Yearly Traffic Safety Analysis

273 CRASHES IN
LANCASTER, MA
2023

All metrics benchmarked against2022

In 2023, Lancaster recorded 273 total traffic crashes, a 3.4% increase from the 264 crashes reported in 2022. While total collisions and the number of people injured (90, up from 75) saw an increase, the number of fatalities decreased from three in the prior year to one in the current year. A notable shift was the 20% year-over-year increase in total injuries despite the drop in deaths.

273

3.4%was 264

Total Crash Events

1

-66.7%was 3

Persons Killed

90

20.0%was 75

Persons Injured

9

125.0%was 4

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Lancaster show a slight increase, with total collisions rising by 3.4% from 264 in 2022 to 273 in 2023. This was accompanied by a more significant 20% increase in the number of people injured, which grew from 75 to 90. However, the number of fatalities saw a substantial decrease from three to one over the same period.

9

Hit-and-Run Crashes — 2023

125.0% vs prior (4)

The number of hit-and-run incidents increased significantly between the two periods. The count of hit-and-run crashes rose from 4 in 2022 to 9 in 2023. Correspondingly, the hit-and-run rate, measured as a percentage of total crashes, more than doubled from 1.5% to 3.3%.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 3-66.7%

1

Cyclists Injured

Prior: 10.0%

89

Motorists Injured

Prior: 7321.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 changes year-over-year. The peak time for collisions remained consistent at the 3 p.m. hour in both 2022 and 2023, with 23 crashes each year. However, the most frequent day for crashes shifted from Wednesday (46 crashes) in 2022 to Thursday (56 crashes) in 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes shifted between the two periods, with a notable decrease in fatal incidents. Fatal crashes dropped from 3 in 2022 to 1 in 2023, and the corresponding fatal crash rate per 100 crashes fell from 1.14 to 0.37. Conversely, the number of serious injury crashes doubled from 2 to 4, and minor injury crashes increased from 27 to 45, representing a rise in their share of total crashes from 10.2% to 16.5%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
-66.7%prior 3
Serious Injury4serious injury crashes1.5%
100.0%prior 2
Minor Injury45minor injury crashes16.5%
66.7%prior 27
Possible Injury23possible injury crashes8.4%
-28.1%prior 32
No Injury199no injury crashes72.9%
1.0%prior 197

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors for crashes remained consistent year-over-year, with 'No improper driving,' 'Followed too closely,' and 'Failed to yield right of way' as the top three reported factors in both 2022 and 2023. While the top rankings were stable, the count of crashes attributed to 'Inattention' rose from 19 to 24, and those involving a 'Distracted' driver increased from 8 to 12. Crashes related to 'Failure to keep in proper lane' also saw an increase in count from 11 to 16.

Officer-Reported Primary Contributing Cause

No improper driving65 (23.8%)-3.0%prior 67
Followed too closely36 (13.2%)2.9%prior 35
Failed to yield right of way34 (12.5%)3.0%prior 33
Inattention24 (8.8%)26.3%prior 19
Failure to keep in proper lane or running off road16 (5.9%)45.5%prior 11
Driving too fast for conditions13 (4.8%)44.4%prior 9
Distracted12 (4.4%)50.0%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner9 (3.3%)-30.8%prior 13
Other improper action9 (3.3%)
Disregarded traffic signs, signals, road markings9 (3.3%)28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained broadly similar across both years, with the majority of incidents occurring in 'Clear' weather (189 in 2023 vs. 178 in 2022) and during 'Daylight' hours (182 vs. 172). However, there was a noticeable increase in crashes occurring on 'Wet' road surfaces, which rose from 39 incidents in 2022 to 54 in 2023. The proportion of crashes in the rain also increased, from 5.7% of all crashes in the prior year to 8.1% in the current year.

Weather

Clear189 (69.5%)
6.2%prior 178
Cloudy30 (11.0%)
-11.8%prior 34
Rain22 (8.1%)
46.7%prior 15
Snow10 (3.7%)
-9.1%prior 11
Cloudy/Rain5 (1.8%)
Snow/Sleet, hail (freezing rain or drizzle)3 (1.1%)
Sleet, hail (freezing rain or drizzle)3 (1.1%)
Rain/Other2 (0.7%)
Fog, smog, smoke2 (0.7%)
Rain/Snow1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight182 (66.7%)
5.8%prior 172
Dark - roadway not lighted56 (20.5%)
7.7%prior 52
Dark - lighted roadway20 (7.3%)
5.3%prior 19
Dusk10 (3.7%)
-16.7%prior 12
Dawn4 (1.5%)
-20.0%prior 5
Dark - unknown roadway lighting1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry200 (73.3%)
2.0%prior 196
Wet54 (19.8%)
38.5%prior 39
Snow16 (5.9%)
14.3%prior 14
Slush2 (0.7%)
Water (standing, moving)1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Ford, and Honda in both 2022 and 2023, although the number of Toyotas involved decreased from 88 to 62. In terms of driver and passenger demographics, the number of individuals aged 26-34 involved in crashes increased from 86 to 105. The 16-20 age group also saw an increase in involvement, from 39 individuals in 2022 to 52 in 2023.

Top Vehicle Makes (451 vehicles)

1
TOYOTA62 (13.7%)
-29.5%prior 88
2
FORD53 (11.8%)
1.9%prior 52
3
HONDA44 (9.8%)
-4.3%prior 46
4
CHEVROLET42 (9.3%)
82.6%prior 23
5
JEEP32 (7.1%)
88.2%prior 17
6
SUBARU31 (6.9%)
24.0%prior 25
7
NISSAN31 (6.9%)
34.8%prior 23
8
HYUNDAI20 (4.4%)
5.3%prior 19
9
GMC13 (2.9%)
44.4%prior 9
10
MAZDA11 (2.4%)
22.2%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (487 persons with recorded sex)

Male296 (60.8%)
1.7%prior 291
Female191 (39.2%)
0.5%prior 190

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones was largely consistent, with 30 mph zones (102 crashes in 2023 vs. 97 in 2022) and 55 mph zones (72 crashes in both years) accounting for the highest volumes. There was a significant shift in the location of fatal crashes. In 2022, two fatal crashes occurred in 30 mph zones and one in a 55 mph zone, whereas the single fatal crash in 2023 occurred in a 65 mph zone.

Fatal crashes by zone: 65 mph: 1 of 9 (11.111%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: LANCASTER, MA
  • Total crash records analyzed: 273
  • Total persons involved: 522
  • Total vehicles involved: 451

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lancaster/2023-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 — 2023 | ThatCarHitMe.com