{"author":{"@type":"Person","name":"Alexander Bock","url":"https://abxk.ai/en/autor/alexander-bock/"},"categories":["Physical AI"],"content":{"markdown":"Every crash of a car that drives itself on US roads has to be reported to the National Highway Traffic Safety Administration (NHTSA), the federal road safety authority, and the reports are public. We analyzed all {{\u003c num \"av\" \"reports\" \u003e}} reports on vehicles with an automated driving system that NHTSA has published for crashes since June 2025, when the current version of the reporting rule took effect. The picture is more specific than most headlines: the typical crash is slow, the robot car is often standing still, and most crashes end without injuries.\n\n![Bar chart of crash reports per month for vehicles with an automated driving system, from June 2025 to the last full month](/images/blog/en/self-driving-car-crash-data-months.webp \"Crash reports per month. More reports mostly mean more driverless miles, not necessarily less safety.\")\n\n## What has to be reported\n\nThe rule is NHTSA's Standing General Order 2021-01, in its third version since June 16, 2025. It covers vehicles with an automated driving system (ADS), SAE Levels 3 to 5: in practice robotaxis, driverless shuttles and delivery vehicles, and test vehicles with a safety driver. A crash has to be reported if the system was active at any time within 30 seconds before the crash and the crash caused a death, a hospital visit, an air bag deployment, a tow, a collision with a pedestrian or cyclist, or property damage above a set limit. Serious crashes have to be reported within five days, all others by the 15th of the following month.\n\nDriver assistance (SAE Level 2), where a human drives and stays responsible, has its own reports. Those are not part of this analysis.\n\n| The reports contain | The reports do not contain |\n|---|---|\n| Date, state, road type and weather | Miles driven, so there are no crash rates |\n| What the vehicle hit, and how fast it was going | A finding on who caused the crash |\n| Injuries, as alleged in the report | Crashes before June 2025, under older rules |\n| Whether a safety driver was on board | Driver assistance crashes (SAE Level 2) |\n\n## Most crashes happen at low speed or standing still\n\nIn {{\u003c num \"av\" \"speed_zero_pct\" \u003e}}% of the reports with a speed, the automated vehicle was not moving at all, and in {{\u003c num \"av\" \"speed_max10_pct\" \u003e}}% it was going 10 mph or slower. Measured by the movement just before the crash, the vehicle was stopped or parked in {{\u003c num \"av\" \"stationary_pct\" \u003e}}% of all reports, and {{\u003c num \"av\" \"rear_pct\" \u003e}}% of the reports list damage at the rear of the vehicle.\n\n![Horizontal bars: share of crash reports by speed of the automated vehicle, from 0 mph to 46 mph or more](/images/blog/en/self-driving-car-crash-data-speed.webp \"The speed of the automated vehicle just before the crash.\")\n\nThe reports do not say who caused a crash. But the pattern explains why so many crashes look alike: a robot car that stops in traffic, at a light or for a pedestrian is easy to hit from behind or from the side. In {{\u003c num \"av\" \"driverless_pct\" \u003e}}% of the reports, nobody was in the driver's seat, which means the crashes come mostly from commercial driverless fleets, not from test drives.\n\n{{\u003c data \"av-movement\" \u003e}}\n\n## What the cars hit\n\nMost crash partners are other cars. Collisions with trucks and buses follow, then fixed objects such as poles, barriers or parked equipment. {{\u003c num \"av\" \"vulnerable\" \u003e}} reports involve a cyclist, a pedestrian or a motorcycle, the road users who are most at risk in any crash.\n\n{{\u003c data \"av-partner\" \u003e}}\n\n## How severe the crashes were\n\n{{\u003c num \"av\" \"no_injury_pct\" \u003e}}% of the reports list no injuries, only property damage. {{\u003c num \"av\" \"serious_or_fatal\" \u003e}} reports list a serious injury or a death, {{\u003c num \"av\" \"fatal\" \u003e}} of them a death. The severity is what the reporting company was told or alleges; NHTSA does not verify each report before it publishes the data.\n\n{{\u003c data \"av-injury\" \u003e}}\n\n## Where the crashes happen\n\nThe reports come from {{\u003c num \"av\" \"states\" \u003e}} states, and California alone accounts for {{\u003c num \"av\" \"top_state_pct\" \u003e}}% of them. That reflects where driverless fleets operate, mainly in San Francisco and Los Angeles, Phoenix and Austin, not where driving is most dangerous.