Monthly Traffic Safety Analysis

944 CRASHES IN
MONTGOMERY, MD
JANUARY 2020

In January 2020, Montgomery County recorded 944 traffic crashes, resulting in 371 injuries and 3 fatalities. A notable finding from this period is that all 3 individuals killed in these crashes were pedestrians. The most common type of collision was a same-direction rear-end crash, accounting for 26.4% of all incidents.

944

Total Crash Events

3

Persons Killed

371

Persons Injured

14.5%

Hit-and-Run Rate

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Aggregate counts from crash, person, and vehicle records

137

Hit-and-Run Crashes — January 2020

During this period, 137 crashes were classified as hit-and-run incidents, representing 14.5% of all crashes. This determination is based on the responding officer's initial report at the scene. The data does not specify the outcome or resolution of these cases.

Vulnerable Road User Casualties

All 3 traffic fatalities recorded during this period were pedestrians. In addition to the fatalities, 49 pedestrians were injured. While no motorists were killed, 315 sustained injuries. There were no cyclist fatalities, but 6 cyclists were injured in collisions.

3

Pedestrians Killed

0

Cyclists Killed

0

Motorists Killed

0

Other Killed

49

Pedestrians Injured

6

Cyclists Injured

315

Motorists Injured

1

Other Injured

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crashes occurred most frequently on Fridays, with 190 incidents recorded. The single busiest hour for crashes was the 6 p.m. hour, with 79 incidents, aligning with the evening commute period which saw elevated crash counts from 3 p.m. onward. While 52.5% of crashes (496) happened in daylight, a substantial number, 330 crashes, occurred after dark on lighted roadways.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash date field aggregated by weekday

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The majority of crashes, 66.5% (628 incidents), resulted in no injuries and involved only property damage. The remaining 33.5% of crashes involved some level of injury, including 180 with possible injuries, 111 with minor injuries, and 21 with serious injuries. There were 3 fatal crashes recorded, resulting in 3 fatalities; in some incidents, the number of fatalities can exceed the number of fatal crashes.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.3%
Serious Injury21serious injury crashes2.2%
Minor Injury111minor injury crashes11.8%
Possible Injury180possible injury crashes19.1%
No Injury628no injury crashes66.5%

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Most severe injury per crash record

Top Contributing Factors

The most frequently cited contributing factors were related to environmental conditions. The top factor was a combination of 'RAIN, SNOW, WET,' listed in 63 crashes (6.7%). This was followed by 'N/A, WET,' which was a factor in 62 crashes (6.6%). Other prevalent factors also involved inclement weather, such as 'ICY OR SNOW-COVERED, RAIN, SNOW,' which was cited in 11 crashes.

Officer-Reported Primary Contributing Cause

RAIN, SNOW, WET63 (6.7%)
N/A, WET62 (6.6%)
ICY OR SNOW-COVERED, RAIN, SNOW11 (1.2%)
SLEET, HAIL, FREEZ. RAIN, WET9 (1%)
ICY OR SNOW-COVERED, N/A7 (0.7%)
N/A, VISION OBSTRUCTION (INCL. BLINDED BY SUN)6 (0.6%)
ANIMAL, N/A6 (0.6%)
N/A, RAIN, SNOW5 (0.5%)
V WIPERS|W OTHER ENVIRONMENTAL, WET3 (0.3%)
ICY OR SNOW-COVERED, V WIPERS|W OTHER ENVIRONMENTAL3 (0.3%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A majority of crashes occurred in favorable conditions, with 583 (61.8%) in clear weather, 609 (64.5%) on dry road surfaces, and 496 (52.5%) during daylight hours. However, adverse conditions were also present in a significant number of incidents. Crashes in the rain accounted for 115 incidents, while 183 crashes occurred on wet roads and 17 on roads with ice or frost.

Weather

Clear583 (68.2%)
Rain115 (13.5%)
Cloudy109 (12.7%)
Snow19 (2.2%)
Fog, Smog, Smoke9 (1.1%)
Sleet Or Hail7 (0.8%)
Wintry Mix6 (0.7%)
Other3 (0.4%)
Blowing Snow2 (0.2%)
Severe Crosswinds2 (0.2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Weather condition at time of crash

Lighting

Daylight496 (53.2%)
Dark - Lighted330 (35.4%)
Dark - Not Lighted42 (4.5%)
Dawn27 (2.9%)
Dusk23 (2.5%)
Dark - Unknown Lighting13 (1.4%)
Other2 (0.2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Lighting condition field

Road Surface

Dry609 (74.2%)
Wet183 (22.3%)
Ice/Frost17 (2.1%)
Snow10 (1.2%)
Other1 (0.1%)
Oil1 (0.1%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in collisions were Toyota (228 vehicles), Honda (186), and Ford (152). The data also includes numerous variations and abbreviations of manufacturer names, such as 'TOYT' (80 vehicles) and 'HOND' (57 vehicles), which also featured prominently in crash reports. The dataset did not contain sufficient information to analyze driver age demographics.

