Monthly Traffic Safety Analysis

682 CRASHES IN
MONTGOMERY, MD
SEPTEMBER 2020

In September 2020, Montgomery County recorded 682 traffic crashes, resulting in 3 fatalities and 253 injuries. The data indicates that the most common type of collision was a same-direction rear-end crash, accounting for 145 incidents or 21.3% of the total. The majority of crashes, 67.4%, did not result in any reported injuries.

682

Total Crash Events

3

Persons Killed

253

Persons Injured

21.3%

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

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Aggregate counts from crash, person, and vehicle records

145

Hit-and-Run Crashes — September 2020

During this period, 145 crashes were classified as hit-and-run incidents, representing 21.3% of all reported collisions. This classification is based on the initial determination made by the responding law enforcement officer at the scene of the crash.

Vulnerable Road User Casualties

A total of three individuals were killed and 253 were injured in crashes during this period. Two of the fatalities were pedestrians, who also sustained 20 injuries. The third fatality was a motorist, and motorists accounted for the largest group of injured persons with 205 injuries. No cyclists were killed, but 23 sustained injuries.

2

Pedestrians Killed

0

Cyclists Killed

1

Motorists Killed

0

Other Killed

20

Pedestrians Injured

23

Cyclists Injured

205

Motorists Injured

5

Other Injured

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash frequency peaked on Wednesdays, which saw 133 incidents. The most common time for crashes was during the afternoon commute, with a peak of 53 crashes occurring in both the 3 PM and 4 PM hours. Overall, 454 crashes, or 66.6% of the total, occurred during daylight hours.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Crash date field aggregated by weekday

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Of the 682 total crashes, 460 (67.4%) resulted in no injuries, being classified as property damage only. The remaining incidents involved possible (107), minor (97), or serious (11) injuries. Three crashes were classified as fatal, resulting in 3 total fatalities; in this period, each fatal crash involved one death.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.4%
Serious Injury11serious injury crashes1.6%
Minor Injury97minor injury crashes14.2%
Possible Injury107possible injury crashes15.7%
No Injury460no injury crashes67.4%

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Most severe injury per crash record

Top Contributing Factors

Analysis of contributing factors indicates that environmental conditions played a significant role. The most frequently cited factor was 'RAIN, SNOW, WET,' attributed to 59 crashes (8.7%). The second most common factor was 'N/A, WET,' noted in 33 crashes (4.8%), highlighting the prevalence of wet road conditions in reported incidents.

Officer-Reported Primary Contributing Cause

RAIN, SNOW, WET59 (8.7%)
N/A, WET33 (4.8%)
N/A, VISION OBSTRUCTION (INCL. BLINDED BY SUN)6 (0.9%)
ANIMAL, N/A5 (0.7%)
N/A, RUTS, HOLES, BUMPS3 (0.4%)
N/A, RAIN, SNOW3 (0.4%)
DEBRIS OR OBSTRUCTION, N/A3 (0.4%)
ANIMAL, WET2 (0.3%)
N/A, PHYSICAL OBSTRUCTION(S)2 (0.3%)
SLEET, HAIL, FREEZ. RAIN, WET2 (0.3%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes occurred in favorable conditions, with 431 (63.2%) happening in clear weather and 461 (67.6%) on dry road surfaces. Correspondingly, 454 crashes (66.6%) took place in daylight. Adverse conditions were also a factor, with 87 crashes occurring during rain and 124 on wet roads.

Weather

Clear431 (69.6%)
Cloudy95 (15.3%)
Rain87 (14.1%)
Fog, Smog, Smoke5 (0.8%)
Sleet Or Hail1 (0.2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Weather condition at time of crash

Lighting

Daylight454 (67.4%)
Dark - Lighted155 (23.0%)
Dark - Not Lighted30 (4.5%)
Dusk17 (2.5%)
Dark - Unknown Lighting8 (1.2%)
Dawn8 (1.2%)
Other2 (0.3%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Lighting condition field

Road Surface

Dry461 (78.8%)
Wet124 (21.2%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Road surface condition field

Vehicles & Demographics

Passenger cars were the most frequently involved vehicle type, accounting for 810 of the 1,152 vehicles in crashes, followed by sport utility vehicles with 99. Among vehicle makes, Toyota was most common with 188 vehicles, followed by Honda with 154 and Ford with 110. Some records contain abbreviations, such as 'TOYT' (57) and 'HOND' (31), which may represent additional vehicles of those makes.

Top Vehicle Makes (1,152 vehicles)

1
TOYOTA188 (16.3%)
2
HONDA154 (13.4%)
3
FORD110 (9.5%)
4
TOYT57 (4.9%)
5
NISSAN48 (4.2%)
6
DODGE34 (3%)
7
HOND31 (2.7%)
8
CHEVROLET29 (2.5%)
9
JEEP28 (2.4%)
10
CHEVY28 (2.4%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Vehicle unit records

At-Fault Party

In crashes where fault was assigned, drivers were determined to be at fault in 623 instances, representing 97.8% of such cases. Non-motorists were found at fault in 10 cases, and both parties were determined to be at fault in 4 cases.

Intersection Type

Among crashes occurring at specified intersection types, four-way intersections were the most common location, accounting for 217 incidents. T-intersections were the second most frequent site, with 100 crashes reported. Together, these two geometries represent the location for the majority of intersection-related crashes.

Junction Type

Analysis of crash locations shows that 234 incidents (45.7% of those specified) occurred at an intersection. A significant number of crashes, 163, occurred on non-intersection roadway segments. An additional 86 crashes were classified as intersection-related.

Junction Type

"Other" combines 3 smaller categories (3 records): CROSSOVER RELATED (1), OTHER DRIVEWAY (1), ALLEY (1).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Crash-level records

Roadway Division

The most common road design at crash locations was a 'Two-way, divided, positive median barrier,' accounting for 277 incidents. The second most frequent was a 'Two-way, not divided' roadway, which was the site of 212 crashes. These two road types were the location for the majority of reported collisions.

Roadway Division

1
TWO-WAY, DIVIDED, POSITIVE MEDIAN BARRIER277 (46.9%)
2
TWO-WAY, NOT DIVIDED212 (35.9%)
3
TWO-WAY, DIVIDED, UNPROTECTED PAINTED MIN 4 FEET75 (12.7%)
4
ONE-WAY TRAFFICWAY19 (3.2%)
5
OTHER5 (0.8%)
6
TWO-WAY, NOT DIVIDED WITH A CONTINUOUS LEFT TURN2 (0.3%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Crash-level records

Vehicle Damage Extent

Disabling damage was the most frequently reported vehicle damage extent, noted in 462 instances, or 42.5% of vehicles with a damage assessment. An additional 59 vehicles were reported as destroyed. In contrast, 280 vehicles sustained superficial damage and 36 had no damage.

Vehicle Damage Extent

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Vehicle unit records

Driver Action / Circumstance

The data field for driver action primarily captured environmental factors. The most frequently cited factor was 'RAIN, SNOW, WET,' which was associated with 94 drivers. The second most common entry was 'N/A, WET,' listed for 61 drivers, suggesting wet conditions were a prevalent circumstance.

Driver Action / Circumstance

1
RAIN, SNOW, WET94 (45.9%)
2
N/A, WET61 (29.8%)
3
N/A, VISION OBSTRUCTION (INCL. BLINDED BY SUN)10 (4.9%)
4
DEBRIS OR OBSTRUCTION, N/A6 (2.9%)
5
ANIMAL, N/A5 (2.4%)
6
N/A, PHYSICAL OBSTRUCTION(S)5 (2.4%)
7
N/A, RUTS, HOLES, BUMPS4 (2%)
8
N/A, RAIN, SNOW3 (1.5%)
9
SLEET, HAIL, FREEZ. RAIN, WET3 (1.5%)

Showing top 9 of 17 reported. 8 additional (14 total) not shown: BACKUP DUE TO PRIOR CRASH, N/A, BACKUP DUE TO NON-RECURRING INCIDENT, N/A, ANIMAL, WET, BLOWING SAND, SOIL, DIRT, RAIN, SNOW, SEVERE CROSSWINDS, SLEET, HAIL, FREEZ. RAIN, WET, V WIPERS|W OTHER ENVIRONMENTAL, WET, N/A, ROAD UNDER CONSTRUCTION/MAINTENANCE, BACKUP DUE TO REGULAR CONGESTION, N/A, DEBRIS OR OBSTRUCTION, N/A, PHYSICAL OBSTRUCTION(S).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Person-level records linked to crash events

Driver Distraction

Among drivers for whom a distraction was recorded, 'Looked but did not see' was the most common, cited for 176 drivers. Other specified distractions included 'Other distraction' (30 drivers), 'Inattentive or lost in thought' (29 drivers), and 'Talking or listening to cellular phone' (4 drivers).

Driver Distraction

1
NOT DISTRACTED676 (72.5%)
2
LOOKED BUT DID NOT SEE176 (18.9%)
3
OTHER DISTRACTION30 (3.2%)
4
INATTENTIVE OR LOST IN THOUGHT29 (3.1%)
5
DISTRACTED BY OUTSIDE PERSON OBJECT OR EVENT5 (0.5%)
6
OTHER ELECTRONIC DEVICE (NAVIGATIONAL PALM PILOT)5 (0.5%)
7
TALKING OR LISTENING TO CELLULAR PHONE4 (0.4%)
8
BY OTHER OCCUPANTS3 (0.3%)
9
OTHER CELLULAR PHONE RELATED2 (0.2%)

Showing top 9 of 12 reported. 3 additional (3 total) not shown: NO DRIVER PRESENT, BY MOVING OBJECT IN VEHICLE, ADJUSTING AUDIO AND OR CLIMATE CONTROLS.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Person-level records linked to crash events

First Harmful Event

The initial event in the majority of crashes was a collision with another vehicle, which occurred in 451 incidents (66.1% of all crashes). The second most common first harmful event was striking a fixed object, such as a guardrail or tree, which happened in 91 crashes. Collisions with parked vehicles were the third most frequent event, with 57 instances.

First Harmful Event

1
OTHER VEHICLE451 (66.5%)
2
FIXED OBJECT91 (13.4%)
3
PARKED VEHICLE57 (8.4%)
4
PEDESTRIAN30 (4.4%)
5
BICYCLE19 (2.8%)
6
OFF ROAD8 (1.2%)
7
ANIMAL6 (0.9%)
8
OTHER OBJECT5 (0.7%)
9
OTHER4 (0.6%)

Showing top 9 of 13 reported. 4 additional (7 total) not shown: BACKING, OVERTURN, OTHER NON COLLISION, OTHER PEDALCYCLE.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Crash-level records

Non-Motorist Safety Equipment

Of the 50 pedestrians and bicyclists involved in crashes, a small number were reported to be using safety equipment. Twelve individuals, primarily cyclists, were noted as wearing a helmet. Only one person was reported to be using reflective clothing.

Non-Motorist Safety Equipment

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Non-motorist records linked to crash events

Point of Impact

The front of the vehicle, or 'twelve o'clock' position, was the most common point of impact, reported for 469 vehicles (40.7% of the total). The rear of the vehicle, or 'six o'clock' position, was the second most frequent impact point, involved in 184 instances (16.0%).

Point of Impact

"Other" combines 8 smaller categories (145 records): FOUR OCLOCK (32), THREE OCLOCK (28), EIGHT OCLOCK (25), NINE OCLOCK (24), SEVEN OCLOCK (23), UNDERSIDE (6), ROOF TOP (5), NON-COLLISION (2).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Vehicle unit records

Pre-Crash Driver Action

The most common action immediately preceding a crash was 'Moving constant speed,' reported for 506 drivers (43.9% of all drivers). The next most frequent pre-crash actions were 'Slowing or stopping' (121 drivers) and 'Making left turn' (119 drivers).

Pre-Crash Driver Action

1
MOVING CONSTANT SPEED506 (44.5%)
2
SLOWING OR STOPPING121 (10.6%)
3
MAKING LEFT TURN119 (10.5%)
4
STOPPED IN TRAFFIC LANE90 (7.9%)
5
ACCELERATING82 (7.2%)
6
MAKING RIGHT TURN45 (4%)
7
BACKING34 (3%)
8
CHANGING LANES30 (2.6%)
9
STARTING FROM LANE23 (2%)

Showing top 9 of 19 reported. 10 additional (88 total) not shown: STARTING FROM PARKED, PARKED, PARKING, OTHER, MAKING U TURN, PASSING, ENTERING TRAFFIC LANE, NEGOTIATING A CURVE, SKIDDING, RIGHT TURN ON RED.

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Vehicle unit records

Pedestrian/Cyclist Action

For the 50 non-motorists involved, 'No improper actions' was the most frequently reported circumstance, with 32 instances. Among improper actions cited, 'Failure to yield right of way,' 'Dart dash,' 'Inattentive,' and 'Failure to obey traffic signs' were each noted 3 times.

Pedestrian/Cyclist Action

1
NO IMPROPER ACTIONS32 (68.1%)
2
FAILURE TO YIELD RIGHT OF WAY3 (6.4%)
3
DART DASH3 (6.4%)
4
INATTENTIVE3 (6.4%)
5
FAILURE TO OBEY TRAFFIC SIGNS SIGNALS OR OFFICER3 (6.4%)
6
IN ROADWAY IMPROPERLY2 (4.3%)
7
WRONG WAY RIDING OR WALKING1 (2.1%)

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Non-motorist records linked to crash events

Manner of Collision

The most frequent crash type was a same-direction rear-end collision, accounting for 145 crashes or 21.3% of the total. This was followed by straight movement angle crashes (134 incidents, 19.6%) and single-vehicle crashes (124 incidents, 18.2%).

Manner of Collision

"Other" combines 10 smaller categories (62 records): SAME DIRECTION LEFT TURN (16), SAME DIRECTION RIGHT TURN (14), OPPOSITE DIRECTION SIDESWIPE (12), ANGLE MEETS LEFT TURN (7), ANGLE MEETS LEFT HEAD ON (4), OPPOSITE DIR BOTH LEFT TURN (3), SAME DIR BOTH LEFT TURN (2), ANGLE MEETS RIGHT TURN (2), SAME DIR REND RIGHT TURN (1), SAME DIR REND LEFT TURN (1).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Crash-level records

Traffic Control Device

A plurality of crashes, 287 out of 682 (42.1%), occurred at locations with no traffic controls. Intersections controlled by a traffic signal were the site of 210 crashes, while 53 crashes occurred at locations with 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 · 2020-09-01 to 2020-09-30 · Crash-level records

Vehicle Type

Passenger cars were the predominant vehicle type involved in crashes, accounting for 810 of the 1,152 vehicles (70.3%). Sport utility vehicles were the second most common type with 99 vehicles involved. Commercial vehicles like transit buses, cargo vans, and heavy trucks were involved in a smaller number of incidents.

Vehicle Type

"Other" combines 14 smaller categories (74 records): MOTORCYCLE (13), OTHER LIGHT TRUCKS (10,000LBS (4,536KG) OR LESS) (12), POLICE VEHICLE/EMERGENCY (9), OTHER (9), MEDIUM/HEAVY TRUCKS 3 AXLES (OVER 10,000LBS (4,536 (9), AMBULANCE/EMERGENCY (4), TRUCK TRACTOR (4), OTHER BUS (3), STATION WAGON (3), FIRE VEHICLE/NON EMERGENCY (3), FIRE VEHICLE/EMERGENCY (2), AUTOCYCLE (1), MOPED (1), LOW SPEED VEHICLE (1).

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Vehicle unit records

Person Injury Severity

Among the 1,207 people involved in crashes, 951 (78.8%) were not injured. Three individuals sustained fatal injuries, and 12 sustained serious injuries. An additional 108 people had minor injuries and 133 had possible injuries.

Person Injury Severity

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · Crash-level records

Vehicles Per Crash

Two-vehicle collisions were the most common scenario, accounting for 412 of the 682 crashes (60.4%). Single-vehicle crashes were the second most frequent type, with 236 incidents (34.6%). Crashes involving three or more vehicles were less common, with 24 three-vehicle and 5 four-vehicle crashes reported.

Vehicles Per Crash

Source: Montgomery County Crash Reporting (ACRS) · Socrata Open Data · 2020-09-01 to 2020-09-30 · 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: 2020-09-01 through 2020-09-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2020-09-01 through 2020-09-30 (30 days)
  • Geographic scope: montgomery, MD
  • Total crash records analyzed: 682
  • Total persons involved: 1,207
  • Total vehicles involved: 1,152

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: September 2020." Published September 9, 2026. Reporting period: 2020-09-01 to 2020-09-30. 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/september-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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