Yearly Traffic Safety Analysis

799 CRASHES IN
BOURNE, MA
2023

All metrics benchmarked against2022

In 2023, Bourne recorded 799 total vehicle crashes, a 13.5% increase from the 704 crashes reported in 2022. While overall crashes rose, the number of injuries decreased from 211 to 174. The most notable year-over-year shift was a 116% increase in hit-and-run incidents, which grew from 37 in 2022 to 80 in 2023.

799

13.5%was 704

Total Crash Events

0

Persons Killed

174

-17.5%was 211

Persons Injured

80

116.2%was 37

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 31 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 totals in Bourne trended upward, increasing by 13.5% from 704 in 2022 to 799 in 2023. In contrast to the rising crash volume, the number of persons injured in these incidents fell by 17.5%, from 211 to 174. No traffic fatalities were recorded in either year.

80

Hit-and-Run Crashes — 2023

116.2% vs prior (37)

Hit-and-run crashes showed a significant upward trend. The total number of hit-and-run incidents more than doubled, increasing by 116% from 37 in 2022 to 80 in 2023. Consequently, the hit-and-run rate, which measures the share of total crashes that are hit-and-runs, nearly doubled from 5.3% in 2022 to 10.0% in 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

7

Pedestrians Injured

Prior: 2250.0%

2

Cyclists Injured

Prior: 3-33.3%

163

Motorists Injured

Prior: 206-20.9%

2

Other Injured

Prior: 0%

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 distribution of crashes remained consistent year-over-year. Friday was the peak day for crashes in both 2023 (131 incidents) and 2022 (126 incidents). The 4 p.m. hour was also the most frequent time for collisions in both periods, accounting for 77 crashes in 2023 and 72 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

No fatal crashes were reported in either 2022 or 2023. Although total crashes increased, the overall severity of incidents decreased, with the proportion of no-injury crashes rising from 73.9% in 2022 to 79.1% in 2023. The number of crashes involving serious injuries declined from 18 to 16, and minor injury crashes fell from 82 to 72.

Outcome by Severity (Crash Events)

Serious Injury16serious injury crashes2%
-11.1%prior 18
Minor Injury72minor injury crashes9%
-12.2%prior 82
Possible Injury48possible injury crashes6%
-14.3%prior 56
No Injury632no injury crashes79.1%
21.5%prior 520

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 top contributing factors for crashes were consistent across both periods, led by "Failed to yield right of way" and "Followed too closely." The count of crashes attributed to following too closely increased by 40%, from 80 incidents in 2022 to 112 in 2023. Similarly, crashes involving a failure to yield right of way rose by 36% from 86 to 117. Crashes linked to inattention, however, remained stable with 68 incidents in 2023 compared to 70 in 2022.

Officer-Reported Primary Contributing Cause

No improper driving163 (20.4%)3.8%prior 157
Failed to yield right of way117 (14.6%)36.0%prior 86
Followed too closely112 (14%)40.0%prior 80
Inattention68 (8.5%)-2.9%prior 70
Failure to keep in proper lane or running off road57 (7.1%)11.8%prior 51
Driving too fast for conditions31 (3.9%)34.8%prior 23
Made an improper turn30 (3.8%)66.7%prior 18
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner28 (3.5%)33.3%prior 21
Other improper action23 (2.9%)15.0%prior 20
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway17 (2.1%)112.5%prior 8

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

Crashes in both years occurred predominantly in clear weather and on dry roads. In 2023, the proportion of crashes in clear weather was 70.3%, down from a 78.3% share in 2022, though the absolute count was similar (562 vs. 551). Daylight crashes accounted for the majority of incidents in both periods, representing 70.7% of the total in 2023 and 73.4% in 2022. The share of crashes on wet roads remained stable at approximately 14% for both years.

Weather

Clear562 (73.9%)
2.0%prior 551
Cloudy77 (10.1%)
45.3%prior 53
Rain50 (6.6%)
31.6%prior 38
Cloudy/Rain18 (2.4%)
100.0%prior 9
Snow14 (1.8%)
75.0%prior 8
Clear/Cloudy8 (1.1%)
Sleet, hail (freezing rain or drizzle)5 (0.7%)
Snow/Sleet, hail (freezing rain or drizzle)5 (0.7%)
Fog, smog, smoke4 (0.5%)
-33.3%prior 6
Cloudy/Fog, smog, smoke4 (0.5%)

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

Lighting

Daylight565 (71.3%)
9.3%prior 517
Dark - lighted roadway94 (11.9%)
6.8%prior 88
Dark - roadway not lighted86 (10.9%)
19.4%prior 72
Dusk30 (3.8%)
275.0%prior 8
Dawn15 (1.9%)
36.4%prior 11
Dark - unknown roadway lighting2 (0.3%)

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

Road Surface

Dry650 (82.1%)
14.8%prior 566
Wet111 (14.0%)
12.1%prior 99
Ice14 (1.8%)
-6.7%prior 15
Snow11 (1.4%)
-8.3%prior 12
Slush5 (0.6%)
Water (standing, moving)1 (0.1%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained largely the same, with Toyota (236), Ford (160), and Honda (134) leading in 2023. This is similar to 2022, when the top makes were Toyota (205), Ford (149), and Chevrolet (102). An analysis of persons involved shows that the 35-44 age group saw a notable increase in involvement, growing from 215 individuals in 2022 to 281 in 2023.

Top Vehicle Makes (1,426 vehicles)

1
TOYOTA236 (16.5%)
15.1%prior 205
2
FORD160 (11.2%)
7.4%prior 149
3
HONDA134 (9.4%)
34.0%prior 100
4
CHEVROLET103 (7.2%)
1.0%prior 102
5
NISSAN90 (6.3%)
32.4%prior 68
6
JEEP64 (4.5%)
1.6%prior 63
7
GMC52 (3.6%)
-1.9%prior 53
8
SUBARU52 (3.6%)
20.9%prior 43
9
KIA35 (2.5%)
66.7%prior 21
10
HYUNDAI34 (2.4%)
25.9%prior 27

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

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

Sex Distribution (1,617 persons with recorded sex)

Male920 (56.9%)
16.0%prior 793
Female697 (43.1%)
15.0%prior 606

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

The 25 mph speed zone accounted for the highest number of crashes in both periods, with incidents in this zone increasing from 158 in 2022 to 191 in 2023. A significant increase was also observed in 55 mph zones, where crashes rose from 73 to 101. Crashes in 40 mph zones were unchanged at 107 incidents in both years. No fatal crashes were recorded in any specific speed zone for either period.

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: BOURNE, MA
  • Total crash records analyzed: 799
  • Total persons involved: 1,845
  • Total vehicles involved: 1,426

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). "BOURNE, 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/bourne/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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Bourne, MA Crash Report — 2023 | ThatCarHitMe.com