ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, MA · APRIL 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/new-bedford/april-2024-report
Monthly Traffic Safety Analysis
280 CRASHES IN
NEW BEDFORD, MA
APRIL 2024
Total crashes in NEW BEDFORD for April decreased slightly from 285 in the prior year to 280 in the current year, a 1.75% reduction. The most significant year-over-year shift was a substantial decrease in total injuries, falling from 80 to 50, a 37.5% decline.
280
▼ -1.8%was 285
Total Crash Events
0
Persons Killed
50
▼ -37.5%was 80
Persons Injured
48
▲ 14.3%was 42
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. 31 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash activity in NEW BEDFORD saw a slight decrease year-over-year, with total crashes falling by 5 from 285 to 280. This represents a 1.75% reduction in crash count. Fatalities remained at zero in both periods, while total injuries significantly decreased by 30, from 80 to 50.
48
Hit-and-Run Crashes — April 2024
▲ 14.3% vs prior (42)
Hit-and-run crashes increased from 42 in the prior period to 48 in the current period. Consequently, the hit-and-run rate also rose from 14.7% to 17.1% year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
4
Pedestrians Injured
1
Cyclists Injured
45
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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 Saturday, with 53 crashes in the prior period, to Monday, with 51 crashes in the current period. The peak hour for crashes also changed, moving from 5 PM with 29 crashes in the prior year to 8 AM with 24 crashes in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either period. Total injuries decreased from 80 in the prior period to 50 in the current period. Serious injuries (Severity A) saw a notable decrease from 5 (1.8% of crashes) to 1 (0.4% of crashes), while minor injuries (Severity B) also decreased from 35 (12.3% of crashes) to 25 (8.9% of crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'No improper driving' saw a significant increase, rising from 84 crashes in the prior period to 120 crashes in the current period, representing a 42.86% increase in count. Conversely, 'Inattention' decreased from 30 crashes to 22 crashes, a 26.67% decrease in count. 'Disregarded traffic signs, signals, road markings' increased from 7 crashes to 11 crashes, a 57.14% increase in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 199 in the prior period to 194 in the current period, while crashes during rain increased from 16 to 22. Crashes during daylight hours decreased from 213 to 184, whereas crashes in dark-lighted roadway conditions increased from 47 to 67. Crashes on dry road surfaces decreased from 245 to 229, while those on wet surfaces increased from 37 to 46.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field
Vehicles & Demographics
Toyota remained the top vehicle make involved in crashes, with its count increasing from 85 in the prior period to 98 in the current period. Honda, previously the second most involved make with 82 crashes, saw a decrease to 64 crashes. Among persons involved in crashes, the 16-20 age group decreased from 65 to 53, and the 35-44 age group decreased from 101 to 84.
Top Vehicle Makes (560 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records
164 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (472 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone continued to account for the highest number of crashes, though it decreased slightly from 179 crashes in the prior period to 173 crashes in the current period. Crashes in the 25 mph zone increased from 43 to 51 year-over-year. No fatal crashes were reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-04-01 through 2024-04-30 (30 days)
- Geographic scope: NEW BEDFORD, MA
- Total crash records analyzed: 280
- Total persons involved: 647
- Total vehicles involved: 560
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). "NEW BEDFORD, MA Crash Intelligence Report: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/new-bedford/april-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: 2024-04-01 – 2024-04-30
Generated: June 21, 2026 · All rights reserved