ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELMSFORD, 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/chelmsford/2023-annual-report
Yearly Traffic Safety Analysis
769 CRASHES IN
CHELMSFORD, MA
2023
In Chelmsford, total traffic crashes increased by 11.0% from 693 in 2022 to 769 in 2023. While the number of crashes and total injuries rose, the most notable year-over-year shift was a decrease in fatalities, which fell from 7 to 4. Concurrently, the number of people reported injured increased from 231 to 303.
769
▲ 11.0%was 693
Total Crash Events
4
▼ -42.9%was 7
Persons Killed
303
▲ 31.2%was 231
Persons Injured
33
▲ 17.9%was 28
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety trends in Chelmsford indicate a rise in overall crash volume year-over-year. Total crashes increased by 11.0%, from 693 to 769. This was accompanied by a 31.2% rise in the number of people injured, which grew from 231 to 303. In contrast, the number of fatalities decreased from 7 in 2022 to 4 in 2023.
33
Hit-and-Run Crashes — 2023
▲ 17.9% vs prior (28)
Hit-and-run incidents experienced a slight increase between the two periods. The total number of hit-and-run crashes rose from 28 in 2022 to 33 in 2023. The hit-and-run rate, as a percentage of all crashes, also trended slightly upward from 4.0% to 4.3%.
Vulnerable Road User Casualties
0
Cyclists Killed
4
Motorists Killed
6
Cyclists Injured
297
Motorists 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 distribution of crashes remained largely consistent between the two periods. Friday was the peak day for crashes in both 2022 (114 crashes) and 2023 (131 crashes). The peak hour for collisions shifted slightly, moving from 3 PM in the prior year (79 crashes) to 4 PM in the current year (70 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
The rate of fatal crashes decreased from 0.9% of all incidents in 2022 to 0.5% in 2023. However, the proportion of crashes resulting in minor injuries increased from a 14.0% share to an 18.9% share. Crashes involving serious injuries saw a slight proportional decrease from 1.9% to 1.3% of the total.
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 factor, "Followed too closely," remained stable with 140 incidents in 2022 and 141 in 2023. Other factors saw significant changes; crashes attributed to "Failed to yield right of way" increased in count by 64% (from 50 to 82), and incidents involving "Driving too fast for conditions" doubled in count (from 38 to 76). These shifts elevated their rankings among contributing factors compared to the prior year.
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
Crashes occurring under adverse road conditions increased in 2023 compared to 2022. The proportion of crashes on wet roads grew from 13.4% to 22.8% of all incidents, with the raw count increasing from 93 to 175. In contrast, the distribution of crashes by lighting conditions, such as daylight versus darkness, remained stable year-over-year.
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—Toyota, Honda, and Ford—were the same in both 2022 and 2023. Regarding the demographics of persons involved, there was a 35.4% increase in the 26-34 age group, rising from 260 individuals to 352. Conversely, the number of persons aged 0-15 involved in crashes decreased from 128 to 84.
Top Vehicle Makes (1,438 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
94 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,669 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
Year-over-year, crashes increased in both 30 mph zones (from 141 to 192) and 65 mph zones (from 183 to 214). There was a notable change in the location of fatal crashes: in 2022, all 6 fatalities in these zones occurred in the 65 mph zone. In 2023, the 4 fatalities were more distributed, with 2 in the 65 mph zone, 1 in a 40 mph zone, and 1 in a 30 mph zone.
Fatal crashes by zone: 30 mph: 1 of 192 (0.521%) · 40 mph: 1 of 34 (2.941%) · 65 mph: 2 of 214 (0.935%)
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: CHELMSFORD, MA
- Total crash records analyzed: 769
- Total persons involved: 1,815
- Total vehicles involved: 1,438
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: 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/chelmsford/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