Yearly Traffic Safety Analysis

501 CRASHES IN
WESTWOOD, MA
2023

All metrics benchmarked against2022

In 2023, Westwood recorded 501 total vehicle crashes, an increase of 12.3% from the 446 crashes reported in 2022. The total number of injuries also rose from 92 to 102. A significant development in 2023 was the occurrence of two fatal crashes resulting in two deaths, whereas no fatalities were recorded in the prior year.

501

12.3%was 446

Total Crash Events

2

Persons Killed

102

10.9%was 92

Persons Injured

28

27.3%was 22

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Westwood show a year-over-year increase, with total incidents rising by 55, from 446 in 2022 to 501 in 2023. This represents a 12.3% increase in total collisions. Correspondingly, the number of people injured in these crashes grew by 10.9%, from 92 to 102.

28

Hit-and-Run Crashes — 2023

27.3% vs prior (22)

The number of hit-and-run crashes increased from 22 in 2022 to 28 in 2023, a rise of 27.3%. The hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, also trended upward. This rate increased from 4.9% in 2022 to 5.6% in 2023.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

5

Pedestrians Injured

Prior: 0%

2

Cyclists Injured

Prior: 0%

95

Motorists Injured

Prior: 923.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained consistent year-over-year. Thursday was the peak day for crashes in both 2023 (88 crashes) and 2022 (77 crashes). Similarly, the 4 p.m. hour was the most frequent time for collisions in both periods, with 53 incidents in 2023 compared to 49 in 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in 2023, with two fatal crashes recorded, compared to none in 2022. While the number of serious injury crashes decreased from 7 to 5, the counts for both minor injury crashes (43 vs. 33) and possible injury crashes (36 vs. 29) increased. Overall, crashes resulting in any level of injury rose from 69 in 2022 to 84 in 2023.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.4%
Serious Injury5serious injury crashes1%
-28.6%prior 7
Minor Injury43minor injury crashes8.6%
30.3%prior 33
Possible Injury36possible injury crashes7.2%
24.1%prior 29
No Injury407no injury crashes81.2%
11.2%prior 366

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in both years was 'Followed too closely,' with the count of such crashes increasing by 28.4% from 95 in 2022 to 122 in 2023. 'Inattention' also saw a significant rise, growing by 30.5% from 59 to 77 incidents, making it the second most common factor in 2023. Crashes attributed to 'Failed to yield right of way' experienced a notable 80% increase in count, rising from 30 incidents in 2022 to 54 in 2023.

Officer-Reported Primary Contributing Cause

Followed too closely122 (24.4%)28.4%prior 95
Inattention77 (15.4%)30.5%prior 59
No improper driving73 (14.6%)7.4%prior 68
Failed to yield right of way54 (10.8%)80.0%prior 30
Other improper action25 (5%)31.6%prior 19
Distracted21 (4.2%)10.5%prior 19
Failure to keep in proper lane or running off road20 (4%)-16.7%prior 24
Driving too fast for conditions11 (2.2%)10.0%prior 10
Made an improper turn9 (1.8%)12.5%prior 8
Disregarded traffic signs, signals, road markings9 (1.8%)-25.0%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In both 2023 and 2022, the majority of crashes occurred in clear weather, on dry roads, and during daylight hours. Crashes in daylight conditions increased from 340 to 375, though their share of total crashes remained stable at approximately 75-76%. Similarly, collisions on dry road surfaces rose from 369 to 428, and incidents during clear weather increased from 336 to 388, with no significant change in their proportional representation.

Weather

Clear/Clear228 (45.6%)
7.0%prior 213
Clear160 (32.0%)
30.1%prior 123
Cloudy/Cloudy22 (4.4%)
-8.3%prior 24
Rain/Rain18 (3.6%)
12.5%prior 16
Rain18 (3.6%)
5.9%prior 17
Cloudy14 (2.8%)
-6.7%prior 15
Clear/Cloudy8 (1.6%)
60.0%prior 5
Cloudy/Rain7 (1.4%)
Snow5 (1.0%)
-44.4%prior 9
Rain/Cloudy4 (0.8%)
-50.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight375 (74.9%)
10.3%prior 340
Dark - lighted roadway81 (16.2%)
28.6%prior 63
Dark - roadway not lighted30 (6.0%)
36.4%prior 22
Dusk7 (1.4%)
-50.0%prior 14
Dawn5 (1.0%)
-16.7%prior 6
Dark - unknown roadway lighting2 (0.4%)
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry428 (85.6%)
16.0%prior 369
Wet63 (12.6%)
12.5%prior 56
Snow4 (0.8%)
-66.7%prior 12
Slush2 (0.4%)
Ice2 (0.4%)
Water (standing, moving)1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford being the most frequent in both years. The number of Toyotas involved in crashes increased from 137 in 2022 to 163 in 2023, while Honda involvement remained unchanged at 111. Analysis of person age distribution shows a notable increase in individuals aged 26-34 involved in crashes, rising from 144 in 2022 to 185 in 2023. The 16-20 age group also saw an increase from 111 to 136 persons involved.

Top Vehicle Makes (936 vehicles)

1
TOYOTA163 (17.4%)
19.0%prior 137
2
HONDA111 (11.9%)
0.0%prior 111
3
FORD90 (9.6%)
-2.2%prior 92
4
NISSAN60 (6.4%)
27.7%prior 47
5
CHEVROLET55 (5.9%)
5.8%prior 52
6
JEEP50 (5.3%)
19.0%prior 42
7
SUBARU42 (4.5%)
27.3%prior 33
8
HYUNDAI31 (3.3%)
47.6%prior 21
9
AUDI29 (3.1%)
38.1%prior 21
10
VOLKSWAGEN26 (2.8%)
62.5%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (1,062 persons with recorded sex)

Male585 (55.1%)
17.7%prior 497
Female477 (44.9%)
13.0%prior 422

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones saw the largest increase, rising from 176 incidents in 2022 to 213 in 2023. Collisions in 55 mph zones also increased from 76 to 82. The two fatal crashes recorded in 2023 occurred in different speed zones: one in a 30 mph zone and the other in a 55 mph zone. No fatal crashes were reported in any speed zone during the prior year.

Fatal crashes by zone: 30 mph: 1 of 213 (0.469%) · 55 mph: 1 of 82 (1.22%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: WESTWOOD, MA
  • Total crash records analyzed: 501
  • Total persons involved: 1,111
  • Total vehicles involved: 936

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). "WESTWOOD, MA Crash Intelligence Report: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westwood/2023-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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Westwood, MA Crash Report — 2023 | ThatCarHitMe.com