ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELMSFORD, MA · MARCH 2026
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/chelmsford/march-2026-report
Monthly Traffic Safety Analysis
66 CRASHES IN
CHELMSFORD, MA
MARCH 2026
Total crashes in CHELMSFORD increased from 41 in March 2025 to 66 in March 2026, marking a 60.98% rise year-over-year. The most significant shift was the increase in total fatalities, which rose from 0 in the prior period to 2 in the current period. This indicates a notable increase in crash frequency and severity.
66
▲ 61.0%was 41
Total Crash Events
2
Persons Killed
16
▲ 23.1%was 13
Persons Injured
5
▲ 150.0%was 2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for CHELMSFORD indicates an upward trend in March 2026 compared to March 2025. Total crashes increased by 60.98%, from 41 to 66. This period also saw a concerning rise in total fatalities from 0 to 2, and total injuries from 13 to 16.
5
Hit-and-Run Crashes — March 2026
▲ 150.0% vs prior (2)
Hit-and-run crashes increased year-over-year, rising from 2 incidents in March 2025 to 5 incidents in March 2026. Consequently, the hit-and-run rate also increased from 4.9% to 7.6% of all crashes.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Pedestrians Injured
1
Cyclists Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year. In March 2026, the peak day for crashes was Friday with 21 incidents, while in March 2025, Sunday had the highest count with 10 crashes. The peak hour for crashes also changed from 5 p.m. with 4 crashes in March 2025 to 3 p.m. with 8 crashes in March 2026.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes notably increased in March 2026 compared to March 2025. Fatal crashes rose from 0 to 2, and serious injury crashes increased from 1 to 4. Minor injury crashes also saw a slight increase from 6 to 7, while crashes resulting in no injury increased from 33 to 51.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw significant changes in crash counts year-over-year. Crashes attributed to "Driving too fast for conditions" increased from 4 to 17, representing a 325% change in count. "Failure to keep in proper lane or running off road" also rose from 2 to 6 crashes, a 200% change in count. Conversely, "Followed too closely" decreased from 9 to 6 crashes, a 33.3% change in count, and "Failed to yield right of way" decreased from 7 to 4 crashes, a 42.9% change in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Clear weather conditions remained the most frequent for crashes, with "Clear/Clear" incidents increasing from 21 to 30. There was a notable increase in crashes under adverse road surface conditions, with "Snow" and "Ice" conditions appearing in 8 and 7 crashes respectively in March 2026, compared to 0 in March 2025. Daylight remained the predominant lighting condition for crashes, increasing from 25 to 41 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 82 in March 2025 to 117 in March 2026. HONDA and TOYOTA remained among the top vehicle makes involved, with HONDA increasing from 13 to 21 vehicles and TOYOTA from 15 to 20 vehicles. NISSAN and FORD, however, saw decreases in their involvement, from 7 to 5 and 8 to 5 vehicles respectively.
Top Vehicle Makes (117 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (159 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes at 65 mph speed limits increased from 15 in March 2025 to 25 in March 2026, and crashes at 30 mph limits rose from 10 to 22. Fatal crashes occurred at 20 mph (1 crash) and 40 mph (1 crash) speed zones in March 2026, whereas no fatal crashes were recorded across any speed zone in March 2025.
Fatal crashes by zone: 20 mph: 1 of 1 (100%) · 40 mph: 1 of 1 (100%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-03-01 through 2026-03-31 (31 days)
- Geographic scope: CHELMSFORD, MA
- Total crash records analyzed: 66
- Total persons involved: 174
- Total vehicles involved: 117
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). "CHELMSFORD, MA Crash Intelligence Report: March 2026." Published June 21, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelmsford/march-2026-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: 2026-03-01 – 2026-03-31
Generated: June 21, 2026 · All rights reserved