Yearly Traffic Safety Analysis

1,660 CRASHES IN
HAVERHILL, MA
2024

All metrics benchmarked against2023

In Haverhill, total crashes increased from 1602 in 2023 to 1660 in 2024, a change of 3.6%. While overall collisions rose, the most significant year-over-year change was a decrease in traffic fatalities, which fell from 2 in the prior period to 0 in the current period. Crashes resulting in serious injuries, however, increased from 11 to 30.

1,660

3.6%was 1,602

Total Crash Events

0

-100.0%was 2

Persons Killed

463

17.5%was 394

Persons Injured

245

1.2%was 242

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. 130 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

The overall trend in Haverhill shows a slight increase in traffic collisions, with total crashes rising by 3.6% from 1602 to 1660 year-over-year. The number of injuries also increased by 17.5%, from 394 to 463. However, fatalities decreased, with zero recorded in the current period compared to two in the prior year.

245

Hit-and-Run Crashes — 2024

1.2% vs prior (242)

The number of hit-and-run crashes remained nearly stable, increasing slightly from 242 in the prior period to 245 in the current period. Despite the small increase in absolute numbers, the hit-and-run rate as a percentage of total crashes saw a slight downward trend, decreasing from 15.1% to 14.8% year-over-year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

0

Other Killed

Prior: 00.0%

26

Pedestrians Injured

Prior: 1844.4%

14

Cyclists Injured

Prior: 6133.3%

412

Motorists Injured

Prior: 36512.9%

11

Other Injured

Prior: 5120.0%

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 saw minor shifts year-over-year. The peak day for collisions moved from Monday (271 crashes) in the prior period to Tuesday (262 crashes) in the current period. Similarly, the peak hour for crashes shifted slightly later, from the 3 p.m. hour (161 crashes) to the 4 p.m. hour (164 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

While fatal crashes decreased from 2 to 0 year-over-year, the number of crashes resulting in serious injuries more than doubled, increasing from 11 to 30. The count of crashes involving minor injuries rose from 228 to 236, and possible injury crashes increased from 57 to 73. The proportion of no-injury crashes remained relatively stable, accounting for 74.2% of crashes in the prior period and 71.7% in the current period.

Outcome by Severity (Crash Events)

Serious Injury30serious injury crashes1.8%
172.7%prior 11
Minor Injury236minor injury crashes14.2%
3.5%prior 228
Possible Injury73possible injury crashes4.4%
28.1%prior 57
No Injury1,191no injury crashes71.7%
0.2%prior 1,189

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

Inattention remained the top contributing factor in both periods, with the count of related crashes increasing by 5.3% from 471 to 496. While the top ranking was unchanged, crashes attributed to 'Failed to yield right of way' decreased by 18.7% in count, from 209 to 170, moving it from the second to the third-ranked factor. Conversely, crashes with 'No improper driving' cited increased in count by 13.4% from 172 to 195, becoming the second most common factor in the current period.

Officer-Reported Primary Contributing Cause

Inattention496 (29.9%)5.3%prior 471
No improper driving195 (11.7%)13.4%prior 172
Failed to yield right of way170 (10.2%)-18.7%prior 209
Followed too closely110 (6.6%)-6.8%prior 118
Failure to keep in proper lane or running off road86 (5.2%)4.9%prior 82
Driving too fast for conditions60 (3.6%)13.2%prior 53
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner60 (3.6%)11.1%prior 54
Disregarded traffic signs, signals, road markings47 (2.8%)0.0%prior 47
Over-correcting/over-steering46 (2.8%)39.4%prior 33
Distracted41 (2.5%)2.5%prior 40

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

Crashes in both periods predominantly occurred in clear weather and daylight on dry roads. The number of crashes on wet road surfaces decreased from 271 to 214, and collisions during rainy weather fell from 145 to 103. Crashes in daylight conditions increased from 1074 to 1117, consistent with the overall rise in total crashes.

Weather

Clear1,142 (69.5%)
7.2%prior 1,065
Cloudy191 (11.6%)
8.5%prior 176
Rain103 (6.3%)
-29.0%prior 145
Clear/Clear58 (3.5%)
26.1%prior 46
Snow44 (2.7%)
-6.4%prior 47
Sleet, hail (freezing rain or drizzle)22 (1.3%)
144.4%prior 9
Snow/Sleet, hail (freezing rain or drizzle)14 (0.9%)
-6.7%prior 15
Cloudy/Rain13 (0.8%)
-40.9%prior 22
Rain/Cloudy8 (0.5%)
-68.0%prior 25
Rain/Rain5 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight1,117 (68.2%)
4.0%prior 1,074
Dark - lighted roadway363 (22.1%)
4.9%prior 346
Dark - roadway not lighted64 (3.9%)
-26.4%prior 87
Dusk60 (3.7%)
15.4%prior 52
Dawn24 (1.5%)
41.2%prior 17
Dark - unknown roadway lighting10 (0.6%)
100.0%prior 5
Other1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry1,332 (80.8%)
7.4%prior 1,240
Wet214 (13.0%)
-21.0%prior 271
Snow51 (3.1%)
-12.1%prior 58
Slush25 (1.5%)
Ice23 (1.4%)
35.3%prior 17
Water (standing, moving)4 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Honda, Toyota, and Ford in both periods, with minimal changes in their counts. The number of Hondas involved was identical at 516, while Toyotas decreased from 401 to 376 and Fords from 312 to 305. Analysis of person age groups shows a notable increase in the 35-44 age group, which grew from 519 to 585 persons involved, while the 16-20 age group saw a decrease from 416 to 381.

Top Vehicle Makes (2,957 vehicles)

1
HONDA516 (17.5%)
0.0%prior 516
2
TOYOTA376 (12.7%)
-6.2%prior 401
3
FORD305 (10.3%)
-2.2%prior 312
4
CHEVROLET257 (8.7%)
4.9%prior 245
5
NISSAN167 (5.6%)
-14.4%prior 195
6
SUBARU150 (5.1%)
50.0%prior 100
7
JEEP132 (4.5%)
5.6%prior 125
8
HYUNDAI108 (3.7%)
38.5%prior 78
9
KIA75 (2.5%)
-6.3%prior 80
10
ACURA72 (2.4%)
-1.4%prior 73

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (3,410 persons with recorded sex)

Male1,880 (55.1%)
1.7%prior 1,848
Female1,530 (44.9%)
-1.2%prior 1,548

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 30 mph zones, with the count in this zone increasing from 589 to 644. Conversely, crashes in 35 mph zones decreased from 431 to 386. In the prior period, two fatal crashes were recorded, one in a 15 mph zone and another in a 30 mph zone; no fatal crashes were recorded in any speed zone in the current period.

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: HAVERHILL, MA
  • Total crash records analyzed: 1,660
  • Total persons involved: 3,882
  • Total vehicles involved: 2,957

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). "HAVERHILL, 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/haverhill/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

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Haverhill, MA Crash Report — 2024 | ThatCarHitMe.com