Self-driving cars are often discussed as if the safety question is a single switch, but the numbers are anything but simple. In the most recent dataset, AV systems are reported around 0.29 crashes per million miles compared with 4.85 for human driving, and some fleets push far beyond that gap while still seeing very specific failure modes. The rest of the post breaks down where those differences come from, including crashes, injuries, and the interventions behind the headlines.
Key Takeaways
- AV crash rates 0.29 per million miles vs human 4.85 USDOT 2022
- Waymo 5.6x safer than human drivers per mile Phoenix 2023
- Cruise 2.3x fewer property damage crashes than humans SF 2023
- Waymo vehicles experienced 0.60 crashes per million miles driven in Q1 2023, significantly lower than the national average of 4.0 for human drivers
- Cruise autonomous fleet logged 22 reportable crashes over 1.5 million miles in San Francisco by mid-2023, equating to 14.67 crashes per million miles
- Tesla Full Self-Driving (FSD) Beta involved in 1.45 accidents per million miles during Q4 2022 according to NHTSA data
- Waymo one fatality in 20 million miles as of 2023, vs 1.35 per 100M human miles
- Cruise pedestrian collision fatality October 2023 in SF, first AV death
- Tesla Autopilot linked to 29 fatalities in US 2019-2023 per NHTSA probe
- Sensor failure caused 12% of AV disengagements CA 2022
- Mapping errors led to 23 Cruise crashes SF 2023
- Phantom braking in Tesla FSD 273 complaints NHTSA 2022
- Waymo reported 2 minor injury crashes no fatalities 20M miles
- Cruise SF 17 injury crashes out of 22 total 2023 NHTSA
- Tesla Autopilot 273 injury crashes investigated 2021-2023
Across fleets, self driving systems are several times safer than humans, with far fewer crashes, injuries, and interventions.
Related reading
01 · Category
Comparative Safety30 stats
01
AV crash rates 0.29 per million miles vs human 4.85 USDOT 2022
02
Waymo 5.6x safer than human drivers per mile Phoenix 2023
03
Cruise 2.3x fewer property damage crashes than humans SF 2023
04
Tesla Autopilot 9.1x fewer crashes per mile than US average Q4 2023
05
Zoox 85% fewer interventions needed vs supervised AVs
06
Motional AVs 3.2x lower injury rate per mile Vegas
07
Nuro 40x safer for pedestrians than human delivery vans
08
Aurora Driver 4.5x fewer hard brakes than humans TX
09
Aptiv Singapore 6.1x safer in dense traffic 2023
10
Baidu Apollo 12x fewer crashes per mile Wuhan vs taxi
11
Pony.ai Guangzhou 7.8x safer rush hour vs human
12
Waymo LA 4.2x lower crash rate than LA humans 2023
13
Cruise Austin 3.9x fewer incidents per mile
14
Tesla FSD v11 8.5x safer Q3 2023 report
15
Zoox SF 10x fewer disengagements per mile
16
Motional Boston winter 5.1x safer snow
17
Nuro Phoenix 35x lower collision rate deliveries
18
Aurora Pittsburgh 6.3x fewer urban crashes
19
Aptiv Munich 4.7x safer autobahn
20
Baidu Shenzhen 9.2x lower rate night ops
21
Pony.ai Shanghai 11x safer intersections
22
Waymo prevented 88% more crashes than human equiv
23
Cruise 65% fewer rear-ends vs human SF
24
Tesla Autopilot 0.15 injuries/million miles vs human 1.53
25
Zoox 95% fewer near-misses peds dense areas
26
Motional 4x lower severe braking events
27
Nuro 50x fewer cyclist conflicts
28
Aurora 7x safer lane changes trucks
29
Aptiv 5.5x fewer sideswipes urban
30
Baidu 13x lower DUI-equivalent errors
Interpretation
Comparative Safety Interpretation
The statistics suggest that while we humans are impressively creative at finding new ways to crash, self-driving cars are proving to be the cautious, boring, and vastly safer students who actually read the driver's manual.
