ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · READING, MA · DECEMBER 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/reading/december-2022-report
Monthly Traffic Safety Analysis
57 CRASHES IN
READING, MA
DECEMBER 2022
December 2022 saw a 5% decrease in total crashes in READING, with 57 crashes compared to 60 in December 2021. Fatalities remained at zero in both periods, while total injuries were stable at 10. A notable shift was the 114.3% increase in crashes attributed to 'Inattention,' rising from 7 in December 2021 to 15 in December 2022.
57
▼ -5.0%was 60
Total Crash Events
0
Persons Killed
10
Persons Injured
1
▼ -66.7%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in READING decreased by 5%, from 60 in December 2021 to 57 in December 2022. Despite this reduction in crash count, the number of total injuries remained stable at 10 in both periods. Fatalities were zero in both December 2021 and December 2022, indicating no change in the most severe outcome.
1
Hit-and-Run Crashes — December 2022
▼ -66.7% vs prior (3)
Hit-and-run crashes decreased significantly from 3 incidents in December 2021 to 1 incident in December 2022. This represents a substantial reduction in the hit-and-run crash rate, which fell from 5% of all crashes in December 2021 to 1.8% in December 2022. The trend for hit-and-run incidents is clearly downward.
Vulnerable Road User Casualties
0
Motorists Killed
10
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted notably year-over-year. In December 2021, Saturday was the peak day for crashes with 15 incidents, but in December 2022, Friday became the peak day with 17 crashes. The peak crash hour also changed significantly, moving from 8 AM with 10 crashes in December 2021 to 5 PM with 13 crashes in December 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both December 2021 and December 2022. The total number of injuries was consistent at 10 for both periods. However, the distribution of injury severity changed: December 2021 recorded 1 serious injury, while December 2022 reported zero serious injuries, with a slight increase in minor injuries from 4 to 5.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The most significant shift in contributing factors was observed in 'Inattention,' which more than doubled from 7 crashes in December 2021 to 15 crashes in December 2022, an increase of 114.3%. Conversely, crashes where 'No improper driving' was cited decreased substantially by 70%, from 20 crashes in December 2021 to 6 in December 2022. 'Followed too closely' incidents saw a modest increase from 10 crashes to 11 crashes, a 10% rise.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in daylight decreased from 41 in December 2021 to 27 in December 2022, while crashes in 'Dark - lighted roadway' conditions increased from 13 to 22. Regarding weather, incidents during 'Rain/Rain' increased from 1 to 7, and 'Snow/Snow' incidents increased from 1 to 4. Correspondingly, crashes on dry road surfaces decreased from 42 to 38, while those on wet surfaces increased from 10 to 14, and snow-covered surfaces increased from 0 to 3.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes remained stable, with 113 in December 2021 and 112 in December 2022. Honda remained a top vehicle make, though its involvement decreased slightly from 19 to 18, while Toyota's involvement increased from 15 to 18. There was a notable shift in the age distribution of persons involved in crashes: individuals aged 0-15 decreased from 13 to 3, and those aged 16-20 decreased from 26 to 13. Conversely, persons aged 21-25 more than doubled from 10 to 22, and those aged 45-54 more than doubled from 10 to 21.
Top Vehicle Makes (112 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (130 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones saw minor shifts year-over-year. Crashes in the 30 mph speed zone decreased from 20 in December 2021 to 16 in December 2022. Incidents in the 55 mph zone also saw a slight decrease from 17 to 16 crashes. Conversely, crashes in the 35 mph and 65 mph zones each increased by one, from 5 to 6 in both categories. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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: 2022-12-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-12-01 through 2022-12-31 (31 days)
- Geographic scope: READING, MA
- Total crash records analyzed: 57
- Total persons involved: 135
- Total vehicles involved: 112
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). "READING, MA Crash Intelligence Report: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/reading/december-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: 2022-12-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved