ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, MA · DECEMBER 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/december-2023-report
Monthly Traffic Safety Analysis
327 CRASHES IN
NEW BEDFORD, MA
DECEMBER 2023
Total crashes in December 2023 were 327, a 4.1% decrease compared to 341 crashes in December 2022. A significant shift was observed in fatalities, which increased from 0 in December 2022 to 2 in December 2023. This change indicates a concerning rise in the severity of crash outcomes despite a reduction in overall crash volume.
327
▼ -4.1%was 341
Total Crash Events
2
Persons Killed
82
▼ -10.9%was 92
Persons Injured
54
▲ 54.3%was 35
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 36 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in December 2023 decreased by 4.1% year-over-year, from 341 crashes in December 2022 to 327 crashes. Despite this reduction in total crashes, fatalities rose sharply from 0 to 2, while total injuries decreased by 10.9%, from 92 to 82. This suggests a shift towards more severe, albeit fewer, incidents.
54
Hit-and-Run Crashes — December 2023
▲ 54.3% vs prior (35)
Hit-and-run crashes increased by 54.3% year-over-year, rising from 35 incidents in December 2022 to 54 in December 2023. The hit-and-run crash rate also increased significantly, from 10.3% in December 2022 to 16.5% in December 2023. This indicates a notable upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
6
Pedestrians Injured
1
Cyclists Injured
74
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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 Friday in December 2022 (73 crashes) to Thursday in December 2023 (56 crashes). The peak hour also changed, moving from 3 PM in December 2022 (35 crashes) to 5 PM in December 2023 (30 crashes). These shifts indicate changes in when crashes are most concentrated, with both peak day and hour seeing fewer incidents year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes increased from 0 in December 2022 to 2 in December 2023, resulting in a fatal crash rate of 0.61% for the current period, up from 0%. Serious injury crashes decreased by 50%, from 4 in December 2022 to 2 in December 2023. Minor injury crashes saw a slight increase from 42 to 44, while possible injury crashes decreased from 22 to 17.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' increased by 8.3% in count, from 84 to 91, and 'Failed to yield right of way' saw a substantial increase of 40% in count, rising from 20 to 28. Conversely, 'Followed too closely' decreased significantly by 55% in count, from 20 to 9, and 'Distracted' crashes decreased by 80% in count, from 10 to 2.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 217 in December 2022 to 206 in December 2023. Crashes in cloudy conditions increased from 18 to 37, while rain-related crashes slightly decreased from 38 to 36. Crashes on dry road surfaces increased from 248 to 253, while those on wet surfaces decreased from 88 to 69.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 686 in December 2022 to 664 in December 2023. Toyota remained the top make, increasing from 96 to 98 vehicles, while Honda decreased from 93 to 90. Notably, Nissan saw a significant decrease from 61 to 40 vehicles, while KIA increased from 23 to 30.
Top Vehicle Makes (664 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records
187 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (577 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
In December 2023, two fatal crashes occurred, one in a 35 mph zone and one in a 65 mph zone, whereas no fatal crashes were recorded in any speed zone in December 2022. Crashes in 30 mph zones slightly decreased from 215 to 210, while crashes in 25 mph zones increased from 34 to 47. Crashes in 35 mph zones decreased from 20 to 12.
Fatal crashes by zone: 35 mph: 1 of 12 (8.333%) · 65 mph: 1 of 7 (14.286%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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: 2023-12-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-12-01 through 2023-12-31 (31 days)
- Geographic scope: NEW BEDFORD, MA
- Total crash records analyzed: 327
- Total persons involved: 787
- Total vehicles involved: 664
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: December 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/new-bedford/december-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: 2023-12-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved