Yearly Traffic Safety Analysis

5,973 CRASHES IN
BOSTON, MA
2023

All metrics benchmarked against2022

Total crashes in Boston increased from 5,744 in 2022 to 5,973 in 2023, representing a 3.99% rise. The most notable year-over-year shift was a 65.91% increase in total injuries, from 1,411 to 2,341.

5,973

▲ 4.0%was 5,744

Total Crash Events

▼ -20.8%was 24

Persons Killed

2,341

▲ 65.9%was 1,411

Persons Injured

811

▲ 27.9%was 634

Hit-and-Run Crashes

Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (18) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 273 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

Overall, crash data for Boston shows an upward trend in total crashes and injuries from 2022 to 2023. Total crashes increased by 229, a 3.99% rise, while total injuries saw a substantial increase of 930, marking a 65.91% growth. Conversely, total fatalities decreased by 5, a 20.83% reduction year-over-year.

811

Hit-and-Run Crashes — 2023

▲ 27.9% vs prior (634)

Hit-and-run crashes in Boston increased from 634 in 2022 to 811 in 2023, marking a 27.92% rise. Concurrently, the hit-and-run rate increased by 2.6 percentage points, from 11% in 2022 to 13.6% in 2023, indicating an upward trend.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 12↓-33.3%

Cyclists Killed

Prior: 1→0.0%

Motorists Killed

Prior: 11↓-9.1%

Other Killed

Prior: 0→0.0%

149

Pedestrians Injured

Prior: 134↑11.2%

Cyclists Injured

Prior: 64↑9.4%

2,107

Motorists Injured

Prior: 1,205↑74.9%

Other Injured

Prior: 8↑87.5%

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 for crashes in Boston showed some shifts between 2022 and 2023. The peak day for crashes moved from Saturday with 910 crashes in 2022 to Sunday with 903 crashes in 2023. The peak hour for crashes also shifted from 3 PM with 357 crashes in 2022 to 4 PM with 372 crashes in 2023.

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

Boston experienced a decrease in fatal crash events and total fatalities from 2022 to 2023, with fatal crashes decreasing by 18.18% (from 22 to 18) and total fatalities decreasing by 20.83% (from 24 to 19). However, there was a notable increase across all injury severity categories. Serious injury crashes (severity A) increased by 77 crashes (from 49 to 126), minor injury crashes (severity B) increased by 379 crashes (from 666 to 1045), and possible injury crashes (severity C) increased by 178 crashes (from 370 to 548).

Severity is per crash event (most severe injury). 18 fatal crash events resulted in 19 persons killed.

Outcome by Severity (Crash Events)

Fatal18fatal crashes0.3%

↓-18.2%prior 22

Serious Injury126serious injury crashes2.1%

↑157.1%prior 49

Minor Injury1,045minor injury crashes17.5%

↑56.9%prior 666

Possible Injury548possible injury crashes9.2%

↑48.1%prior 370

No Injury3,963no injury crashes66.3%

↑34.8%prior 2,940

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

Among contributing factors, "No improper driving" increased by 304 crashes (from 782 to 1086), a 38.87% rise year-over-year. "Failed to yield right of way" saw a significant increase of 193 crashes (from 342 to 535), a 56.43% change in count. "Followed too closely" also increased by 82 crashes (from 776 to 858), a 10.57% change in count.

Officer-Reported Primary Contributing Cause

No improper driving1,086 (18.2%)↑38.9%prior 782

Followed too closely858 (14.4%)↑10.6%prior 776

Failed to yield right of way535 (9%)↑56.4%prior 342

Disregarded traffic signs, signals, road markings286 (4.8%)↑68.2%prior 170

Failure to keep in proper lane or running off road268 (4.5%)↑57.6%prior 170

Inattention267 (4.5%)↑21.4%prior 220

Other improper action189 (3.2%)↓-6.0%prior 201

Driving too fast for conditions189 (3.2%)↑8.0%prior 175

Exceeded authorized speed limit175 (2.9%)↓-3.3%prior 181

Made an improper turn168 (2.8%)↑46.1%prior 115

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

Analysis of conditions reveals shifts in weather and road surface involvement in crashes. Crashes occurring in "Rain" conditions increased by 122 (from 562 to 684), while those in "Snow" conditions decreased by 40 (from 92 to 52). Crashes on "Wet" road surfaces increased by 188 (from 821 to 1009), whereas those on "Ice" surfaces decreased by 23 (from 55 to 32).

Weather

Clear3,962 (73.1%)

↓-3.9%prior 4,124

Rain684 (12.6%)

↑21.7%prior 562

Cloudy461 (8.5%)

↑5.5%prior 437

Cloudy/Rain123 (2.3%)

↑66.2%prior 74

Snow52 (1.0%)

↓-43.5%prior 92

Sleet, hail (freezing rain or drizzle)33 (0.6%)

↑65.0%prior 20

Clear/Cloudy20 (0.4%)

↑150.0%prior 8

Other14 (0.3%)

↓-22.2%prior 18

Rain/Cloudy11 (0.2%)

↑22.2%prior 9

Fog, smog, smoke11 (0.2%)

↑57.1%prior 7

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

Lighting

Daylight3,102 (55.1%)

↑3.1%prior 3,009

Dark - lighted roadway2,152 (38.3%)

↑1.5%prior 2,120

Dusk134 (2.4%)

↑57.6%prior 85

Dawn117 (2.1%)

↓-37.8%prior 188

Dark - roadway not lighted61 (1.1%)

↓-17.6%prior 74

Dark - unknown roadway lighting40 (0.7%)

↑8.1%prior 37

Other19 (0.3%)

↑90.0%prior 10

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

Road Surface

Dry4,237 (79.5%)

↓-0.8%prior 4,270

Wet1,009 (18.9%)

↑22.9%prior 821

Ice32 (0.6%)

↓-41.8%prior 55

Snow28 (0.5%)

↓-68.2%prior 88

Slush17 (0.3%)

↑30.8%prior 13

Water (standing, moving)4 (0.1%)

Sand, mud, dirt, oil, gravel3 (0.1%)

↓-78.6%prior 14

Other2 (0.0%)

↓-84.6%prior 13

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 486, from 11,336 in 2022 to 11,822 in 2023, a 4.29% rise. Among top makes, TOYOTA and HONDA continued to be the most involved, with TOYOTA increasing by 95 vehicles (from 2070 to 2165) and HONDA increasing by 116 vehicles (from 1697 to 1813). NISSAN involvement slightly decreased by 4 vehicles, from 715 to 711.

Top Vehicle Makes (11,822 vehicles)

TOYOTA2,165 (18.3%)

↑4.6%prior 2,070

HONDA1,813 (15.3%)

↑6.8%prior 1,697

FORD1,198 (10.1%)

↑0.3%prior 1,194

NISSAN711 (6%)

↓-0.6%prior 715

CHEVROLET637 (5.4%)

↑4.6%prior 609

JEEP539 (4.6%)

↑4.3%prior 517

HYUNDAI359 (3%)

↑10.1%prior 326

SUBARU336 (2.8%)

↑0.6%prior 334

BMW292 (2.5%)

↑10.2%prior 265

KIA258 (2.2%)

↑8.9%prior 237

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

2,032 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (12,130 persons with recorded sex)

Male7,618 (62.8%)

↑38.4%prior 5,504

Female4,509 (37.2%)

↑35.6%prior 3,326

X / Unspecified3 (0.0%)

↑50.0%prior 2

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 25 MPH speed zones increased by 150 (from 1942 to 2092), with the number of fatal crashes remaining at 13 in both periods, resulting in a decrease in the fatal rate from 0.669% to 0.621%. In 55 MPH zones, crashes decreased by 14 (from 703 to 689), and fatal crashes significantly dropped from 6 to 1, leading to a substantial decrease in the fatal rate from 0.853% to 0.145%. Conversely, 30 MPH zones saw a decrease of 30 crashes (from 449 to 419) but an increase from 0 to 1 fatal crash.

Fatal crashes by zone: 25 mph: 13 of 2,092 (0.621%) · 30 mph: 1 of 419 (0.239%) · 35 mph: 1 of 519 (0.193%) · 45 mph: 1 of 734 (0.136%) · 55 mph: 1 of 689 (0.145%)

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: BOSTON, MA
Total crash records analyzed: 5,973
Total persons involved: 14,530
Total vehicles involved: 11,822

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: 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/boston/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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5,973 CRASHES INBOSTON, MA2023