ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LITTLETON, MA · 2023
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/littleton/2023-annual-report
Yearly Traffic Safety Analysis
318 CRASHES IN
LITTLETON, MA
2023
In 2023, Littleton recorded 318 total vehicle crashes, a decrease from the 348 crashes documented in 2022, representing an 8.6% year-over-year reduction. While overall crashes and injuries declined, the number of traffic fatalities increased from one in 2022 to three in 2023. The most significant shift in contributing factors was a 43% increase in the count of crashes attributed to 'Driving too fast for conditions'.
318
▼ -8.6%was 348
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
67
▼ -29.5%was 95
Persons Injured
11
▲ 37.5%was 8
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. 2 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
The overall trend in traffic crashes in Littleton is downward, with total incidents falling by 8.6% from 348 in 2022 to 318 in 2023. This decline was accompanied by a 29.5% decrease in total injuries, which dropped from 95 to 67. However, this positive trend was contrasted by a rise in fatalities from one to three over the same period.
11
Hit-and-Run Crashes — 2023
▲ 37.5% vs prior (8)
Hit-and-run incidents trended upward between the two periods. The total count of hit-and-run crashes increased from 8 in 2022 to 11 in 2023. Consequently, the hit-and-run rate, as a percentage of total crashes, also rose from 2.3% to 3.5% year-over-year.
Vulnerable Road User Casualties
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
1
Cyclists Injured
64
Motorists Injured
2
Other Injured
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 timing of crashes remained broadly consistent year-over-year, with afternoon commute hours being the most frequent period for collisions. In 2023, the peak day for crashes shifted slightly to Thursday (59 crashes) from Friday (58 crashes) in the prior year. Similarly, the peak hour moved one hour earlier to the 4 p.m. hour in 2023, which saw 29 crashes, compared to the 5 p.m. hour in 2022 with 32 crashes.
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
While total crashes decreased, the severity of outcomes worsened, with fatal crashes increasing from one in 2022 to three in 2023, raising the fatal crash rate from 0.29% to 0.94%. Despite this, the total number of people injured fell from 95 to 67. The proportion of crashes involving any level of injury (from possible to fatal) decreased from 18.7% of all crashes in 2022 to 13.8% in 2023.
Outcome by Severity (Crash Events)
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 leading contributing factors remained consistent across both years, with 'No improper driving,' 'Followed too closely,' and 'Inattention' as the top three reported circumstances. The count for crashes involving 'Followed too closely' (from 49 to 51) and 'Inattention' (from 48 to 50) saw minimal change. Notably, the count of crashes attributed to 'Driving too fast for conditions' increased by 43%, from 14 incidents in 2022 to 20 in 2023, while crashes from 'Failed to yield right of way' decreased by 47% from 19 to 10.
Officer-Reported Primary Contributing Cause
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
Crash conditions were largely similar between 2022 and 2023. In both periods, the vast majority of collisions occurred in daylight (67.9% in 2023 vs. 65.2% in 2022) and on dry road surfaces (79.2% in 2023 vs. 77.3% in 2022). There was a slight increase in the proportion of crashes occurring in adverse weather, which accounted for 13.8% of crashes in 2023 compared to 11.2% in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—were the same in both 2023 and 2022, though the counts for Toyota (132 to 98) and Honda (82 to 65) declined. An analysis of persons involved shows a demographic shift, with the 35-44 age group's share increasing from 14.3% of all persons in 2022 to 18.0% in 2023. Conversely, the 16-20 age group's involvement decreased from representing 85 individuals in 2022 to 69 in 2023.
Top Vehicle Makes (604 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
32 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (604 persons with recorded sex)
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 distribution of crashes across different speed zones showed minor changes, with the 65 mph zone having the highest number of crashes in both years (90 in 2022 vs. 85 in 2023). A notable shift occurred in the location of fatal crashes. In 2022, the single fatal crash occurred in a 45 mph zone, whereas in 2023, the three fatal crashes were distributed across 45 mph, 55 mph, and 65 mph zones.
Fatal crashes by zone: 45 mph: 1 of 41 (2.439%) · 55 mph: 1 of 49 (2.041%) · 65 mph: 1 of 85 (1.176%)
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: LITTLETON, MA
- Total crash records analyzed: 318
- Total persons involved: 687
- Total vehicles involved: 604
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). "LITTLETON, 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/littleton/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved