Yearly Traffic Safety Analysis

289 CRASHES IN
REHOBOTH, MA
2024

All metrics benchmarked against2023

In 2024, Rehoboth recorded 289 traffic crashes, a 20.9% increase from the 239 crashes reported in 2023. While the number of fatalities decreased from two to one, total injuries rose by 21.6% from 74 to 90. The most notable year-over-year shift is the overall increase in both crash volume and the number of people injured.

289

20.9%was 239

Total Crash Events

1

-50.0%was 2

Persons Killed

90

21.6%was 74

Persons Injured

5

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Rehoboth are on an upward trend year-over-year, with total incidents increasing by 20.9% from 239 in 2023 to 289 in 2024. This was accompanied by a 21.6% rise in total injuries, from 74 to 90. However, the number of fatalities decreased from two in the prior year to one in the current year.

5

Hit-and-Run Crashes — 2024

0.0% vs prior (5)

The total number of hit-and-run crashes in Rehoboth remained stable at five incidents in both 2023 and 2024. However, due to the overall increase in total crashes in the current year, the hit-and-run rate per 100 crashes decreased. The rate fell from 2.1 in 2023 to 1.7 in 2024, indicating that hit-and-runs constituted a smaller proportion of all crashes in the most recent period.

Vulnerable Road User Casualties

1

Cyclists Killed

Prior: 0%

0

Motorists Killed

Prior: 2-100.0%

1

Cyclists Injured

Prior: 5-80.0%

89

Motorists Injured

Prior: 6929.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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 the two periods. The peak day for crashes moved from Tuesday (46 incidents) in 2023 to Friday (53 incidents) in 2024. Similarly, the peak hour for collisions shifted earlier, from 5 p.m. in the prior year (24 crashes) to 3 p.m. in the current year (31 crashes). Weekday afternoon hours saw a substantial increase in crash volume year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Although total crashes increased, the severity of crashes generally decreased year-over-year. The fatal crash rate fell from 0.84 per 100 crashes in 2023 to 0.35 in 2024, with fatal incidents dropping from two to one. The proportion of crashes resulting in serious injuries also declined from a 2.5% share to a 1.0% share. Conversely, the share of crashes with no injuries increased from 72.0% in the prior year to 78.2% in the current year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
-50.0%prior 2
Serious Injury3serious injury crashes1%
-50.0%prior 6
Minor Injury32minor injury crashes11.1%
0.0%prior 32
Possible Injury23possible injury crashes8%
4.5%prior 22
No Injury226no injury crashes78.2%
31.4%prior 172

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted between the two years. "Failed to yield right of way" saw a significant increase, more than doubling from 21 crashes in 2023 to 49 in 2024, making it the second most cited factor in the current period. Crashes attributed to "Failure to keep in proper lane or running off road" also doubled in count from 11 to 22. Conversely, crashes attributed to "Followed too closely" decreased from 21 to 13 incidents.

Officer-Reported Primary Contributing Cause

No improper driving108 (37.4%)24.1%prior 87
Failed to yield right of way49 (17%)133.3%prior 21
Failure to keep in proper lane or running off road22 (7.6%)100.0%prior 11
Other improper action18 (6.2%)80.0%prior 10
Inattention17 (5.9%)70.0%prior 10
Followed too closely13 (4.5%)-38.1%prior 21
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner10 (3.5%)-28.6%prior 14
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway10 (3.5%)25.0%prior 8
Fatigued/asleep8 (2.8%)
Driving too fast for conditions7 (2.4%)-30.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across environmental conditions showed a notable shift, particularly concerning winter weather. Crashes occurring on snow or ice-covered roads increased from 9 incidents in 2023 to 44 in 2024. Correspondingly, crashes reported during snow or sleet conditions rose from 6 to 33. While most crashes in both years happened in daylight on dry roads, the proportion of crashes in these ideal conditions decreased in 2024 as adverse weather-related incidents became more frequent.

Weather

Clear195 (67.5%)
9.6%prior 178
Cloudy27 (9.3%)
42.1%prior 19
Snow25 (8.7%)
Rain17 (5.9%)
0.0%prior 17
Snow/Sleet, hail (freezing rain or drizzle)8 (2.8%)
Cloudy/Rain7 (2.4%)
-12.5%prior 8
Cloudy/Snow2 (0.7%)
Clear/Clear2 (0.7%)
Rain/Severe crosswinds2 (0.7%)
Rain/Cloudy2 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight188 (65.1%)
29.7%prior 145
Dark - roadway not lighted71 (24.6%)
6.0%prior 67
Dark - lighted roadway12 (4.2%)
-7.7%prior 13
Dusk10 (3.5%)
11.1%prior 9
Dawn8 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry206 (71.3%)
10.2%prior 187
Wet36 (12.5%)
-10.0%prior 40
Snow31 (10.7%)
Ice13 (4.5%)
160.0%prior 5
Sand, mud, dirt, oil, gravel2 (0.7%)
Water (standing, moving)1 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

While the top vehicle makes involved in crashes—Toyota, Ford, and Chevrolet—remained consistent across both years with increased counts, the age demographics of persons involved showed a significant change. The number of individuals in the 16-20 age group more than doubled, rising from 40 in 2023 to 91 in 2024. As a result, this group's share of all persons involved in crashes increased from 8.6% to 15.7%. The representation of other age groups remained relatively stable year-over-year.

Top Vehicle Makes (450 vehicles)

1
TOYOTA73 (16.2%)
9.0%prior 67
2
FORD60 (13.3%)
20.0%prior 50
3
CHEVROLET43 (9.6%)
19.4%prior 36
4
HONDA39 (8.7%)
30.0%prior 30
5
NISSAN27 (6%)
68.8%prior 16
6
HYUNDAI23 (5.1%)
109.1%prior 11
7
GMC21 (4.7%)
90.9%prior 11
8
JEEP20 (4.4%)
100.0%prior 10
9
KIA15 (3.3%)
25.0%prior 12
10
VOLKSWAGEN15 (3.3%)
50.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (555 persons with recorded sex)

Male337 (60.7%)
23.9%prior 272
Female218 (39.3%)
40.6%prior 155

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones remained broadly similar, with most incidents occurring in 35, 40, and 50 mph zones in both years. However, the number of crashes in 35 mph zones saw the largest increase, rising from 47 to 70. The locations of fatal crashes shifted; in 2024, the single fatality occurred in a 45 mph zone, whereas in 2023, fatalities were recorded in 25 mph and 40 mph zones.

Fatal crashes by zone: 45 mph: 1 of 19 (5.263%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: REHOBOTH, MA
  • Total crash records analyzed: 289
  • Total persons involved: 578
  • Total vehicles involved: 450

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). "REHOBOTH, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rehoboth/2024-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

ThatCarHitMe.com · An Injuria.ai Company

Rehoboth, MA Crash Report — 2024 | ThatCarHitMe.com