\n\n{{\u003c data \"av-states\" \u003e}}\n\n## Why more reports do not mean less safety\n\nThe number of reports grew from an average of {{\u003c num \"av\" \"avg_first3\" \u003e}} a month in the first three months to {{\u003c num \"av\" \"avg_last6\" \u003e}} a month in the last six. That sounds alarming, but the fleets grew at the same time, and every mile driven creates a chance to be hit. The public files contain no miles driven, so a report count cannot be turned into a crash rate. A fair comparison needs crashes per million miles, compared with human drivers on the same roads at the same times of day, and many minor crashes of human drivers never reach any statistic because no police report is filed. Some companies publish such figures for their own fleets; the NHTSA data cannot provide them.\n\nThis is also why this page shows no ranking of companies: one company with a large fleet and many miles will always file more reports than a small test program.\n\n## How we counted\n\nWe used the public file of NHTSA reports for ADS vehicles (Standing General Order 2021-01) and kept the latest version of each report, because follow-up reports replace the first one. The series per month starts in June 2025, the first full month under the current rule, and ends with the last full month; the newest month is still incomplete because monthly reports arrive by the 15th of the following month. Speeds come from the report's field for the vehicle's speed before the crash; reports without a speed are left out of the speed table. The source and date are below each table.\n\nHow these vehicles see the road, plan and brake is the subject of our learning path in [Physical AI](/en/physical-ai/).","text":"Every crash of a car that drives itself on US roads has to be reported to the National Highway Traffic Safety Administration (NHTSA), the federal road safety authority, and the reports are public. We analyzed all 1,551 reports on vehicles with an automated driving system that NHTSA has published for crashes since June 2025, when the current version of the reporting rule took effect. The picture is more specific than most headlines: the typical crash is slow, the robot car is often standing still, and most crashes end without injuries.\nCrash reports per month. More reports mostly mean more driverless miles, not necessarily less safety. What has to be reported The rule is NHTSA\u0026rsquo;s Standing General Order 2021-01, in its third version since June 16, 2025. It covers vehicles with an automated driving system (ADS), SAE Levels 3 to 5: in practice robotaxis, driverless shuttles and delivery vehicles, and test vehicles with a safety driver. A crash has to be reported if the system was active at any time within 30 seconds before the crash and the crash caused a death, a hospital visit, an air bag deployment, a tow, a collision with a pedestrian or cyclist, or property damage above a set limit. Serious crashes have to be reported within five days, all others by the 15th of the following month.\nDriver assistance (SAE Level 2), where a human drives and stays responsible, has its own reports. Those are not part of this analysis.\nSelf-Driving Car Crashes in Numbers: What the NHTSA Reports Show The reports contain The reports do not contain Date, state, road type and weather Miles driven, so there are no crash rates What the vehicle hit, and how fast it was going A finding on who caused the crash Injuries, as alleged in the report Crashes before June 2025, under older rules Whether a safety driver was on board Driver assistance crashes (SAE Level 2) Most crashes happen at low speed or standing still In 50.9% of the reports with a speed, the automated vehicle was not moving at all, and in 77.4% it was going 10 mph or slower. Measured by the movement just before the crash, the vehicle was stopped or parked in 50.2% of all reports, and 22.1% of the reports list damage at the rear of the vehicle.\nThe speed of the automated vehicle just before the crash. The reports do not say who caused a crash. But the pattern explains why so many crashes look alike: a robot car that stops in traffic, at a light or for a pedestrian is easy to hit from behind or from the side. In 83.3% of the reports, nobody was in the driver\u0026rsquo;s seat, which means the crashes come mostly from commercial driverless fleets, not from test drives.