Top Vehicle Makes (1,686 vehicles)

1
TOYOTA228 (13.5%)
2
HONDA186 (11%)
3
FORD152 (9%)
4
NISSAN97 (5.8%)
5
TOYT80 (4.7%)
6
HOND57 (3.4%)
7
DODGE55 (3.3%)
8
JEEP47 (2.8%)
9
HYUNDAI43 (2.6%)
10
NISS34 (2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Vehicle unit records

At-Fault Party

In crashes where fault was assigned to a specific party, a driver was determined to be at fault in 880 cases. By contrast, a non-motorist was found to be at fault in 16 instances.

Intersection Type

Among crashes occurring at specified intersection types, four-way intersections were the most common location, accounting for 307 incidents. T-intersections were the second most frequent geometry, with 142 crashes reported.

Junction Type

Crashes were more likely to occur at or near a junction than on a non-junction roadway segment. The data shows 328 crashes occurred within an intersection and an additional 110 were classified as intersection-related. This compares to 198 crashes that happened at a non-intersection location.

Junction Type

"Other" combines 2 smaller categories (4 records): CROSSOVER RELATED (2), OTHER DRIVEWAY (2).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash-level records

Roadway Division

The most common roadway design where crashes occurred was a two-way, divided road with a positive median barrier, which was the site of 428 crashes. The second most frequent road type was a two-way, undivided road, where 282 crashes were recorded.

Roadway Division

1
TWO-WAY, DIVIDED, POSITIVE MEDIAN BARRIER428 (51%)
2
TWO-WAY, NOT DIVIDED282 (33.6%)
3
TWO-WAY, DIVIDED, UNPROTECTED PAINTED MIN 4 FEET95 (11.3%)
4
ONE-WAY TRAFFICWAY19 (2.3%)
5
OTHER14 (1.7%)
6
TWO-WAY, NOT DIVIDED WITH A CONTINUOUS LEFT TURN1 (0.1%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash-level records

Vehicle Damage Extent

The most commonly reported level of vehicle damage was 'Disabling,' which was noted for 613 of the 1,686 vehicles involved in crashes. 'Superficial' damage was reported for 461 vehicles, and 'Functional' damage was noted for 435 vehicles. A total of 80 vehicles were reported as 'Destroyed.'

Vehicle Damage Extent

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Vehicle unit records

Driver Action / Circumstance

The data on driver actions primarily reflects environmental conditions rather than specific behaviors. The most cited factor was 'N/A, WET,' attributed to 114 drivers. The second most common entry was 'RAIN, SNOW, WET,' noted for 109 drivers, indicating a strong correlation between reported actions and adverse weather.

Driver Action / Circumstance

1
N/A, WET114 (32.4%)
2
RAIN, SNOW, WET109 (31%)
3
ICY OR SNOW-COVERED, RAIN, SNOW19 (5.4%)
4
SLEET, HAIL, FREEZ. RAIN, WET14 (4%)
5
ICY OR SNOW-COVERED, N/A11 (3.1%)
6
N/A, VISION OBSTRUCTION (INCL. BLINDED BY SUN)11 (3.1%)
7
N/A, RAIN, SNOW10 (2.8%)
8
ANIMAL, N/A8 (2.3%)
9
ICY OR SNOW-COVERED, SLEET, HAIL, FREEZ. RAIN, WET7 (2%)

Showing top 9 of 30 reported. 21 additional (49 total) not shown: V WIPERS|W OTHER ENVIRONMENTAL, WET, BACKUP DUE TO REGULAR CONGESTION, N/A, ICY OR SNOW-COVERED, V WIPERS|W OTHER ENVIRONMENTAL, BACKUP DUE TO REGULAR CONGESTION, RAIN, SNOW, WET, BACKUP DUE TO NON-RECURRING INCIDENT, N/A, ICY OR SNOW-COVERED, SLEET, HAIL, FREEZ. RAIN, N/A, V EXHAUST SYSTEM|R OTHER ROAD, N/A, ROAD UNDER CONSTRUCTION/MAINTENANCE, N/A, TRAFFIC CONTROL DEVICE INOPERATIVE, N/A, SLEET, HAIL, FREEZ. RAIN, BACKUP DUE TO PRIOR CRASH, N/A, DEBRIS OR OBSTRUCTION, N/A, DEBRIS OR OBSTRUCTION, RAIN, SNOW, WET, WORN, TRAVEL-POLISHED SURFACE, ICY OR SNOW-COVERED, RAIN, SNOW, SLEET, HAIL, FREEZ. RAIN, WET, ANIMAL, ICY OR SNOW-COVERED, N/A, NON-HIGHWAY WORK, N/A, PHYSICAL OBSTRUCTION(S), ANIMAL, WET, ANIMAL, RAIN, SNOW, WET, VISION OBSTRUCTION (INCL. BLINDED BY SUN), WET, ICY OR SNOW-COVERED, RAIN, SNOW, WET.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Person-level records linked to crash events

