable increase was in crashes involving a fatigued or asleep driver, which rose from 7 incidents in 2023 to 12 in 2024, a 71.4% increase in count.

Officer-Reported Primary Contributing Cause

No improper driving44 (17.3%)-32.3%prior 65
Followed too closely33 (13%)-8.3%prior 36
Failed to yield right of way30 (11.8%)-11.8%prior 34
Inattention26 (10.2%)8.3%prior 24
Failure to keep in proper lane or running off road16 (6.3%)0.0%prior 16
Driving too fast for conditions14 (5.5%)7.7%prior 13
Fatigued/asleep12 (4.7%)71.4%prior 7
Disregarded traffic signs, signals, road markings10 (3.9%)11.1%prior 9
Distracted10 (3.9%)-16.7%prior 12
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner10 (3.9%)11.1%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both 2024 (79.1%) and 2023 (73.3%) occurred on dry road surfaces. The proportion of crashes on wet roads saw a notable decrease, accounting for 13.4% of crashes in 2024 compared to 19.8% in 2023. Lighting conditions remained stable, with approximately 67% of crashes in both years occurring during daylight and 28% occurring in dark conditions. Crashes during clear weather were slightly more prevalent in 2024 (72.0%) than in 2023 (69.2%).

Weather

Clear183 (72.6%)
-3.2%prior 189
Cloudy17 (6.7%)
-43.3%prior 30
Rain16 (6.3%)
-27.3%prior 22
Snow9 (3.6%)
-10.0%prior 10
Clear/Clear8 (3.2%)
Cloudy/Rain6 (2.4%)
20.0%prior 5
Rain/Cloudy4 (1.6%)
Rain/Sleet, hail (freezing rain or drizzle)2 (0.8%)
Blowing sand, snow1 (0.4%)
Clear/Cloudy1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight170 (66.9%)
-6.6%prior 182
Dark - roadway not lighted50 (19.7%)
-10.7%prior 56
Dark - lighted roadway19 (7.5%)
-5.0%prior 20
Dusk7 (2.8%)
-30.0%prior 10
Dawn5 (2.0%)
Dark - unknown roadway lighting3 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry201 (79.4%)
0.5%prior 200
Wet34 (13.4%)
-37.0%prior 54
Snow12 (4.7%)
-25.0%prior 16
Slush2 (0.8%)
Ice2 (0.8%)
Sand, mud, dirt, oil, gravel2 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Ford, and Honda in both years, with only minor changes in their rankings and counts. There was a notable shift in the age distribution of persons involved in crashes; the 35-44 age group became the largest cohort in 2024 with 102 individuals, up from 82 in 2023. Conversely, the 26-34 age group decreased from being the largest group (105 individuals) in 2023 to the third largest (82 individuals) in 2024.

Top Vehicle Makes (440 vehicles)

1
TOYOTA63 (14.3%)
1.6%prior 62
2
HONDA57 (13%)
29.5%prior 44
3
FORD52 (11.8%)
-1.9%prior 53
4
CHEVROLET32 (7.3%)
-23.8%prior 42
5
NISSAN23 (5.2%)
-25.8%prior 31
6
SUBARU23 (5.2%)
-25.8%prior 31
7
GMC18 (4.1%)
38.5%prior 13
8
JEEP16 (3.6%)
-50.0%prior 32
9
HYUNDAI15 (3.4%)
-25.0%prior 20
10
KIA14 (3.2%)
100.0%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (499 persons with recorded sex)

Male289 (57.9%)
-2.4%prior 296
Female210 (42.1%)
9.9%prior 191

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

In both 2024 and 2023, the highest number of crashes occurred in 30 mph zones, with 89 and 102 crashes respectively. Crashes in 55 mph zones were the second most common in both years, decreasing from 72 to 61. The locations of fatal crashes shifted to lower speed zones in 2024. While the single fatal crash in 2023 occurred in a 65 mph zone, the two fatal crashes in 2024 took place in 45 mph and 55 mph zones.

Fatal crashes by zone: 45 mph: 1 of 12 (8.333%) · 55 mph: 1 of 61 (1.639%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: LANCASTER, MA
  • Total crash records analyzed: 254
  • Total persons involved: 538
  • Total vehicles involved: 440

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). "LANCASTER, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lancaster/2024-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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Lancaster, MA Crash Report — 2024 | ThatCarHitMe.com