ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AUSTIN, TX · 2019
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/texas/austin/2019-annual-report
Yearly Traffic Safety Analysis
16,924 CRASHES IN
AUSTIN, TX
2019
In 2019, Austin recorded 16,924 total traffic crashes, a 2.3% increase from the 16,551 crashes reported in 2018. While total crashes and injuries saw modest year-over-year increases, the most significant change was in traffic fatalities. The number of persons killed rose from 71 in 2018 to 88 in 2019, representing a 23.9% increase.
16,924
▲ 2.3%was 16,551
Total Crash Events
88
▲ 23.9%was 71
Persons Killed
10,530
▲ 4.3%was 10,096
Persons Injured
90
▲ 23.3%was 73
Fatal Crash Events
Note: "Persons Killed" (88) counts individual fatalities across all crash events. "Fatal" in the severity table below (90) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Austin Crash Reports · Socrata Open Data · 2019-01-01 to 2019-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety metrics worsened in 2019 compared to the previous year. Total crashes increased by 2.3% (from 16,551 to 16,924), and total injuries rose by 4.3% (from 10,096 to 10,530). Most notably, total fatalities increased by 23.9%, from 71 in 2018 to 88 in 2019.
Vulnerable Road User Casualties
34
Pedestrians Killed
4
Cyclists Killed
37
Motorists Killed
0
Pedestrians Injured
0
Cyclists Injured
0
Motorists Injured
Source: Austin Crash Reports · Socrata Open Data · 2019-01-01 to 2019-12-31 · 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 largely consistent year-over-year. Friday was the peak day for crashes in both 2019 (2,722 crashes) and 2018 (2,670 crashes), and the 5 PM hour was the peak hour in both periods, though the count for that hour decreased slightly from 1,308 to 1,293. While the overall daily and hourly distributions did not shift significantly, crashes on Sunday saw a decrease from 1,958 in 2018 to 1,830 in 2019.
Source: Austin Crash Reports · Socrata Open Data · 2019-01-01 to 2019-12-31 · Crash date field aggregated by weekday
Source: Austin Crash Reports · Socrata Open Data · 2019-01-01 to 2019-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened in 2019 compared to 2018. The number of fatal crashes rose from 73 to 90, increasing their share of all crashes from 0.4% to 0.5%. Similarly, serious injury crashes increased from 453 to 485, with their proportion rising from 2.7% to 2.9%. The proportion of crashes resulting in no injury decreased from 50.1% in 2018 to 49.1% in 2019, indicating a shift toward more severe outcomes.
Severity is per crash event (most severe injury). 90 fatal crash events resulted in 88 persons killed.
Outcome by Severity (Crash Events)
Source: Austin Crash Reports · Socrata Open Data · 2019-01-01 to 2019-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Austin Crash Reports · Socrata Open Data · 2019-01-01 to 2019-12-31 · Most severe injury per crash record
Speed Limit Zones
The distribution of crashes across different speed zones showed a mixed pattern between 2018 and 2019. Crashes increased in lower speed zones (25 mph or less) and mid-range zones (40-45 mph), while decreasing in 30-35 mph, 50-60 mph, and high-speed zones (65 mph or more). A notable trend emerged in fatal crashes within the 35-45 mph speed zones, where fatalities increased from 22 in 2018 to 39 in 2019. Conversely, fatalities in the 50-60 mph zones decreased from 22 to 19 over the same period.
Fatal crashes by zone: 15 mph: 1 of 63 (1.587%) · 35 mph: 10 of 2,268 (0.441%) · 40 mph: 7 of 998 (0.701%) · 45 mph: 22 of 2,124 (1.036%) · 50 mph: 2 of 794 (0.252%) · 55 mph: 5 of 1,331 (0.376%) · 60 mph: 12 of 645 (1.86%) · 65 mph: 3 of 1,092 (0.275%) · 70 mph: 9 of 534 (1.685%) · 75 mph: 2 of 91 (2.198%)
Source: Austin Crash Reports · Socrata Open Data · 2019-01-01 to 2019-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Austin Crash Reports (https://data.austintexas.gov/d/y2wy-tgr5), 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.austintexas.gov/d/y2wy-tgr5
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2019-01-01 through 2019-12-31
- Report generated: July 5, 2026
Data Coverage
- Reporting period: 2019-01-01 through 2019-12-31 (365 days)
- Geographic scope: Austin, TX
- Total crash records analyzed: 16,924
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). "Austin, TX Crash Intelligence Report: 2019." Published July 5, 2026. Reporting period: 2019-01-01 to 2019-12-31. Data source: Austin Crash Reports, Socrata Open Data. Dataset: https://data.austintexas.gov/d/y2wy-tgr5. Available at: https://thatcarhitme.com/crash-data/texas/austin/2019-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: Austin Crash Reports · Socrata
Period: 2019-01-01 – 2019-12-31
Generated: July 5, 2026 · All rights reserved