Monthly Traffic Safety Analysis

40 CRASHES IN
READING, MA
JULY 2022

All metrics benchmarked againstJuly 2021

In July 2022, Reading experienced 40 crashes, a decrease of 17 crashes or approximately 29.8% compared to the 57 crashes reported in July 2021. Total injuries also saw a significant reduction, falling from 14 to 8, a 42.9% decrease year-over-year. This period also saw no fatal crashes, consistent with the prior year.

40

-29.8%was 57

Total Crash Events

0

Persons Killed

8

-42.9%was 14

Persons Injured

0

-100.0%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 · 2022-07-01 to 2022-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in Reading showed a declining trend year-over-year, with total crashes decreasing by 17, from 57 in July 2021 to 40 in July 2022. This represents a reduction of approximately 29.8% in total crashes. The number of injured persons also decreased from 14 to 8, a 42.9% decline.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

7

Motorists Injured

Prior: 14-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Thursday in both periods, though the count decreased from 13 in July 2021 to 8 in July 2022. The peak hour shifted from 6 p.m. in July 2021, with 7 crashes, to 1 p.m. in July 2022, with 5 crashes. Notably, Saturday crashes saw a significant reduction, falling from 12 in July 2021 to 3 in July 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes reported in either July 2021 or July 2022. Total injuries decreased from 14 to 8, representing a 42.9% reduction. Serious injury crashes, which accounted for 1.8% of crashes in July 2021 (1 crash), were not reported in July 2022.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes7.5%
-50.0%prior 6
Possible Injury4possible injury crashes10%
-20.0%prior 5
No Injury33no injury crashes82.5%
-25.0%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Followed too closely' decreased by 9 crashes, from 18 in July 2021 to 9 in July 2022, representing a 50% reduction in count. Conversely, 'Inattention' increased by 3 crashes, from 7 to 10, marking a 42.9% increase in count and becoming the leading contributing factor in July 2022. 'No improper driving' decreased from 10 crashes to 8 crashes, a 20% reduction in count.

Officer-Reported Primary Contributing Cause

Inattention10 (25%)42.9%prior 7
Followed too closely9 (22.5%)-50.0%prior 18
No improper driving8 (20%)-20.0%prior 10
Failed to yield right of way2 (5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5%)
Fatigued/asleep1 (2.5%)
Visibility obstructed1 (2.5%)
Disregarded traffic signs, signals, road markings1 (2.5%)
Exceeded authorized speed limit1 (2.5%)
Made an improper turn1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

July 2022 saw a notable decrease in crashes occurring under adverse weather and road surface conditions compared to July 2021. Crashes on wet road surfaces decreased significantly from 11 to 1. Similarly, rain-related weather conditions, which contributed to 11 crashes in July 2021, were not reported in July 2022.

Weather

Clear/Clear22 (55.0%)
0.0%prior 22
Clear16 (40.0%)
0.0%prior 16
Cloudy1 (2.5%)
Cloudy/Clear1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Weather condition at time of crash

Lighting

Daylight34 (85.0%)
-27.7%prior 47
Dark - lighted roadway5 (12.5%)
0.0%prior 5
Dawn1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Lighting condition field

Road Surface

Dry39 (97.5%)
-15.2%prior 46
Wet1 (2.5%)
-90.9%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 117 in July 2021 to 77 in July 2022. The top vehicle makes involved also saw reductions, with Honda decreasing from 25 to 9 and Toyota from 19 to 17. The age distribution of persons involved showed a decrease in older age groups, particularly 45-54 (from 23 to 8) and 65+ (from 23 to 14), while younger age groups like 0-15 (from 7 to 10) and 16-20 (from 16 to 22) saw increases.

Top Vehicle Makes (77 vehicles)

1
TOYOTA17 (22.1%)
-10.5%prior 19
2
HONDA9 (11.7%)
-64.0%prior 25
3
CHEVROLET7 (9.1%)
-41.7%prior 12
4
FORD5 (6.5%)
-37.5%prior 8
5
SUBARU5 (6.5%)
6
NISSAN4 (5.2%)
7
JEEP4 (5.2%)
-33.3%prior 6
8
HYUNDAI3 (3.9%)
9
BUICK2 (2.6%)
10
MAZDA2 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Vehicle unit records

4 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (100 persons with recorded sex)

Male54 (54.0%)
-18.2%prior 66
Female46 (46.0%)
-16.4%prior 55

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes across most speed limit zones decreased year-over-year. Crashes in 55 mph zones decreased from 18 to 11, a 38.9% reduction, while crashes in 30 mph zones decreased from 12 to 11, an 8.3% reduction. There were no fatal crashes reported in any speed limit zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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: 2022-07-01 through 2022-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-07-01 through 2022-07-31 (31 days)
  • Geographic scope: READING, MA
  • Total crash records analyzed: 40
  • Total persons involved: 106
  • Total vehicles involved: 77

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: July 2022." Published June 21, 2026. Reporting period: 2022-07-01 to 2022-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/reading/july-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

Reading, MA Crash Report — July 2022 | ThatCarHitMe.com