ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELMSFORD, MA · OCTOBER 2022
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/october-2022-report
Monthly Traffic Safety Analysis
74 CRASHES IN
CHELMSFORD, MA
OCTOBER 2022
In October 2022, Chelmsford recorded 74 crashes, a 2.78% increase from the 72 crashes reported in October 2021. The most notable shift was the increase in total fatalities, which rose from 0 in the prior year to 2 in the current period. Total injuries decreased from 28 to 15 year-over-year.
74
▲ 2.8%was 72
Total Crash Events
2
Persons Killed
15
▼ -46.4%was 28
Persons Injured
6
▲ 200.0%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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Chelmsford saw a slight increase of 2.78% year-over-year, rising from 72 crashes in October 2021 to 74 crashes in October 2022. Despite this small increase in total crashes, the period saw a significant and concerning shift with two fatalities reported in October 2022, compared to none in October 2021. Conversely, total injuries decreased by 46.43%, from 28 to 15.
6
Hit-and-Run Crashes — October 2022
▲ 200.0% vs prior (2)
Hit-and-run crashes increased significantly year-over-year, rising by 200% from 2 incidents in October 2021 to 6 incidents in October 2022. Consequently, the hit-and-run rate more than doubled, increasing from 2.8% to 8.1% of all crashes. This indicates a clear upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
13
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes shifted year-over-year, with Friday becoming the peak day in October 2022 with 17 crashes, replacing Saturday which had 15 crashes in October 2021. Similarly, the peak hour for crashes moved from 4 p.m. (8 crashes) in October 2021 to 3 p.m. (11 crashes) in October 2022. This indicates a shift in when crashes are most concentrated during the week and day.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution saw a critical change, with fatal crashes increasing from 0 in October 2021 to 2 in October 2022, representing 2.7% of all crashes. Minor injury crashes decreased from 15 (20.8% share) to 8 (10.8% share) year-over-year, while possible injury crashes decreased from 9 (12.5% share) to 4 (5.4% share). Crashes with no injury increased from 47 (65.3% share) to 60 (81.1% share), indicating a shift towards less severe outcomes for non-fatal incidents.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw significant shifts, with 'Followed too closely' crashes increasing by 128.6% from 7 to 16, and 'Inattention' crashes rising by 85.7% from 7 to 13. Conversely, 'No improper driving' as a factor decreased by 55.6% from 18 to 8, and 'Failed to yield right of way' decreased by 45.5% from 11 to 6. These changes led to 'Followed too closely' and 'Inattention' becoming the top two factors in October 2022, displacing 'No improper driving' from its prior top position.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on wet road surfaces increased by 50%, from 12 in October 2021 to 18 in October 2022. The number of crashes in daylight conditions increased from 41 to 49, while crashes in dark conditions (totaling Dark - lighted roadway, Dark - roadway not lighted, Dark - unknown roadway lighting) slightly decreased from 24 to 20. The overall number of crashes occurring in clear weather conditions remained stable at 54 in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 155 to 168 year-over-year. Notable shifts in age distribution include an increase in the 21-25 age group from 12 to 23 persons and the 26-34 age group from 19 to 29 persons. Toyota remained the top vehicle make involved in crashes, with its count increasing from 16 to 23, while Honda also saw an increase from 11 to 16 vehicles involved.
Top Vehicle Makes (141 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (150 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 65 mph speed zones increased from 13 in October 2021 to 21 in October 2022. This speed zone also saw 2 fatal crashes in the current period, whereas there were none in the prior period. Conversely, crashes in 35 mph speed zones decreased from 23 to 11, and those in 30 mph speed zones decreased from 17 to 9.
Fatal crashes by zone: 65 mph: 2 of 21 (9.524%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-10-01 through 2022-10-31 (31 days)
- Geographic scope: CHELMSFORD, MA
- Total crash records analyzed: 74
- Total persons involved: 168
- Total vehicles involved: 141
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: October 2022." Published June 21, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelmsford/october-2022-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: 2022-10-01 – 2022-10-31
Generated: June 21, 2026 · All rights reserved