ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MALDEN, 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/malden/may-2024-report
Monthly Traffic Safety Analysis
78 CRASHES IN
MALDEN, MA
MAY 2024
In May 2024, Malden experienced 78 total crashes, an 8.24% decrease compared to the 85 crashes reported in May 2023. While total injuries remained consistent at 31 in both periods, the number of serious injuries decreased from 3 to 1. The most notable shift was a decrease in sideswipe, same direction collisions from 23 to 10.
78
▼ -8.2%was 85
Total Crash Events
0
Persons Killed
31
Persons Injured
27
▼ -6.9%was 29
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. 17 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
Overall, crash incidents in Malden saw a slight decline, with total crashes decreasing from 85 in May 2023 to 78 in May 2024, representing an 8.24% reduction. Despite this, the total number of injuries remained stable at 31 for both periods.
27
Hit-and-Run Crashes — May 2024
▼ -6.9% vs prior (29)
The number of hit-and-run crashes decreased from 29 in May 2023 to 27 in May 2024. Despite this, the hit-and-run rate slightly increased from 34.1% of all crashes in May 2023 to 34.6% in May 2024.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
5
Pedestrians Injured
26
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 remained Monday in both periods, though the count slightly decreased from 19 crashes in May 2023 to 18 crashes in May 2024. The peak hour for crashes shifted from 5 p.m. with 7 crashes in May 2023 to 9 p.m. with 7 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
Fatalities remained at 0 in both May 2023 and May 2024. Serious injuries (Severity A) decreased from 3 (3.5% of crashes) in the prior period to 1 (1.3% of crashes) in the current period. Conversely, minor injuries (Severity B) increased from 9 (10.6% of crashes) to 14 (17.9% of crashes) year-over-year.
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
The count of crashes attributed to "No improper driving" increased from 21 in May 2023 to 29 in May 2024. "Inattention" also saw a slight increase in count, from 4 to 5 crashes. Factors such as "Failure to keep in proper lane or running off road" (3 crashes in prior period) and "Over-correcting/over-steering" (2 crashes in prior period) were present in the prior period but not among the top factors in the current period.
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 or clear/clear weather conditions decreased in proportion from 77.6% (66 of 85 crashes) in May 2023 to 75.6% (59 of 78 crashes) in May 2024. Crashes on wet road surfaces increased from 5 incidents (5.9% of crashes) to 8 incidents (10.3% of crashes) year-over-year. The proportion of crashes occurring in daylight conditions remained stable at approximately 65% in both periods.
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 decreased from 144 in May 2023 to 137 in May 2024. Toyota and Honda remained the top two vehicle makes involved in crashes, both showing slight increases in counts. The 16-20 age group saw a notable increase in persons involved in crashes, rising from 6 to 13, while the 65+ age group decreased from 17 to 5.
Top Vehicle Makes (137 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records
34 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (132 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 occurring in 25 mph speed zones slightly decreased from 65 in May 2023 to 63 in May 2024. Crashes in 30 mph speed zones also saw a reduction, from 10 incidents to 6 incidents. No fatalities were recorded in any speed zone during 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: MALDEN, MA
- Total crash records analyzed: 78
- Total persons involved: 168
- Total vehicles involved: 137
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). "MALDEN, 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/malden/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