Monthly Traffic Safety Analysis

281 CRASHES IN
NEW BEDFORD, MA
JUNE 2024

All metrics benchmarked againstJune 2023

Total crashes in June 2024 decreased by 2.77% to 281 from 289 in June 2023. A significant year-over-year shift was the 400% increase in bicycle crashes, rising from 1 in June 2023 to 5 in June 2024, alongside a 75% decrease in speeding-related crashes, from 4 to 1.

281

-2.8%was 289

Total Crash Events

0

Persons Killed

90

-15.1%was 106

Persons Injured

41

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. 20 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for June 2024 shows a slight decrease in total crashes, dropping by 2.77% from 289 to 281 compared to June 2023. Total injuries also decreased by 15.09%, from 106 to 90. Fatalities remained stable at zero in both periods.

41

Hit-and-Run Crashes — June 2024

0.0% vs prior (41)

The number of hit-and-run crashes remained stable at 41 in both June 2023 and June 2024. However, the hit-and-run rate slightly increased from 14.2% of total crashes in the prior period to 14.6% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 8-62.5%

3

Cyclists Injured

Prior: 1200.0%

84

Motorists Injured

Prior: 97-13.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, though the count decreased from 58 in June 2023 to 50 in June 2024. The peak hour for crashes shifted from 4 PM with 24 crashes in June 2023 to 3 PM with 22 crashes in June 2024. Crashes at 4 PM decreased significantly from 24 to 14.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both June 2023 and June 2024. The proportion of crashes resulting in no injury increased from 66.1% in June 2023 to 70.5% in June 2024. Serious injury crashes increased slightly from 5 to 6, while minor injury crashes decreased from 45 to 40.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes2.1%
20.0%prior 5
Minor Injury40minor injury crashes14.2%
-11.1%prior 45
Possible Injury17possible injury crashes6%
6.3%prior 16
No Injury198no injury crashes70.5%
3.7%prior 191

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

Crashes with "No improper driving" as a contributing factor increased by 43, from 75 in June 2023 to 118 in June 2024. Conversely, crashes attributed to "Failure to keep in proper lane or running off road" decreased by 8, from 12 to 4. Crashes where "Exceeded authorized speed limit" was a factor decreased by 3, from 4 to 1.

Officer-Reported Primary Contributing Cause

No improper driving118 (42%)57.3%prior 75
Inattention31 (11%)-11.4%prior 35
Other improper action19 (6.8%)18.8%prior 16
Failed to yield right of way17 (6%)21.4%prior 14
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner13 (4.6%)85.7%prior 7
Followed too closely10 (3.6%)25.0%prior 8
Disregarded traffic signs, signals, road markings8 (2.8%)14.3%prior 7
Visibility obstructed7 (2.5%)
Over-correcting/over-steering5 (1.8%)0.0%prior 5
Distracted5 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased by 29, from 205 to 234. Conversely, crashes in cloudy weather decreased by 15, from 28 to 13, and crashes in rainy conditions decreased by 7, from 16 to 9. Crashes on wet road surfaces also saw a decrease of 16, from 31 to 15.

Weather

Clear234 (84.8%)
14.1%prior 205
Cloudy13 (4.7%)
-53.6%prior 28
Rain9 (3.3%)
-43.8%prior 16
Clear/Other6 (2.2%)
Clear/Unknown4 (1.4%)
-42.9%prior 7
Clear/Cloudy4 (1.4%)
-71.4%prior 14
Cloudy/Rain3 (1.1%)
-40.0%prior 5
Cloudy/Other1 (0.4%)
Rain/Cloudy1 (0.4%)
Severe crosswinds1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight216 (77.7%)
0.9%prior 214
Dark - lighted roadway51 (18.3%)
-8.9%prior 56
Dusk6 (2.2%)
Dawn3 (1.1%)
Dark - roadway not lighted1 (0.4%)
-85.7%prior 7
Dark - unknown roadway lighting1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry261 (94.2%)
2.8%prior 254
Wet15 (5.4%)
-51.6%prior 31
Sand, mud, dirt, oil, gravel1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased slightly from 566 to 560. Ford vehicles involved in crashes decreased by 13, from 66 to 53, while Jeep vehicles increased by 12, from 17 to 29. In terms of persons involved, the 65+ age group saw an increase of 19 individuals, rising from 46 to 65.

Top Vehicle Makes (560 vehicles)

1
TOYOTA102 (18.2%)
-2.9%prior 105
2
HONDA74 (13.2%)
4.2%prior 71
3
FORD53 (9.5%)
-19.7%prior 66
4
CHEVROLET34 (6.1%)
25.9%prior 27
5
HYUNDAI33 (5.9%)
17.9%prior 28
6
NISSAN30 (5.4%)
-9.1%prior 33
7
JEEP29 (5.2%)
70.6%prior 17
8
KIA21 (3.8%)
-25.0%prior 28
9
ACURA10 (1.8%)
-23.1%prior 13
10
GMC10 (1.8%)
-37.5%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

140 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (532 persons with recorded sex)

Male285 (53.6%)
7.1%prior 266
Female247 (46.4%)
-7.1%prior 266

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones decreased by 8, from 56 to 48. Crashes in 65 mph zones also decreased by 6, from 15 to 9. Conversely, crashes in 35 mph zones increased by 5, from 10 to 15. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: NEW BEDFORD, MA
  • Total crash records analyzed: 281
  • Total persons involved: 696
  • 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: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/new-bedford/june-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