ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LAWRENCE, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
1,839 CRASHES IN
LAWRENCE, MA
2023
In Lawrence, total traffic crashes increased by 15.8% from 1,588 in 2022 to 1,839 in 2023. During this period, the number of persons killed in crashes rose from one to three. The most notable shift was a 41.3% increase in the count of crashes attributed to disregarding traffic signs or signals, which grew from 46 incidents in 2022 to 65 in 2023.
1,839
▲ 15.8%was 1,588
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
639
▲ 15.8%was 552
Persons Injured
70
▲ 32.1%was 53
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. 19 crashes with unreported severity are 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, traffic collisions in Lawrence showed a rising trend from 2022 to 2023. Total crashes increased by 15.8%, from 1,588 to 1,839. Correspondingly, the number of people injured rose by 15.8% from 552 to 639, and fatalities increased from one to three.
70
Hit-and-Run Crashes — 2023
▲ 32.1% vs prior (53)
Hit-and-run incidents increased from 2022 to 2023. The total count of hit-and-run crashes rose by 32.1% from 53 to 70. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also trended upward from 3.3% to 3.8%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
42
Pedestrians Injured
11
Cyclists Injured
580
Motorists Injured
6
Other Injured
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 between the two years. While the peak hour for crashes remained the 4 p.m. hour in both 2022 (124 crashes) and 2023 (148 crashes), the peak day of the week shifted from Friday in 2022 (257 crashes) to Monday in 2023 (299 crashes).
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
Crash severity worsened from 2022 to 2023. The number of fatal crashes increased from one to three, and the fatal crash rate rose from 0.06% to 0.16%. While the share of serious injury crashes decreased slightly from 2.5% to 2.3%, the proportion of crashes involving possible injuries increased from 5.5% to 6.1%. The share of crashes with no injuries remained stable, moving from 73.6% to 74.0%.
Outcome by Severity (Crash Events)
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 leading contributing factors remained consistent, though their counts shifted. Crashes attributed to 'Failed to yield right of way' increased by 14.8%, from 142 in 2022 to 163 in 2023. More significantly, the count of crashes involving 'Disregarded traffic signs, signals, road markings' grew by 41.3% from 46 to 65. Conversely, crashes involving 'Inattention' saw a slight decrease in count from 179 to 172.
Officer-Reported Primary Contributing Cause
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
There was a noticeable shift in crash conditions year-over-year. The proportion of crashes occurring on wet road surfaces increased from 13.3% of all crashes in 2022 to 20.5% in 2023. Correspondingly, crashes on dry roads decreased as a share of the total, from 83.5% to 75.8%. Lighting conditions for crashes remained proportionally similar, with about 65% of incidents in both years occurring during daylight.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
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—Honda, Toyota, and Ford—remained the same in both 2022 and 2023, with the number of vehicles from each make increasing in line with the overall rise in crashes. The age distribution of persons involved in crashes also remained broadly consistent. For instance, the 26-34 age group was the most represented in both years, accounting for 17.0% of persons in 2022 and 15.7% in 2023.
Top Vehicle Makes (3,718 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
1,375 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,640 persons with recorded sex)
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
Crashes predominantly occurred in 30 mph speed zones in both periods, with the count in this zone increasing from 1,235 in 2022 to 1,557 in 2023. In 2023, two fatal crashes occurred in 30 mph zones and one occurred in a 55 mph zone. In 2022, no fatal crashes were recorded in these specific speed zones.
Fatal crashes by zone: 30 mph: 2 of 1,557 (0.128%) · 55 mph: 1 of 43 (2.326%)
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: LAWRENCE, MA
- Total crash records analyzed: 1,839
- Total persons involved: 5,994
- Total vehicles involved: 3,718
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: 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/lawrence/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved