Yearly Traffic Safety Analysis

414 CRASHES IN
NORWOOD, MA
2024

All metrics benchmarked against2023

In Norwood, total traffic crashes increased by 10.4% from 375 in 2023 to 414 in 2024. While the number of injuries remained stable, the most significant year-over-year change was the increase in total fatalities from one to three. This included a rise in fatal crashes from one to three.

414

10.4%was 375

Total Crash Events

3

200.0%was 1

Persons Killed

140

-0.7%was 141

Persons Injured

8

60.0%was 5

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 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 safety trends in Norwood show a rise in crash frequency. Total crashes increased from 375 to 414 year-over-year, a 10.4% increase. While total injuries decreased minimally from 141 to 140, the number of fatalities rose from one in 2023 to three in 2024.

8

Hit-and-Run Crashes — 2024

60.0% vs prior (5)

Hit-and-run incidents showed an upward trend. The total number of hit-and-run crashes increased from 5 in 2023 to 8 in 2024. This corresponds to a rise in the hit-and-run rate from 1.3% of all crashes in the prior year to 1.9% in the current year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 1100.0%

0

Other Killed

Prior: 00.0%

9

Pedestrians Injured

Prior: 2350.0%

1

Cyclists Injured

Prior: 3-66.7%

129

Motorists Injured

Prior: 136-5.1%

1

Other Injured

Prior: 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 showed a slight shift between the two periods. In 2024, the peak day for crashes was Wednesday with 77 incidents, a change from Thursday (62 incidents) in the prior year. The peak hour for collisions remained 1 p.m. in both periods, though the crash count during that hour increased from 30 to 40.

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 severity of crashes worsened year-over-year. The number of fatal crashes increased from one in 2023 to three in 2024, which elevated the fatal crash rate from 0.27% to 0.72%. Crashes involving serious injuries also increased in count from five to nine, while those resulting in minor injuries decreased from 69 to 59.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.7%
200.0%prior 1
Serious Injury9serious injury crashes2.2%
80.0%prior 5
Minor Injury59minor injury crashes14.3%
-14.5%prior 69
Possible Injury38possible injury crashes9.2%
35.7%prior 28
No Injury302no injury crashes72.9%
11.4%prior 271

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 top three contributing factors remained consistent across both years: "No improper driving," "Failed to yield right of way," and "Inattention." However, the count of crashes where no improper driving was cited grew by 54.9%, from 71 in 2023 to 110 in 2024. Conversely, crashes attributed to failing to yield the right of way saw their count decrease by 13.2%, from 68 to 59.

Officer-Reported Primary Contributing Cause

No improper driving110 (26.6%)54.9%prior 71
Failed to yield right of way59 (14.3%)-13.2%prior 68
Inattention52 (12.6%)2.0%prior 51
Followed too closely38 (9.2%)-13.6%prior 44
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner19 (4.6%)-24.0%prior 25
Disregarded traffic signs, signals, road markings16 (3.9%)14.3%prior 14
Failure to keep in proper lane or running off road14 (3.4%)-12.5%prior 16
Other improper action13 (3.1%)8.3%prior 12
Distracted9 (2.2%)-18.2%prior 11
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway9 (2.2%)50.0%prior 6

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 environmental conditions was largely stable year-over-year. The majority of incidents in both 2024 and 2023 occurred in clear weather (65.7% and 66.9% of total crashes, respectively) and on dry road surfaces (73.7% and 76.3%). Crashes during daylight hours constituted the largest share in both periods, accounting for 73.9% of crashes in 2024 compared to 70.1% in 2023.

Weather

Clear272 (65.9%)
8.4%prior 251
Cloudy33 (8.0%)
10.0%prior 30
Rain28 (6.8%)
-24.3%prior 37
Cloudy/Rain18 (4.4%)
80.0%prior 10
Snow14 (3.4%)
Clear/Unknown14 (3.4%)
7.7%prior 13
Clear/Other7 (1.7%)
0.0%prior 7
Rain/Cloudy6 (1.5%)
20.0%prior 5
Clear/Clear4 (1.0%)
Sleet, hail (freezing rain or drizzle)3 (0.7%)

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

Lighting

Daylight306 (73.9%)
16.3%prior 263
Dark - lighted roadway80 (19.3%)
8.1%prior 74
Dark - roadway not lighted14 (3.4%)
-12.5%prior 16
Dawn7 (1.7%)
-22.2%prior 9
Dusk7 (1.7%)
-30.0%prior 10

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

Road Surface

Dry305 (73.8%)
6.6%prior 286
Wet83 (20.1%)
1.2%prior 82
Snow14 (3.4%)
Ice5 (1.2%)
Slush3 (0.7%)
Sand, mud, dirt, oil, gravel2 (0.5%)
Other1 (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—Toyota, Honda, and Ford—were the same in both periods, with each seeing an increase in their total counts. The age demographics of persons involved in collisions shifted, with the 35-44 age group becoming the most represented in 2024 at 167 individuals, up from 126 in 2023. In the prior year, the 26-34 age group was the largest cohort with 165 individuals.

Top Vehicle Makes (757 vehicles)

1
TOYOTA149 (19.7%)
12.0%prior 133
2
HONDA121 (16%)
40.7%prior 86
3
FORD87 (11.5%)
16.0%prior 75
4
CHEVROLET46 (6.1%)
-8.0%prior 50
5
JEEP32 (4.2%)
18.5%prior 27
6
NISSAN31 (4.1%)
-16.2%prior 37
7
KIA23 (3%)
9.5%prior 21
8
BMW22 (2.9%)
-8.3%prior 24
9
HYUNDAI20 (2.6%)
-4.8%prior 21
10
SUBARU20 (2.6%)
-28.6%prior 28

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

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

Sex Distribution (926 persons with recorded sex)

Male538 (58.1%)
4.7%prior 514
Female388 (41.9%)
16.5%prior 333

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 238 to 244. The location of fatal crashes shifted from a 20 mph zone in 2023 (one fatality) to 25 mph and 30 mph zones in 2024 (one and two fatalities, respectively). Crashes in 45 mph zones remained nearly unchanged, with 51 incidents in 2024 compared to 50 in the prior year.

Fatal crashes by zone: 25 mph: 1 of 21 (4.762%) · 30 mph: 2 of 244 (0.82%)

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: NORWOOD, MA
  • Total crash records analyzed: 414
  • Total persons involved: 975
  • Total vehicles involved: 757

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). "NORWOOD, 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/norwood/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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Norwood, MA Crash Report — 2024 | ThatCarHitMe.com