Driver Distraction

Among the 349 drivers for whom a distraction was recorded, the most common was 'Looked but did not see,' reported in 246 cases. 'Inattentive or lost in thought' was the next most frequent distraction with 45 occurrences. Other specified distractions included 'Other distraction' (31) and various forms of cell phone use (9).

Driver Distraction

1
NOT DISTRACTED1,052 (74.8%)
2
LOOKED BUT DID NOT SEE246 (17.5%)
3
INATTENTIVE OR LOST IN THOUGHT45 (3.2%)
4
OTHER DISTRACTION31 (2.2%)
5
DISTRACTED BY OUTSIDE PERSON OBJECT OR EVENT8 (0.6%)
6
OTHER CELLULAR PHONE RELATED5 (0.4%)
7
NO DRIVER PRESENT5 (0.4%)
8
OTHER ELECTRONIC DEVICE (NAVIGATIONAL PALM PILOT)4 (0.3%)
9
TALKING OR LISTENING TO CELLULAR PHONE4 (0.3%)

Showing top 9 of 14 reported. 5 additional (6 total) not shown: EATING OR DRINKING, USING OTHER DEVICE CONTROLS INTEGRAL TO VEHICLE, BY OTHER OCCUPANTS, USING DEVICE OBJECT BROUGHT INTO VEHICLE, BY MOVING OBJECT IN VEHICLE.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Person-level records linked to crash events

First Harmful Event

The first harmful event for the vast majority of crashes was a collision with another motor vehicle, which occurred in 653 incidents (69.2% of all crashes). The second most common first event was striking a fixed object (117 crashes), followed by striking a parked vehicle (72 crashes).

First Harmful Event

1
OTHER VEHICLE653 (69.7%)
2
FIXED OBJECT117 (12.5%)
3
PARKED VEHICLE72 (7.7%)
4
PEDESTRIAN51 (5.4%)
5
OTHER OBJECT15 (1.6%)
6
OFF ROAD11 (1.2%)
7
ANIMAL8 (0.9%)
8
BICYCLE5 (0.5%)
9
OTHER2 (0.2%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: U-TURN, BACKING, OTHER CONVEYANCE.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash-level records

Point of Impact

The front of the vehicle ('Twelve O'clock') was the most frequent point of impact, accounting for 690 vehicles, or 40.9% of all impacts recorded. The rear of the vehicle ('Six O'clock') was the second most common impact point, involved in 345 instances (20.5%).

Point of Impact

"Other" combines 8 smaller categories (190 records): FIVE OCLOCK (39), NINE OCLOCK (37), THREE OCLOCK (35), SEVEN OCLOCK (34), EIGHT OCLOCK (32), UNDERSIDE (7), ROOF TOP (4), NON-COLLISION (2).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Vehicle unit records

Pre-Crash Driver Action

The most common action for vehicles immediately before a crash was 'Moving at a constant speed,' which was reported for 676 of the 1,686 vehicles involved (40.1%). The next most frequent actions were 'Slowing or stopping' (240 vehicles) and being 'Stopped in traffic lane' (182 vehicles).

Pre-Crash Driver Action

1
MOVING CONSTANT SPEED676 (40.6%)
2
SLOWING OR STOPPING240 (14.4%)
3
STOPPED IN TRAFFIC LANE182 (10.9%)
4
MAKING LEFT TURN177 (10.6%)
5
ACCELERATING90 (5.4%)
6
MAKING RIGHT TURN48 (2.9%)
7
BACKING47 (2.8%)
8
STARTING FROM LANE43 (2.6%)
9
CHANGING LANES41 (2.5%)

Showing top 9 of 20 reported. 11 additional (120 total) not shown: PARKED, STARTING FROM PARKED, MAKING U TURN, PARKING, NEGOTIATING A CURVE, SKIDDING, ENTERING TRAFFIC LANE, PASSING, LEAVING TRAFFIC LANE, OTHER, RIGHT TURN ON RED.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Vehicle unit records

Pedestrian/Cyclist Action

For the 55 pedestrians involved in crashes, 'No improper actions' was the most common finding, reported in 33 cases. Where improper actions were noted, 'Failure to yield right of way' and 'In roadway improperly' were each cited in 6 instances. 'Dart/dash' and 'Inattentive' were each recorded for 4 pedestrians.