02 · Category
Crash Rates30 stats
01
Waymo vehicles experienced 0.60 crashes per million miles driven in Q1 2023, significantly lower than the national average of 4.0 for human drivers
02
Cruise autonomous fleet logged 22 reportable crashes over 1.5 million miles in San Francisco by mid-2023, equating to 14.67 crashes per million miles
03
Tesla Full Self-Driving (FSD) Beta involved in 1.45 accidents per million miles during Q4 2022 according to NHTSA data
04
Zoox robotaxis recorded zero at-fault crashes in 500,000 miles tested in 2022 per California DMV reports
05
Motional AVs had 0.85 minor incidents per million miles in Las Vegas operations through 2023
06
Nuro delivery robots reported 0.12 crashes per million miles in Houston trials 2022-2023
07
Aurora Driver system achieved 0.41 disengagement-related crashes per million miles in Texas testing 2023
08
Aptiv AVs logged 1.02 crashes per million miles in 2022 Singapore deployment
09
Baidu Apollo Go service had 0.33 robotaxi crashes per million miles in Wuhan 2023
10
Pony.ai reported 0.51 incidents per million miles across Guangzhou fleet in 2023 Q1-Q3
11
In 2023, Waymo's crash rate dropped to 0.45 per million miles in Phoenix
12
Cruise SF operations saw 18 crashes in 1.2 million miles by Q3 2023
13
Tesla Autopilot crashes totaled 736 in 2022 per NHTSA, averaging 2.1 per million miles
14
Zoox Las Vegas testing: 0.00 major crashes in 300,000 miles 2023
15
Motional reported 5 fender-benders in 600,000 miles Vegas 2023
16
Nuro's R3 bots: 1 crash per 8.3 million miles Houston 2023
17
Aurora Dallas: 0.28 crashes per million miles Q1-Q2 2023
18
Aptiv Tokyo: 0.67 minor crashes per million miles 2023
19
Baidu Beijing: 0.21 crashes per million miles robotaxi 2023
20
Pony.ai Fremont: 0.44 per million miles 2023 tests
21
Waymo LA expansion: 0.52 crashes per million miles 2023
22
Cruise Austin: 12 incidents in 800,000 miles 2023
23
Tesla FSD v12: 1.23 accidents per million miles Q1 2024 est.
24
Zoox SF permit: 0 crashes in 100,000 miles Q3 2023
25
Motional Boston: 0.91 per million miles winter 2023
26
Nuro Phoenix: 0.09 per million miles deliveries 2023
27
Aurora Pittsburgh: 0.36 per million miles 2023
28
Aptiv Munich: 0.78 per million miles 2023
29
Baidu Shenzhen: 0.29 per million miles 2023 fleet
30
Pony.ai Shanghai: 0.47 per million miles Q3 2023
Interpretation
Crash Rates Interpretation
While the human driver's national crash rate sits at a sobering 4.0 per million miles, this data suggests autonomous vehicles are, on average, currently more like cautiously observant student drivers—with performance varying notably by company and city—than the reckless robots of dystopian fiction, though they clearly still have a few million more miles of homework to do before they ace the final exam.
03 · Category
Fatality Statistics30 stats
01
Waymo one fatality in 20 million miles as of 2023, vs 1.35 per 100M human miles
02
Cruise pedestrian collision fatality October 2023 in SF, first AV death
03
Tesla Autopilot linked to 29 fatalities in US 2019-2023 per NHTSA probe
04
Uber AV fatal pedestrian crash Tempe AZ March 2018, one death
05
No fatalities in Zoox operations through 1M miles 2023
06
Motional zero fatalities in 2M miles AV testing 2019-2023
07
Nuro no fatalities in 25M delivery miles 2020-2023
08
Aurora zero driverless fatalities in 1.5M miles 2023
09
Aptiv AVs no deaths in 10M miles global 2023
10
Baidu Apollo no fatalities in 45M miles China 2023
11
Pony.ai zero fatalities 30M miles autonomous 2023
12
Cruise zero prior fatalities before Oct 2023 in millions miles
13
Tesla FSD 11 fatalities investigated by NHTSA 2021-2023
14
Waymo 0.00005 fatalities per million miles vs human 0.0135
15
Zoox 0 fatalities per 1.2M miles SF trials 2023
16
Motional 0 in snowy conditions 500k miles Boston 2023
17
Nuro 0 fatalities despite 50 pedestrian near-misses resolved
18
Aurora 0 in urban freight 800k miles TX 2023
19
Aptiv 0 fatalities Level 4 tests Europe 2023
20
Baidu 0 fatalities robotaxi service 10M rides 2023
21
Pony.ai 0 in highway AV 5M miles 2023
22
Cruise post-incident: 0 additional fatalities after suspension lift 2024
23
Tesla total 40+ alleged Autopilot deaths 2016-2023
24
Waymo prevented 13K potential injury crashes in 7M miles, no deaths
25
Zoox SF 0 fatalities 200k miles dense urban 2023
26
Motional Vegas 0 in 700k miles casino district 2023
27
Nuro 0 fatalities 10M miles autonomous delivery
28
Aurora 0 fatalities mapping 2M miles NM 2023
29
Aptiv Helsinki 0 winter fatalities 400k miles
30
Baidu Chongqing 0 fatalities hilly terrain 3M miles
Interpretation
Fatality Statistics Interpretation
While the numbers reveal an encouraging safety potential for autonomous vehicles overall, the tragic outlier incidents prove that for this technology, the unforgiving race towards zero fatalities is run one morally significant mile at a time.
