ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, 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/new-bedford/2024-annual-report
Yearly Traffic Safety Analysis
3,438 CRASHES IN
NEW BEDFORD, MA
2024
In 2024, New Bedford recorded 3,438 total crashes, a 9.5% decrease from the 3,798 crashes reported in 2023. While overall crashes and injuries declined, the number of total fatalities increased from 5 to 6. A notable year-over-year change was a 28.9% increase in crashes involving a driver suspected of being under the influence of alcohol, which rose from 76 to 98 incidents.
3,438
▼ -9.5%was 3,798
Total Crash Events
6
▲ 20.0%was 5
Persons Killed
991
▼ -6.5%was 1,060
Persons Injured
511
▼ -13.8%was 593
Hit-and-Run Crashes
Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 263 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
Overall, traffic crashes in New Bedford showed a downward trend year-over-year, with total incidents falling by 9.5% from 3,798 in 2023 to 3,438 in 2024. This decline was accompanied by a 6.5% decrease in total injuries, which fell from 1,060 to 991. However, total fatalities increased by one, from 5 in the prior year to 6 in the current year.
511
Hit-and-Run Crashes — 2024
▼ -13.8% vs prior (593)
Hit-and-run incidents decreased year-over-year, both in absolute numbers and as a proportion of total crashes. The total count of hit-and-run crashes fell by 13.8%, from 593 in 2023 to 511 in 2024. The hit-and-run rate also trended downward, decreasing from 15.6% of all crashes in the prior year to 14.9% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
1
Cyclists Killed
4
Motorists Killed
0
Other Killed
53
Pedestrians Injured
29
Cyclists Injured
903
Motorists Injured
6
Other 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 remained largely consistent year-over-year. Friday was the peak day for crashes in both 2024 (541 crashes) and 2023 (583 crashes). The peak hour for crashes shifted slightly earlier, moving from the 3 PM hour in 2023 (293 crashes) to the 2 PM hour in 2024 (273 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
The number of fatal crash events remained unchanged at 5 for both 2024 and 2023, though the fatal crash rate increased from 0.13% to 0.15% due to the lower overall crash volume. The proportion of crashes resulting in a serious injury grew from 1.4% to 1.6% year-over-year. Crashes resulting in no injury represented 71.1% of all incidents in 2024, an increase from 67.5% in the prior year.
Severity is per crash event (most severe injury). 5 fatal crash events resulted in 6 persons killed.
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 leading contributing factors remained consistent, though their counts shifted. 'Inattention' as a factor decreased in count by 17.5%, from 365 incidents in 2023 to 301 in 2024. Similarly, crashes attributed to 'Failed to yield right of way' dropped by 19.2% from 297 to 240. Conversely, incidents involving 'Followed too closely' increased by 24.5% from 98 to 122, and crashes where 'No improper driving' was cited grew from 1,090 to 1,309.
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
The distribution of crashes across different environmental conditions remained remarkably stable year-over-year. In both 2024 and 2023, approximately 66% of crashes occurred during daylight hours. Crashes on dry roads accounted for about 83% of the total in both periods, and clear weather was reported in roughly 70% of all crashes for both years, indicating no significant shift in the role of adverse conditions.
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 most common vehicle makes involved in crashes were consistent across both periods, with Toyota, Honda, and Ford ranking as the top three in both 2024 and 2023. Regarding person demographics, the 26-34 age group was the most frequently involved cohort in both years, representing 14.7% of all persons in 2023 and increasing its share slightly to 15.4% in 2024.
Top Vehicle Makes (6,857 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
1,815 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (6,304 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 majority of crashes in both years occurred in the 30 mph speed zone, though the count in this zone decreased from 2,297 to 1,963. However, fatalities within the 30 mph zone rose from one to three. A notable change occurred in the 65 mph zone, where crashes fell from 127 to 81, and the three fatalities recorded in 2023 were eliminated in 2024. Conversely, the 55 mph zone saw an increase in crashes from 65 to 71 and recorded one fatality in 2024 where there were none the previous year.
Fatal crashes by zone: 30 mph: 3 of 1,963 (0.153%) · 55 mph: 1 of 71 (1.408%)
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: NEW BEDFORD, MA
- Total crash records analyzed: 3,438
- Total persons involved: 8,282
- Total vehicles involved: 6,857
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: 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/new-bedford/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