ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELMSFORD, 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/chelmsford/2024-annual-report
Yearly Traffic Safety Analysis
646 CRASHES IN
CHELMSFORD, MA
2024
In 2024, Chelmsford recorded 646 total traffic crashes, a 16.0% decrease from the 769 crashes reported in 2023. This overall reduction in collisions was accompanied by a significant year-over-year shift in crash severity. The most notable change was the decline in traffic fatalities from 4 in the prior year to 1 in the current year.
646
▼ -16.0%was 769
Total Crash Events
1
▼ -75.0%was 4
Persons Killed
212
▼ -30.0%was 303
Persons Injured
38
▲ 15.2%was 33
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. 4 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
Traffic safety trends in Chelmsford show a significant improvement year-over-year. Total crashes fell by 16.0%, from 769 in 2023 to 646 in 2024. This downward trend extended to crash outcomes, with total injuries decreasing by 30.0% (from 303 to 212) and fatalities dropping from 4 to 1.
38
Hit-and-Run Crashes — 2024
▲ 15.2% vs prior (33)
While total crashes declined, hit-and-run incidents trended upward. The number of hit-and-run crashes increased by 15.2%, from 33 in 2023 to 38 in 2024. Consequently, the hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, rose from 4.3% to 5.9% year-over-year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
4
Pedestrians Injured
7
Cyclists Injured
201
Motorists 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 remained largely consistent year-over-year. Friday was the peak day for crashes in both 2024 (108 crashes) and 2023 (131 crashes). There was a minor shift in the peak hour for collisions, moving from the 4 p.m. hour in 2023 (70 crashes) to the 5 p.m. hour in 2024 (65 crashes), keeping the evening commute as the highest-risk time block.
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 decreased in 2024 compared to the previous year. The number of fatal crashes fell from 4 to 1, and the fatal crash rate dropped from 0.5% to 0.2% of all collisions. The proportion of crashes resulting in any injury also declined from 27.6% in 2023 to 24.6% in 2024, driven by a large reduction in 'Minor Injury' crashes from 145 to 77.
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
The leading contributing factors for crashes in Chelmsford were consistent across both periods. 'Followed too closely' remained the top factor, with its count increasing slightly from 141 to 147. 'Failed to yield right of way' also saw a small increase in count from 82 to 86. However, other major factors saw significant decreases in their incident counts, including 'Driving too fast for conditions' (from 76 to 42, a 44.7% drop in count) and 'Failure to keep in proper lane' (from 71 to 44, a 38.0% drop in count).
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
Crashes in 2024 were more concentrated in clear weather and on dry roads compared to the prior year. The proportion of crashes occurring on wet road surfaces decreased from 22.8% in 2023 to 15.5% in 2024. Similarly, the share of crashes happening during rainy weather fell from 18.3% to 11.6%. Conversely, the share of crashes on dry roads increased from 71.4% to 78.8% year-over-year.
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 collisions—Toyota, Honda, and Ford—remained the same in 2024 as in 2023, with the count for each decreasing in line with the overall trend. An analysis of persons involved in crashes shows a demographic shift; the proportion of individuals in the 16-20 age group decreased from 13.1% in 2023 to 9.6% in 2024. In contrast, the share of persons aged 65 and older increased from 11.1% to 12.5% of all individuals involved.
Top Vehicle Makes (1,259 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
106 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,444 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
Year-over-year, the distribution of crashes shifted slightly from higher to mid-range speed zones. The proportion of crashes in zones 55 mph or higher decreased from 43.8% in 2023 to 41.8% in 2024, with a notable drop in the 55 mph zone from 120 to 59 incidents. The single fatal crash in 2024 occurred in a 55 mph zone, whereas the four fatalities in 2023 were spread across 30, 40, and 65 mph zones.
Fatal crashes by zone: 55 mph: 1 of 59 (1.695%)
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: CHELMSFORD, MA
- Total crash records analyzed: 646
- Total persons involved: 1,568
- Total vehicles involved: 1,259
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: 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/chelmsford/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