\nWhat the automated vehicle was doing just before the crash MovementReportsShare Stopped (traffic, light)66042.6% Driving straight54335.0% Parked1187.6% Turning left684.4% Turning right422.7% Changing lanes372.4% Backing up261.7% Passing211.4% Source as for the first table on this page.\nWhat the cars hit Most crash partners are other cars. Collisions with trucks and buses follow, then fixed objects such as poles, barriers or parked equipment. 37 reports involve a cyclist, a pedestrian or a motorcycle, the road users who are most at risk in any crash.\nWhat the automated vehicle collided with Crash partnerReportsShare Car, SUV, pickup or van1,07669.4% Truck or bus20213.0% Cyclist, pedestrian or motorcycle372.4% Object, pole, tree or animal1076.9% Other or unclear1298.3% Source as for the first table on this page.\nHow severe the crashes were 88.3% of the reports list no injuries, only property damage. 6 reports list a serious injury or a death, 2 of them a death. The severity is what the reporting company was told or alleges; NHTSA does not verify each report before it publishes the data.\nHighest injury severity alleged in the report InjuryReportsShare No injury reported1,36988.3% Minor1388.9% Moderate130.8% Serious40.3% Fatal20.1% Unknown251.6% Source as for the first table on this page.\nWhere the crashes happen The reports come from 14 states, and California alone accounts for 52.1% of them. That reflects where driverless fleets operate, mainly in San Francisco and Los Angeles, Phoenix and Austin, not where driving is most dangerous.\nStates with the most reports StateReportsShare California80852.1% Texas32220.8% Arizona20813.4% Georgia815.2% Nevada493.2% Florida473.0% Tennessee100.6% Pennsylvania70.5% Source as for the first table on this page.\nWhy more reports do not mean less safety The number of reports grew from an average of 62 a month in the first three months to 126 a month in the last six. That sounds alarming, but the fleets grew at the same time, and every mile driven creates a chance to be hit. The public files contain no miles driven, so a report count cannot be turned into a crash rate. A fair comparison needs crashes per million miles, compared with human drivers on the same roads at the same times of day, and many minor crashes of human drivers never reach any statistic because no police report is filed. Some companies publish such figures for their own fleets; the NHTSA data cannot provide them.\nThis is also why this page shows no ranking of companies: one company with a large fleet and many miles will always file more reports than a small test program.\nHow we counted We used the public file of NHTSA reports for ADS vehicles (Standing General Order 2021-01) and kept the latest version of each report, because follow-up reports replace the first one. The series per month starts in June 2025, the first full month under the current rule, and ends with the last full month; the newest month is still incomplete because monthly reports arrive by the 15th of the following month. Speeds come from the report\u0026rsquo;s field for the vehicle\u0026rsquo;s speed before the crash; reports without a speed are left out of the speed table. The source and date are below each table.\nHow these vehicles see the road, plan and brake is the subject of our learning path in Physical AI.\n","words":1003},"date":"2026-10-18","description":"Every crash of a self-driving car on US roads must be reported to NHTSA. We analyzed the reports: what the cars hit, how fast they were going and how severe it was.","image":"https://abxk.ai/images/cover/self-driving-car-crash-data.webp","json":"https://abxk.ai/en/physical-ai/self-driving-car-crash-data/index.json","kind":"page","language":"en","modified":"2026-10-18","section":"physical-ai","seo_title":"Self-Driving Car Crash Statistics: NHTSA Data Analyzed","tags":["autonomous-driving","robotaxi","crash-data","nhtsa","physical-ai"],"title":"Self-Driving Car Crashes in Numbers: What the NHTSA Reports Show","translations":[{"json":"https://abxk.ai/de/physical-ai/self-driving-car-crash-data/index.json","language":"de","url":"https://abxk.ai/de/physical-ai/self-driving-car-crash-data/"}],"url":"https://abxk.ai/en/physical-ai/self-driving-car-crash-data/"}