ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH READING, 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/north-reading/2023-annual-report
Yearly Traffic Safety Analysis
197 CRASHES IN
NORTH READING, MA
2023
In North Reading, total traffic crashes remained stable, with 197 incidents in 2023 compared to 196 in 2022, an increase of just one crash. Despite the consistent crash volume, the number of resulting fatalities decreased from two to one, and total injuries fell by 16.7% from 54 to 45. The most significant year-over-year shift was this reduction in overall crash severity, even as the total number of collisions held steady.
197
▲ 0.5%was 196
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
45
▼ -16.7%was 54
Persons Injured
6
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. 6 crashes with unreported severity are 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
The overall trend in crash volume in North Reading was stable from 2022 to 2023, with total incidents increasing by only one crash from 196 to 197. However, the severity of these crashes trended downward. The number of people killed in crashes fell from two to one, and the total number of injuries decreased from 54 to 45.
6
Hit-and-Run Crashes — 2023
▼ 0.0% vs prior (6)
The number of hit-and-run incidents in North Reading remained unchanged year-over-year, with 6 such crashes recorded in both 2022 and 2023. The hit-and-run rate as a percentage of total crashes was also stable, moving from 3.1% in 2022 to 3.0% in 2023. This indicates no significant trend change in hit-and-run events for the period.
Vulnerable Road User Casualties
1
Motorists Killed
45
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 patterns of crashes in North Reading showed some shifts between 2022 and 2023. While Friday remained the peak day for crashes in both years (40 in 2022 and 39 in 2023), the peak hour shifted an hour earlier, from 5 p.m. in 2022 to 4 p.m. in 2023. Crashes on weekends (Saturday and Sunday) saw a notable decrease, dropping from a combined 56 incidents in 2022 to 32 in 2023.
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
Crash severity in North Reading decreased from 2022 to 2023. The number of fatal crashes was halved, falling from two incidents to one, while the share of crashes resulting in any injury (fatal, serious, minor, or possible) declined from 25.5% in 2022 to 21.8% in 2023. Correspondingly, the proportion of crashes with no reported injuries increased from 74.5% to 78.2% of all incidents.
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 to crashes in both periods was 'Failed to yield right of way,' with the count for this factor increasing by 16.3% from 49 incidents in 2022 to 57 in 2023. The second most common factor, 'No improper driving,' remained stable with 42 incidents in 2022 and 41 in 2023. Notably, crashes attributed to 'Failure to keep in proper lane or running off road' more than doubled, rising from 5 to 11 incidents year-over-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
Driving conditions for most crashes were consistent year-over-year, with the majority of incidents in both 2022 and 2023 occurring in 'Daylight' (144 and 142 crashes, respectively) on 'Dry' road surfaces (155 and 152 crashes). Crashes during adverse weather conditions like rain or snow saw a slight increase from 18 total incidents in 2022 to 23 in 2023. Similarly, crashes on wet, icy, or snowy road surfaces increased slightly from 41 to 45 incidents.
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 remained Toyota, Honda, and Ford in both years, with Toyota leading at 47 vehicles in 2022 and 53 in 2023. Regarding the age of persons involved in crashes, there was a significant shift in demographic representation. The number of individuals aged 0-15 more than doubled from 20 in 2022 to 49 in 2023, while the 65+ age group also saw a notable increase from 44 to 59 persons. Conversely, involvement for the 16-20 and 55-64 age groups decreased from 60 to 54 and 66 to 54, respectively.
Top Vehicle Makes (355 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (411 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
The distribution of crashes across speed zones shifted between 2022 and 2023. While 30 mph zones accounted for the highest number of crashes in both years, the count decreased from 87 to 75. In contrast, crashes in 40 mph zones increased from 50 to 58. The location of fatal crashes also changed, with two fatalities occurring in 30 mph zones in 2022 and one fatality occurring in a 35 mph zone in 2023.
Fatal crashes by zone: 35 mph: 1 of 25 (4%)
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: NORTH READING, MA
- Total crash records analyzed: 197
- Total persons involved: 437
- Total vehicles involved: 355
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). "NORTH READING, 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/north-reading/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