ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ARLINGTON, MA · MARCH 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/arlington/march-2024-report
Monthly Traffic Safety Analysis
29 CRASHES IN
ARLINGTON, MA
MARCH 2024
Total crashes in Arlington increased by 11.5% year-over-year, from 26 crashes in March 2023 to 29 crashes in March 2024. Despite this increase in total crashes, the number of total injuries remained constant at 4 in both periods. A notable shift was the decrease in hit-and-run crashes from 2 in the prior period to 1 in the current period.
29
▲ 11.5%was 26
Total Crash Events
0
Persons Killed
4
Persons Injured
1
▼ -50.0%was 2
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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a slight increase in crashes, with total crashes rising from 26 in March 2023 to 29 in March 2024. This represents an 11.5% increase in the number of reported crashes year-over-year. Fatalities remained at zero in both periods, and total injuries held steady at 4.
1
Hit-and-Run Crashes — March 2024
▼ -50.0% vs prior (2)
Hit-and-run crashes decreased from 2 in March 2023 to 1 in March 2024. This change resulted in the hit-and-run rate decreasing from 7.7% of total crashes in the prior period to 3.4% in the current period. This indicates a downward trend in the proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
3
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Both March 2023 and March 2024 periods observed Friday as the peak day for crashes, with 7 crashes in the prior period and 9 in the current period. The peak hour for crashes shifted from 3 PM with 5 crashes in March 2023 to 9 AM with 5 crashes in March 2024. While the peak day remained consistent, the busiest time of day for crashes changed.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either March 2023 or March 2024. Total injuries remained at 4 in both periods, even as total crashes increased. The proportion of Minor Injury crashes decreased from 15.4% (4 crashes) in the prior period to 10.3% (3 crashes) in the current period, while Possible Injury crashes appeared in the current period with 1 crash (3.4%) where there were none previously.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'No improper driving' decreased from 12 crashes in the prior period to 8 crashes in the current period. Conversely, 'Failed to yield right of way' increased significantly from 3 crashes to 7 crashes year-over-year. 'Inattention' emerged as a factor in the current period with 3 crashes, whereas it was not among the top factors in the prior period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under 'Clear' weather conditions increased from 14 in March 2023 to 16 in March 2024. The number of crashes on 'Wet' road surfaces increased from 2 in the prior period to 6 in the current period. Crashes occurring in 'Dark - lighted roadway' conditions decreased from 4 to 3, while 1 crash in the current period occurred in 'Dark - roadway not lighted' conditions, which was not observed in the prior period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (53 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records
9 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (62 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events
Speed Limit Zones
The 25 mph speed zone remained the most common location for crashes, increasing from 15 crashes in March 2023 to 18 crashes in March 2024. Crashes in the 30 mph zone increased from 4 to 5, while those in the 20 mph zone decreased from 3 to 2. Notably, crashes in the 45 mph and 55 mph zones, present in the prior period, were absent in the current period, which instead saw crashes in 10 mph and 35 mph zones.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-03-01 through 2024-03-31 (31 days)
- Geographic scope: ARLINGTON, MA
- Total crash records analyzed: 29
- Total persons involved: 71
- Total vehicles involved: 53
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). "ARLINGTON, MA Crash Intelligence Report: March 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/arlington/march-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: 2024-03-01 – 2024-03-31
Generated: June 21, 2026 · All rights reserved