ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RANDOLPH, MA · 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/randolph/2024-annual-report
Yearly Traffic Safety Analysis
903 CRASHES IN
RANDOLPH, MA
2024
In 2024, Randolph recorded 903 total crashes, a 6.1% decrease from the 962 crashes reported in 2023. Despite the overall reduction in collisions, the number of reported injuries increased significantly, rising from 146 in the prior year to 266 in the current year.
903
▼ -6.1%was 962
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
266
▲ 82.2%was 146
Persons Injured
94
▲ 22.1%was 77
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. 198 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows a decrease in the total number of crashes in Randolph, with a 6.1% drop from 962 in 2023 to 903 in 2024. However, the severity of outcomes worsened, as total injuries surged by 82.2% year-over-year, from 146 to 266. The number of fatalities decreased from 3 in the prior period to 1 in the current period.
94
Hit-and-Run Crashes — 2024
▲ 22.1% vs prior (77)
The number of hit-and-run incidents increased from 77 in 2023 to 94 in 2024, a 22.1% rise in count. This increase, combined with the overall decrease in total crashes, resulted in a higher hit-and-run rate. In the current year, hit-and-runs constituted 10.4% of all crashes, up from 8.0% in the prior year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
262
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes saw minor shifts between the two periods. The peak day for crashes moved from Thursday (148 crashes) in 2023 to Wednesday (147 crashes) in 2024. Similarly, the peak hour for collisions shifted later in the day, from the 2 p.m. hour in the prior year (73 crashes) to the 4 p.m. hour in the current year (78 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the number of fatal crashes decreased from 2 to 1 year-over-year, resulting in a lower fatal crash rate (0.11% in 2024 vs. 0.21% in 2023), the proportion of crashes involving injuries increased. In the current period, crashes resulting in any level of injury (Serious, Minor, or Possible) accounted for 18.9% of all incidents, up from 11.4% in the prior year. Specifically, crashes with Serious Injuries rose from 4 to 7, and those with Minor Injuries increased from 68 to 91.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors remained consistent across both periods: 'Followed too closely,' 'Failed to yield right of way,' and 'No improper driving.' The count of crashes attributed to 'Followed too closely' saw a slight increase from 207 to 211. In contrast, crashes involving 'Failed to yield right of way' decreased in count from 187 to 152, and those citing 'Inattention' dropped from 72 to 50.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in daylight (62.5% in 2024 vs. 64.3% in 2023) and on dry roads (75.3% vs. 78.6%). Crashes happening on wet road surfaces saw a proportional decrease, accounting for 14.4% of crashes in the current year compared to 19.4% in the prior year. The proportion of crashes occurring during clear weather was stable, at approximately 72% in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The vehicle and person demographics involved in crashes showed stability between the two years. The top three vehicle makes involved in collisions remained Toyota, Honda, and Ford in both 2023 and 2024, with counts for each decreasing slightly in the current period. The age distribution of persons involved in crashes also saw minimal change, with the 26-34 age group representing the largest share in both years (20.5% in 2024 vs. 20.3% in 2023).
Top Vehicle Makes (1,868 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
128 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,134 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones showed some shifts between periods. Crashes in 25 mph and 55 mph zones decreased, from 218 to 203 and 186 to 170, respectively. Conversely, incidents in 30 mph zones increased from 132 to 147, and crashes in 65 mph zones rose from 139 to 163. The single fatal crash in 2024 occurred in a 30 mph zone, whereas the two fatal crashes in 2023 both occurred in a 35 mph zone.
Fatal crashes by zone: 30 mph: 1 of 147 (0.68%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: RANDOLPH, MA
- Total crash records analyzed: 903
- Total persons involved: 2,338
- Total vehicles involved: 1,868
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). "RANDOLPH, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/randolph/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved