ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LAWRENCE, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
1,957 CRASHES IN
LAWRENCE, MA
2024
In 2024, Lawrence recorded 1,957 total traffic crashes, a 6.4% increase from the 1,839 crashes documented in 2023. While total crashes and injuries rose, the number of fatalities decreased from three to one. The most significant year-over-year change was a 76% increase in the count of crashes attributed to inattention, which rose from 172 incidents in 2023 to 303 in 2024.
1,957
▲ 6.4%was 1,839
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
715
▲ 11.9%was 639
Persons Injured
66
▼ -5.7%was 70
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. 33 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
Overall traffic safety trends in Lawrence show an increase in crash frequency year-over-year. Total crashes rose by 6.4%, from 1,839 in 2023 to 1,957 in 2024. This was accompanied by an 11.9% increase in total injuries, which grew from 639 to 715, even as the number of fatalities declined from three to one.
66
Hit-and-Run Crashes — 2024
▼ -5.7% vs prior (70)
Hit-and-run incidents showed a slight downward trend year-over-year. The total count of hit-and-run crashes decreased from 70 in 2023 to 66 in 2024. This resulted in a corresponding decrease in the hit-and-run rate, which fell from 3.8% of all crashes in the prior year to 3.4% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
43
Pedestrians Injured
9
Cyclists Injured
657
Motorists Injured
6
Other Injured
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 in Lawrence shifted slightly between the two periods. The peak day for collisions moved from Monday in 2023, which saw 299 crashes, to Friday in 2024 with 291 crashes. Similarly, the peak hour for crashes shifted an hour earlier, from 4 PM in the prior year (148 crashes) to 3 PM in the current year (160 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 profiles shifted between the two years, with a notable decrease in the most severe outcomes. Fatal crashes fell from 3 in 2023 to 1 in 2024, and serious injury crashes decreased from 42 to 33. Conversely, crashes classified as 'Possible Injury' saw an increase in count from 112 to 160. The overall proportion of crashes resulting in any level of injury (from possible to fatal) increased slightly from 25.0% in 2023 to 25.6% in 2024.
Outcome by Severity (Crash Events)
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
While the top contributing factors remained consistent, their counts shifted significantly year-over-year. Crashes attributed to 'Inattention' surged by 76% in count, rising from 172 in 2023 to 303 in 2024. Similarly, incidents involving 'Failed to yield right of way' increased by 66% in count, from 163 to 270. Another notable change was an 87% increase in the count of crashes due to 'Followed too closely,' which grew from 53 to 99.
Officer-Reported Primary Contributing Cause
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 environmental conditions during crashes showed a shift towards clearer weather and drier roads in 2024 compared to the prior year. Crashes on dry road surfaces accounted for 81.4% of all incidents in 2024, up from a 75.8% share in 2023. Correspondingly, the proportion of crashes on wet roads decreased from 20.5% to 15.0%. Lighting conditions remained largely consistent, with approximately two-thirds of crashes in both years occurring during daylight.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
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—Honda, Toyota, and Ford—remained consistent across both years, with their counts increasing in line with the overall rise in collisions. A notable demographic shift occurred in the age of persons involved; the proportion of individuals in the 26-34 and 35-44 age groups increased as a share of total persons in 2024 compared to 2023. Despite an increase in total crashes, the number of passengers involved decreased from 2,187 to 1,311.
Top Vehicle Makes (3,995 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
653 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,750 persons with recorded sex)
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
The vast majority of crashes in both periods occurred in 30 mph speed zones, with counts rising from 1,557 in 2023 to 1,620 in 2024. There was also a notable increase in crashes within 25 mph zones, which rose from 58 to 101 incidents. The single fatal crash in 2024 occurred in a 20 mph zone, a shift from 2023 when the three fatalities were recorded in 30 mph and 55 mph zones.
Fatal crashes by zone: 20 mph: 1 of 70 (1.429%)
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: LAWRENCE, MA
- Total crash records analyzed: 1,957
- Total persons involved: 5,373
- Total vehicles involved: 3,995
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: 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/lawrence/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved