ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WALTHAM, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/waltham/2022-annual-report
Yearly Traffic Safety Analysis
1,602 CRASHES IN
WALTHAM, MA
2022
In 2022, Waltham recorded 1,602 total vehicle crashes, a 15.1% increase from the 1,392 crashes documented in 2021. This rise in overall crash volume was accompanied by an increase in total injuries from 329 to 360 and a rise in fatalities from one to three. The most notable year-over-year shift was this significant increase in the total number of crashes.
1,602
▲ 15.1%was 1,392
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
360
▲ 9.4%was 329
Persons Injured
325
▲ 24.5%was 261
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 161 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Waltham showed a rising trend year-over-year. The total number of crashes increased by 15.1%, from 1,392 in 2021 to 1,602 in 2022. This trend included an increase in total injuries from 329 to 360 and an increase in fatalities from one to three.
325
Hit-and-Run Crashes — 2022
▲ 24.5% vs prior (261)
Hit-and-run crashes increased in both count and rate. The number of hit-and-run incidents rose from 261 in 2021 to 325 in 2022. The corresponding hit-and-run rate also climbed, from 18.8% of all crashes in the prior year to 20.3% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
27
Pedestrians Injured
22
Cyclists Injured
311
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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 between the two periods. Friday was the peak day for crashes in both 2021 (238 crashes) and 2022 (267 crashes), and the 3 p.m. hour was the peak hour in both years (132 and 167 crashes, respectively). While the peak times did not shift, the volume of crashes during these and other times, particularly weekday afternoons, increased in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted year-over-year, with the number of fatal crashes increasing from one to three, raising the fatal crash rate from 0.07% to 0.19%. While the absolute count of serious injury crashes was nearly unchanged (138 in 2022 vs. 137 in 2021), their proportion of total crashes decreased from 9.8% to 8.6%. The share of non-injury crashes grew, increasing from 70.2% of all incidents in 2021 to 72.5% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors were consistent across both years, though their counts and rankings changed. Crashes attributed to 'Inattention' grew from 226 to 295, a 30.5% increase in count, making it the top factor in 2022 after being second in 2021. 'Failed to yield right of way' incidents increased by 33.9% (from 124 to 166), and 'Followed too closely' incidents rose from 105 to 131.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both years, the vast majority of crashes occurred in clear weather, during daylight, and on dry roads. The proportion of crashes under these favorable conditions saw a slight increase in 2022. Crashes in daylight grew from 67.2% to 69.4% of the total, while incidents on dry roads increased from 78.9% to 80.4% of the total. The absolute number of crashes in adverse conditions also rose, in line with the overall increase in crash volume.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same in both 2021 and 2022, with their involvement counts increasing proportionally with the overall crash trend. The number of people involved in crashes increased across all reported age demographics. The largest numerical increases were observed in the 35-44 age group, which grew from 412 to 510 individuals, and the 65+ age group, which increased from 283 to 372 individuals.
Top Vehicle Makes (3,108 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
713 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,119 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones, the most frequent location for incidents, increased from 966 in 2021 to 1,108 in 2022, and the number of fatalities in this zone rose from one to two. Conversely, crashes in 55 mph zones saw a slight decrease from 147 to 139. However, the 55 mph zone recorded one fatal crash in 2022, where none had occurred in the prior year.
Fatal crashes by zone: 30 mph: 2 of 1,108 (0.181%) · 55 mph: 1 of 139 (0.719%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: WALTHAM, MA
- Total crash records analyzed: 1,602
- Total persons involved: 3,782
- Total vehicles involved: 3,108
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). "WALTHAM, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/waltham/2022-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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved