ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, MA · NOVEMBER 2023
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/november-2023-report
Monthly Traffic Safety Analysis
304 CRASHES IN
NEW BEDFORD, MA
NOVEMBER 2023
In November 2023, New Bedford experienced 304 total crashes, an 8.43% decrease compared to the 332 crashes recorded in November 2022. Total injuries saw a substantial decrease, falling from 123 in November 2022 to 81 in November 2023, representing a 34.15% reduction.
304
▼ -8.4%was 332
Total Crash Events
1
Persons Killed
81
▼ -34.1%was 123
Persons Injured
49
▲ 14.0%was 43
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. 30 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for November indicates a downward trend year-over-year, with total crashes decreasing by 8.43% from 332 to 304. Fatalities remained stable at 1, while total injuries significantly declined by 34.15%, from 123 to 81.
49
Hit-and-Run Crashes — November 2023
▲ 14.0% vs prior (43)
Hit-and-run crashes increased from 43 in November 2022 to 49 in November 2023, representing a 13.95% increase in count. The hit-and-run crash rate also rose from 13% of total crashes in November 2022 to 16.1% in November 2023, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
5
Pedestrians Injured
76
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 Tuesday in November 2022 (55 crashes) to Thursday in November 2023 (57 crashes). The peak crash hour remained 3 PM in both periods, though the number of crashes at this hour decreased from 33 in November 2022 to 29 in November 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash count remained stable at 1 in both November 2022 and November 2023, with the fatal crash rate slightly increasing from 0.3% to 0.33% due to fewer overall crashes. Serious injury crashes (severity 'A') decreased significantly from 6 in November 2022 to 2 in November 2023. Overall injury crashes (A, B, C) decreased by 20% year-over-year, from 75 to 60, resulting in a lower proportion of injury crashes relative to total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'No improper driving,' decreased by 9 crashes, from 101 in November 2022 to 92 in November 2023. 'Failed to yield right of way' saw an increase of 4 crashes, from 21 to 25, while 'Disregarded traffic signs, signals, road markings' doubled from 5 crashes to 10 crashes. 'Followed too closely' decreased from 11 crashes to 9 crashes, and 'Disregarded traffic signs, signals, road markings' entered the top five factors in November 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 260 in November 2022 to 236 in November 2023, while crashes in 'Rain' conditions also decreased from 18 to 10. Crashes on 'Wet' road surfaces saw a reduction from 44 to 28. There was no change in the count of crashes occurring in 'Dark - lighted roadway' conditions, which remained at 92 in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 652 in November 2022 to 613 in November 2023. Toyota became the most frequently involved vehicle make with 88 vehicles, surpassing Honda which dropped from 85 to 60. The age group 35-44 saw an increase of 19 persons involved in crashes, from 103 to 122, while the 45-54 age group experienced a decrease of 29 persons involved, from 87 to 58.
Top Vehicle Makes (613 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
154 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (550 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased from 208 in November 2022 to 190 in November 2023. Conversely, crashes in the 65 mph speed zone increased from 11 to 17, with one fatal crash occurring in this zone in November 2023, compared to zero in the prior period. A fatal crash occurred in the 50 mph zone in November 2022, but no crashes were reported in this zone in November 2023.
Fatal crashes by zone: 65 mph: 1 of 17 (5.882%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: NEW BEDFORD, MA
- Total crash records analyzed: 304
- Total persons involved: 734
- Total vehicles involved: 613
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: November 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/new-bedford/november-2023-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: 2023-11-01 – 2023-11-30
Generated: June 21, 2026 · All rights reserved