Yearly Traffic Safety Analysis

507 CRASHES IN
NEEDHAM, MA
2022

All metrics benchmarked against2021

In 2022, Needham recorded 507 total crashes, an 11.7% increase from the 454 crashes documented in 2021. While the number of fatalities decreased from two to one year-over-year, the number of people injured rose by 35.1%, from 97 in 2021 to 131 in 2022. The most significant percentage change was observed in crashes involving a driver suspected of being under the influence of alcohol, which increased from 7 to 13 incidents.

507

11.7%was 454

Total Crash Events

1

-50.0%was 2

Persons Killed

131

35.1%was 97

Persons Injured

22

57.1%was 14

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 12 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Needham indicates a rising trend in 2022 compared to the prior year. Total collisions increased by 11.7%, from 454 to 507. This was accompanied by a 35.1% increase in total injuries, which grew from 97 to 131, while fatalities declined from two to one.

22

Hit-and-Run Crashes — 2022

57.1% vs prior (14)

Hit-and-run crashes increased in both absolute numbers and as a proportion of total crashes in 2022. The count of hit-and-run incidents rose from 14 in 2021 to 22 in 2022, a 57.1% increase in volume. Consequently, the hit-and-run rate trended upward, increasing from 3.1% of all crashes in the prior year to 4.3% in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 2-50.0%

0

Other Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 7-71.4%

12

Cyclists Injured

Prior: 850.0%

116

Motorists Injured

Prior: 8143.2%

1

Other Injured

Prior: 10.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between 2021 and 2022. The peak day for collisions moved from Friday (83 incidents) in 2021 to Wednesday (95 incidents) in 2022. Similarly, the most common time for a crash shifted an hour earlier, from the 4 PM hour in 2021 (50 crashes) to the 3 PM hour in 2022 (56 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes remained stable at one incident in both 2021 and 2022, the overall severity of non-fatal crashes increased. The count of serious injury crashes more than doubled from 5 to 12, with their share of total crashes rising from 1.1% to 2.4%. The proportions of both minor and possible injury crashes also increased, while the share of crashes resulting in no injury fell from 80.2% in 2021 to 76.1% in 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
0.0%prior 1
Serious Injury12serious injury crashes2.4%
140.0%prior 5
Minor Injury58minor injury crashes11.4%
31.8%prior 44
Possible Injury38possible injury crashes7.5%
31.0%prior 29
No Injury386no injury crashes76.1%
6.0%prior 364

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors changed year-over-year. 'Inattention' became the leading factor in 2022 with 85 incidents, an 18.1% increase in count from 72 in the prior year. 'Failed to yield right of way' saw a 37.5% increase in count, rising from 56 to 77 incidents. In contrast, crashes with 'No improper driving' cited as the main factor decreased by 17.4% in count, from 92 to 76, falling from the top-ranked factor in 2021 to third place in 2022.

Officer-Reported Primary Contributing Cause

Inattention85 (16.8%)18.1%prior 72
Failed to yield right of way77 (15.2%)37.5%prior 56
No improper driving76 (15%)-17.4%prior 92
Followed too closely51 (10.1%)13.3%prior 45
Failure to keep in proper lane or running off road31 (6.1%)10.7%prior 28
Driving too fast for conditions22 (4.3%)-18.5%prior 27
Other improper action21 (4.1%)5.0%prior 20
Disregarded traffic signs, signals, road markings18 (3.6%)20.0%prior 15
Made an improper turn15 (3%)114.3%prior 7
Distracted14 (2.8%)133.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In both periods, the vast majority of crashes occurred in clear weather and during daylight hours, with these proportions remaining stable year-over-year. For instance, daylight crashes accounted for 74.7% of incidents in 2021 and 75.1% in 2022. A notable shift occurred in lighting conditions, where the proportion of crashes taking place on dark but lighted roadways increased from 11.9% of all incidents in 2021 to 15.0% in 2022.

Weather

Clear359 (70.9%)
13.6%prior 316
Cloudy43 (8.5%)
-6.5%prior 46
Rain30 (5.9%)
-31.8%prior 44
Snow17 (3.4%)
54.5%prior 11
Cloudy/Rain16 (3.2%)
166.7%prior 6
Clear/Cloudy13 (2.6%)
44.4%prior 9
Snow/Sleet, hail (freezing rain or drizzle)7 (1.4%)
Clear/Other3 (0.6%)
Clear/Unknown3 (0.6%)
Snow/Blowing sand, snow3 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight381 (75.7%)
12.4%prior 339
Dark - lighted roadway76 (15.1%)
40.7%prior 54
Dark - roadway not lighted25 (5.0%)
-32.4%prior 37
Dusk18 (3.6%)
63.6%prior 11
Dawn2 (0.4%)
-77.8%prior 9
Dark - unknown roadway lighting1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry395 (78.1%)
8.2%prior 365
Wet69 (13.6%)
-1.4%prior 70
Snow26 (5.1%)
116.7%prior 12
Ice12 (2.4%)
Slush4 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—were the same in both years, and all saw an increase in total incidents. An analysis of persons involved in crashes reveals a demographic shift, with the number of individuals in the 65+ age group increasing from 124 in 2021 to 173 in 2022. This represents a growth in their share of all persons involved from 12.8% to 15.9% year-over-year.

Top Vehicle Makes (938 vehicles)

1
TOYOTA183 (19.5%)
41.9%prior 129
2
HONDA108 (11.5%)
4.9%prior 103
3
FORD84 (9%)
20.0%prior 70
4
JEEP46 (4.9%)
-6.1%prior 49
5
CHEVROLET45 (4.8%)
-18.2%prior 55
6
NISSAN43 (4.6%)
0.0%prior 43
7
SUBARU38 (4.1%)
2.7%prior 37
8
AUDI35 (3.7%)
52.2%prior 23
9
LEXUS34 (3.6%)
126.7%prior 15
10
BMW30 (3.2%)
30.4%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (1,014 persons with recorded sex)

Male576 (56.8%)
18.0%prior 488
Female438 (43.2%)
6.6%prior 411

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones shifted notably between 2021 and 2022. The number of collisions in 30 mph zones increased from 226 to 321, while crashes in 55 mph zones decreased from 123 to 102. The single fatal crash in 2022 occurred in a 30 mph zone, which is where the fatal crash in the prior year also took place.

Fatal crashes by zone: 30 mph: 1 of 321 (0.312%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: NEEDHAM, MA
  • Total crash records analyzed: 507
  • Total persons involved: 1,090
  • Total vehicles involved: 938

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). "NEEDHAM, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/needham/2022-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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Needham, MA Crash Report — 2022 | ThatCarHitMe.com