ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, MA · AUGUST 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/august-2024-report
Monthly Traffic Safety Analysis
287 CRASHES IN
NEW BEDFORD, MA
AUGUST 2024
In August 2024, NEW BEDFORD experienced 287 crashes, a decrease from 327 crashes in August 2023, representing a 12.23% reduction year-over-year. Despite the overall decrease in crashes, total fatalities increased from 0 to 1, and total injuries rose from 77 to 109, indicating a shift towards more severe outcomes per crash.
287
▼ -12.2%was 327
Total Crash Events
1
Persons Killed
109
▲ 41.6%was 77
Persons Injured
36
▼ -28.0%was 50
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. 13 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in NEW BEDFORD show a decrease in total crashes by 12.23% from 327 in August 2023 to 287 in August 2024. However, this period saw an increase in crash severity, with total fatalities rising from 0 to 1 and total injuries increasing by 41.56%, from 77 to 109.
36
Hit-and-Run Crashes — August 2024
▼ -28.0% vs prior (50)
Hit-and-run incidents decreased year-over-year, with the number of hit-and-run crashes falling from 50 in August 2023 to 36 in August 2024. This reduction is also reflected in the hit-and-run rate, which decreased from 15.3% of all crashes in August 2023 to 12.5% in August 2024.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
5
Pedestrians Injured
2
Cyclists Injured
102
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year, with the peak day moving from Tuesday in August 2023 (57 crashes) to Saturday in August 2024 (62 crashes). The peak crash hour also changed, with 5 PM being the busiest hour in August 2023 (26 crashes) and 4 PM in August 2024 (28 crashes). This indicates a shift in high-frequency crash times towards later in the week and slightly earlier in the afternoon.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity in August 2024 saw a notable increase compared to the prior year, with total fatalities rising from 0 in August 2023 to 1 in August 2024. Total injuries also increased by 41.56%, from 77 to 109. Serious injuries (code A) increased from 6 crashes (1.8% of total) in August 2023 to 10 crashes (3.5% of total) in August 2024, while minor injuries (code B) rose from 26 crashes (8% of total) to 47 crashes (16.4% of total).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record
Top Contributing Factors
Analysis of contributing factors shows significant shifts in crash counts year-over-year. "No improper driving" crashes increased by 13 (from 99 to 112), while "Inattention" crashes decreased by 16 (from 35 to 19), a 45.71% reduction in count. Conversely, crashes attributed to "Followed too closely" saw a substantial increase of 14 (from 4 to 18), and "Distracted" crashes increased by 4 (from 3 to 7).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather decreased by 10 (from 230 to 220), and crashes in "Rain" conditions decreased by 10 (from 17 to 7). Crashes during "Daylight" conditions decreased by 26 (from 229 to 203), while those in "Dark - lighted roadway" increased by 3 (from 65 to 68). The number of crashes on "Wet" road surfaces decreased by 24 (from 42 to 18), indicating fewer adverse road condition crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes saw a slight shift in ranking, with HONDA becoming the most frequent in August 2024 (90 crashes) compared to TOYOTA in August 2023 (94 crashes), while TOYOTA dropped to second (83 crashes). The age group 26-34 remained the most represented in both periods, though its count decreased from 117 to 111. There was a slight increase in male persons involved (from 293 to 305) and a decrease in female persons involved (from 281 to 236).
Top Vehicle Makes (578 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Vehicle unit records
147 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (541 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones decreased by 17 (from 179 to 162), and crashes in 25 mph zones decreased by 7 (from 68 to 61). Similarly, crashes in 65 mph speed zones decreased by 2 (from 9 to 7). For both August 2023 and August 2024, no fatal crashes were recorded in any specific speed limit zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-08-01 through 2024-08-31 (31 days)
- Geographic scope: NEW BEDFORD, MA
- Total crash records analyzed: 287
- Total persons involved: 708
- Total vehicles involved: 578
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: August 2024." Published June 21, 2026. Reporting period: 2024-08-01 to 2024-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/new-bedford/august-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: 2024-08-01 – 2024-08-31
Generated: June 21, 2026 · All rights reserved