Monthly Traffic Safety Analysis

529 CRASHES IN
BOSTON, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, Boston experienced 529 total crashes, a slight decrease of 1.67% compared to the 538 crashes in October 2022. The most notable year-over-year shift was an 80% reduction in total fatalities, from 5 in October 2022 to 1 in October 2023. Conversely, total injuries increased by 54.14%, from 133 to 205.

529

-1.7%was 538

Total Crash Events

1

-80.0%was 5

Persons Killed

205

54.1%was 133

Persons Injured

72

33.3%was 54

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the total number of crashes remained relatively stable, decreasing by 1.67% from 538 to 529. However, total fatalities saw a significant downward trend, dropping by 80% year-over-year, while total injuries increased by 54.14%.

72

Hit-and-Run Crashes — October 2023

33.3% vs prior (54)

Hit-and-run crashes increased by 33.33%, from 54 incidents in October 2022 to 72 in October 2023. The hit-and-run rate also rose from 10% to 13.6% of all crashes, indicating an upward trend in these types of incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 3-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 2-50.0%

0

Other Killed

Prior: 00.0%

11

Pedestrians Injured

Prior: 922.2%

4

Cyclists Injured

Prior: 5-20.0%

187

Motorists Injured

Prior: 11957.1%

3

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday or Sunday (85 crashes each) in October 2022 to Monday (92 crashes) in October 2023. The peak hour also changed, moving from 7 p.m. with 37 crashes in October 2022 to 4 p.m. with 41 crashes in October 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate significantly decreased from 0.74% in October 2022 to 0.19% in October 2023. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) increased from 17.66% of total crashes in October 2022 to 27.22% in October 2023.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
-75.0%prior 4
Serious Injury11serious injury crashes2.1%
57.1%prior 7
Minor Injury89minor injury crashes16.8%
71.2%prior 52
Possible Injury44possible injury crashes8.3%
22.2%prior 36
No Injury367no injury crashes69.4%
46.2%prior 251

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

The top three contributing factors remained consistent in ranking, with 'Followed too closely' increasing by 19 crashes (26.03%) and 'No improper driving' increasing by 18 crashes (29.51%). 'Failed to yield right of way' saw a 100% increase in count, rising from 28 crashes to 56. In contrast, crashes attributed to 'Exceeded authorized speed limit' decreased by 7 crashes (43.75%).

Officer-Reported Primary Contributing Cause

Followed too closely92 (17.4%)26.0%prior 73
No improper driving79 (14.9%)29.5%prior 61
Failed to yield right of way56 (10.6%)100.0%prior 28
Failure to keep in proper lane or running off road31 (5.9%)138.5%prior 13
Other improper action24 (4.5%)4.3%prior 23
Inattention23 (4.3%)0.0%prior 23
Driving too fast for conditions20 (3.8%)-13.0%prior 23
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner17 (3.2%)112.5%prior 8
Disregarded traffic signs, signals, road markings16 (3%)45.5%prior 11
Exceeded authorized speed limit9 (1.7%)-43.8%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions slightly increased from 357 to 365, while those in 'Rain' decreased from 72 to 59. The number of crashes on 'Wet' road surfaces decreased from 98 to 79. Crashes occurring in 'Dark - lighted roadway' conditions also decreased from 213 to 189.

Weather

Clear365 (77.5%)
2.2%prior 357
Rain59 (12.5%)
-18.1%prior 72
Cloudy36 (7.6%)
-29.4%prior 51
Cloudy/Rain6 (1.3%)
-40.0%prior 10
Clear/Cloudy4 (0.8%)
Clear/Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight267 (53.8%)
-0.4%prior 268
Dark - lighted roadway189 (38.1%)
-11.3%prior 213
Dawn14 (2.8%)
0.0%prior 14
Dusk13 (2.6%)
116.7%prior 6
Dark - roadway not lighted6 (1.2%)
20.0%prior 5
Dark - unknown roadway lighting5 (1.0%)
Other2 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry386 (83.0%)
-1.0%prior 390
Wet79 (17.0%)
-19.4%prior 98

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

The number of persons involved in crashes increased across most age groups, with the 26-34 age group showing a notable increase from 176 to 302 persons. Male persons involved in crashes increased from 450 to 720, and female persons increased from 268 to 376. Toyota remained the most frequently involved vehicle make, though its count decreased from 216 to 200.

Top Vehicle Makes (1,060 vehicles)

1
TOYOTA200 (18.9%)
-7.4%prior 216
2
HONDA160 (15.1%)
8.1%prior 148
3
FORD100 (9.4%)
-7.4%prior 108
4
NISSAN69 (6.5%)
16.9%prior 59
5
CHEVROLET57 (5.4%)
-8.1%prior 62
6
JEEP49 (4.6%)
-9.3%prior 54
7
HYUNDAI39 (3.7%)
56.0%prior 25
8
BMW35 (3.3%)
40.0%prior 25
9
SUBARU33 (3.1%)
13.8%prior 29
10
KIA23 (2.2%)
9.5%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (1,096 persons with recorded sex)

Male720 (65.7%)
60.0%prior 450
Female376 (34.3%)
40.3%prior 268

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed limit zone increased from 159 to 176, while the fatal rate in this zone slightly decreased from 0.629% to 0.568%. Notably, fatal crashes in the 55 mph speed limit zone decreased from 3 in October 2022 to 0 in October 2023, contributing to the overall reduction in total fatal crashes.

Fatal crashes by zone: 25 mph: 1 of 176 (0.568%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: BOSTON, MA
  • Total crash records analyzed: 529
  • Total persons involved: 1,300
  • Total vehicles involved: 1,060

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). "BOSTON, MA Crash Intelligence Report: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/boston/october-2023-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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Boston, MA Crash Report — October 2023 | ThatCarHitMe.com