ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LAWRENCE, MA · JANUARY 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/lawrence/january-2022-report
Monthly Traffic Safety Analysis
143 CRASHES IN
LAWRENCE, MA
JANUARY 2022
In January 2022, Lawrence experienced 143 total crashes, an increase of 30% compared to the 110 crashes recorded in January 2021. Despite the overall increase in crashes, total injuries decreased by 23.3%, from 60 in the prior period to 46 in the current period. A notable shift was the 166.7% increase in speeding-related crashes, rising from 3 to 8 year-over-year.
143
▲ 30.0%was 110
Total Crash Events
0
Persons Killed
46
▼ -23.3%was 60
Persons Injured
5
▼ -37.5%was 8
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crashes year-over-year, with total crashes rising from 110 in January 2021 to 143 in January 2022. This represents a 30% increase in crash incidents for the month. Fatalities remained at zero in both periods.
5
Hit-and-Run Crashes — January 2022
▼ -37.5% vs prior (8)
Hit-and-run crashes decreased by 37.5%, from 8 incidents in January 2021 to 5 in January 2022. The hit-and-run rate also decreased, falling from 7.3% of total crashes in the prior period to 3.5% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
3
Pedestrians Injured
43
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Monday with 22 crashes in January 2021 to Tuesday with 29 crashes in January 2022. The peak hour remained 4 p.m. in both periods, though the count decreased slightly from 14 crashes in the prior period to 13 crashes in the current period. Crashes on Tuesdays saw a significant increase of 15 incidents, rising from 14 to 29.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either January 2021 or January 2022. Serious injury crashes doubled from 3 in the prior period to 6 in the current period. Conversely, minor injury crashes decreased by 45.8%, from 24 to 13, and possible injury crashes decreased by 16.7%, from 12 to 10.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving,' increased by 4 crashes, from 30 in January 2021 to 34 in January 2022. 'Failed to yield right of way' crashes increased by 3, from 10 to 13, and 'Inattention' crashes increased by 2, from 11 to 13. 'Distracted' driving crashes saw a 400% increase, rising from 1 to 5 incidents year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 15, from 86 in January 2021 to 101 in January 2022. Crashes on 'Wet' road surfaces increased by 9, from 12 to 21, representing a 75% increase. Crashes on 'Ice' increased significantly by 600%, rising from 1 to 7 incidents year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased by 31.4%, from 312 in January 2021 to 410 in January 2022. The 0-15 age group saw a 78.9% increase in persons involved, rising from 19 to 34. Honda remained the most frequently involved vehicle make, with its count increasing by 19, from 67 to 86.
Top Vehicle Makes (285 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records
44 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (369 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones increased by 14, from 87 in January 2021 to 101 in January 2022. Crashes in 25 mph zones increased by 83.3%, from 6 to 11. Higher speed zones also saw increases, with crashes in 55 mph zones doubling from 3 to 6, and crashes in 65 mph zones increasing by 150%, from 2 to 5.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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 2022-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-01-31 (31 days)
- Geographic scope: LAWRENCE, MA
- Total crash records analyzed: 143
- Total persons involved: 410
- Total vehicles involved: 285
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). "LAWRENCE, MA Crash Intelligence Report: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lawrence/january-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: 2022-01-01 – 2022-01-31
Generated: June 21, 2026 · All rights reserved