ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEWTON, MA · MAY 2024
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/newton/may-2024-report
Monthly Traffic Safety Analysis
172 CRASHES IN
NEWTON, MA
MAY 2024
Total crashes in May 2024 increased to 172, up from 145 crashes in May 2023, representing an 18.62% rise year-over-year. The most notable shift was a 42.86% increase in total injuries, rising from 28 to 40. Fatalities remained at zero in both periods.
172
▲ 18.6%was 145
Total Crash Events
0
Persons Killed
40
▲ 42.9%was 28
Persons Injured
16
▼ -20.0%was 20
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. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash activity year-over-year, with total crashes rising by 18.62% from 145 in May 2023 to 172 in May 2024. Total injuries also saw a substantial increase of 42.86%, from 28 to 40. There were no reported fatalities in either period.
16
Hit-and-Run Crashes — May 2024
▼ -20.0% vs prior (20)
Hit-and-run crashes decreased from 20 in May 2023 to 16 in May 2024, representing a 20% reduction in count. The hit-and-run rate also declined from 13.8% to 9.3% of total crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
4
Cyclists Injured
34
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Tuesday in May 2023 (30 crashes) to Thursday in May 2024 (40 crashes). The peak hour remained consistent at 3 PM, experiencing an increase from 14 crashes in May 2023 to 20 crashes in May 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either period. The proportion of crashes resulting in injuries increased from 19.31% (28 injuries out of 145 crashes) in May 2023 to 23.26% (40 injuries out of 172 crashes) in May 2024. Minor injuries (Severity B) increased by 85.71% from 14 to 26, while serious injuries (Severity A) decreased from 1 in May 2023 to 0 in May 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record
Top Contributing Factors
Inattention remained a leading contributing factor, increasing from 27 crashes in May 2023 to 50 crashes in May 2024, an 85.2% count increase. Crashes attributed to 'Followed too closely' rose by 61.1%, from 18 to 29, and 'Failed to yield right of way' increased by 90.9%, from 11 to 21. Conversely, crashes with 'No improper driving' as a factor decreased by 33.3%, from 30 to 20.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 111 in May 2023 to 123 in May 2024, while those in rainy conditions rose from 9 to 15. The number of crashes occurring during daylight hours increased from 112 to 142. The count of crashes on dry road surfaces increased from 124 to 151, while crashes on wet road surfaces remained stable at 17.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 20.2%, from 272 in May 2023 to 327 in May 2024. Toyota remained the most frequently involved make, with its count increasing from 44 to 58, and Honda saw a substantial increase from 28 to 53 involved vehicles. The age group 65+ experienced a significant increase in persons involved, rising from 31 to 61.
Top Vehicle Makes (327 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records
32 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (342 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased by 26.1%, from 69 in May 2023 to 87 in May 2024. Crashes in 55 mph zones also rose by 22.7%, from 22 to 27. Conversely, crashes in 30 mph zones decreased by 16.7%, from 24 to 20. No fatalities were reported across any speed limit zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-05-01 through 2024-05-31 (31 days)
- Geographic scope: NEWTON, MA
- Total crash records analyzed: 172
- Total persons involved: 380
- Total vehicles involved: 327
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). "NEWTON, MA Crash Intelligence Report: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/may-2024-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: 2024-05-01 – 2024-05-31
Generated: June 21, 2026 · All rights reserved