Pedestrian/Cyclist Action

1
NO IMPROPER ACTIONS33 (60%)
2
FAILURE TO YIELD RIGHT OF WAY6 (10.9%)
3
IN ROADWAY IMPROPERLY6 (10.9%)
4
DART DASH4 (7.3%)
5
INATTENTIVE4 (7.3%)
6
OTHER2 (3.6%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Non-motorist records linked to crash events

Manner of Collision

Same-direction rear-end collisions were the most common type of crash, accounting for 249 incidents (26.4% of the total). Single-vehicle crashes were the second most frequent type with 165 incidents (17.5%), followed closely by straight movement angle collisions at 162 incidents (17.2%).

Manner of Collision

"Other" combines 10 smaller categories (77 records): SAME DIRECTION LEFT TURN (18), OPPOSITE DIRECTION SIDESWIPE (15), ANGLE MEETS LEFT TURN (14), ANGLE MEETS RIGHT TURN (9), SAME DIRECTION RIGHT TURN (8), ANGLE MEETS LEFT HEAD ON (4), SAME DIR REND RIGHT TURN (3), SAME DIR BOTH LEFT TURN (3), SAME DIR REND LEFT TURN (2), OPPOSITE DIR BOTH LEFT TURN (1).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash-level records

Traffic Control Device

A large portion of crashes, 406 out of 944 (43.0%), occurred at locations with no traffic controls. For crashes at controlled locations, 274 occurred where a traffic signal was present, and 70 occurred at a stop sign.

Traffic Control Device

"Other" combines 1 smaller categories (1 records): WARNING SIGN (1).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash-level records

Vehicle Type

Passenger cars were the most common vehicle type involved in crashes, representing 1,190 of the 1,686 vehicles (70.6%). Sport Utility Vehicles were the second most frequent type with 176 vehicles involved. Various commercial vehicles, including buses, medium/heavy trucks, and light trucks, accounted for at least 112 of the vehicles in collisions.

Vehicle Type

"Other" combines 15 smaller categories (87 records): OTHER LIGHT TRUCKS (10,000LBS (4,536KG) OR LESS) (15), POLICE VEHICLE/EMERGENCY (12), CARGO VAN/LIGHT TRUCK 2 AXLES (OVER 10,000LBS (4,5 (11), OTHER (9), MOTORCYCLE (8), OTHER BUS (7), MEDIUM/HEAVY TRUCKS 3 AXLES (OVER 10,000LBS (4,536 (7), FIRE VEHICLE/NON EMERGENCY (3), AMBULANCE/NON EMERGENCY (3), TRUCK TRACTOR (3), STATION WAGON (3), FIRE VEHICLE/EMERGENCY (2), AMBULANCE/EMERGENCY (2), RECREATIONAL VEHICLE (1), ALL TERRAIN VEHICLE (ATV) (1).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Vehicle unit records

Person Injury Severity

Of the 1,751 people involved in crashes, 1,377 (78.6%) were not injured. Among the 374 people who were injured, 22 sustained serious injuries and 3 sustained fatal injuries. Combined, fatal and serious injuries accounted for 1.4% of all individuals involved in crashes.

Person Injury Severity

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash-level records

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 573 of the 944 total crashes (60.7%). Single-vehicle crashes represented 30.9% of incidents (292 crashes). The remaining crashes involved three or more vehicles, with one incident involving as many as 6 vehicles.

Vehicles Per Crash

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-01-01 to 2020-01-31 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Montgomery County Crash Reporting (ACRS) (https://data.montgomerycountymd.gov/d/bhju-22kf), accessed programmatically via the Socrata 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: Socrata Open Data API (SoQL queries)
  • Dataset URL: https://data.montgomerycountymd.gov/d/bhju-22kf
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2020-01-01 through 2020-01-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-01-01 through 2020-01-31 (31 days)
  • Geographic scope: montgomery, MD
  • Total crash records analyzed: 944
  • Total persons involved: 1,751
  • Total vehicles involved: 1,686

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). "montgomery, MD Crash Intelligence Report: January 2020." Published September 9, 2026. Reporting period: 2020-01-01 to 2020-01-31. Data source: Montgomery County Crash Reporting (ACRS), Socrata Open Data. Dataset: https://data.montgomerycountymd.gov/d/bhju-22kf. Available at: https://thatcarhitme.com/crash-data/maryland/statewide/january-2020-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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