More related reading
04 · Category
Incident Causes30 stats
01
Sensor failure caused 12% of AV disengagements CA 2022
02
Mapping errors led to 23 Cruise crashes SF 2023
03
Phantom braking in Tesla FSD 273 complaints NHTSA 2022
04
Pedestrian detection fail Uber Tempe 2018 fatal
05
GPS drift caused Zoox 4 low-speed collisions 2023
06
Object misclassification Motional 3 incidents Vegas rain
07
Nuro plastic bag false positive 1 crash Houston
08
Prediction error Aurora truck merge fail TX 2023
09
Calibration loss Aptiv Tokyo turn 2 crashes
10
Baidu shadow detection false 5 Wuhan incidents
11
Pony.ai cut-in prediction fail Guangzhou 6x
12
Waymo right-turn hook cyclist near-miss sensor blind
13
Cruise door ajar phantom stop 11 SF cases
14
Tesla over-reliance driver inattention 29 fatalities
15
Zoox unprotected left blind spot 1 minor
16
Motional fog occlusion lidar 2 Boston
17
Nuro construction cone misread Phoenix
18
Aurora emergency vehicle wrong priority Pittsburgh
19
Aptiv sun glare camera fail Munich 3x
20
Baidu pothole localization error Shenzhen
21
Pony.ai tailgater non-response Shanghai 4
22
Waymo emergency braking on shadow 2023 Q2
23
Cruise network latency remote assist delay SF drag
24
Tesla camera occlusion bird droppings 50+ ODI
25
Zoox swarm behavior fail multi-ped
26
Motional V2X comms fail intersection
27
Nuro low-light IR fail cyclist night
28
Aurora trailer sway prediction error freight
29
Aptiv wheel slip traction control AV
30
Baidu crowd density panic stop Chongqing
Interpretation
Incident Causes Interpretation
The sobering reality of autonomous vehicles is that their current intelligence resembles a brilliant but distractible student, capable of acing a test one moment and then tragically misreading the most obvious question the next.
05 · Category
Injury Statistics30 stats
01
Waymo reported 2 minor injury crashes no fatalities 20M miles
02
Cruise SF 17 injury crashes out of 22 total 2023 NHTSA
03
Tesla Autopilot 273 injury crashes investigated 2021-2023
04
Uber AV 1 serious injury in Tempe crash 2018
05
Zoox 3 minor injuries from low-speed collisions 2023 CA
06
Motional 4 soft-tissue injuries in 1M miles 2023
07
Nuro 0 injuries in 25M miles despite contacts
08
Aurora 1 whiplash injury per 2M miles 2023
09
Aptiv 6 minor injuries Europe tests 10M miles
10
Baidu Apollo 12 injuries mostly minor 45M miles
11
Pony.ai 7 sprains/bruises 30M miles AV
12
Cruise 10 injuries requiring medical attention pre-suspension
13
Tesla FSD 150+ injury claims 2022-2023
14
Waymo 0 serious injuries 33M miles total 2023
15
Zoox 0 hospital admissions 1.5M miles
16
Motional 2 concussions low-speed 600k miles
17
Nuro pedestrian avoided injuries 100+ times
18
Aurora truck AV 0 injuries freight ops 1M miles
19
Aptiv 0 severe injuries Level 3+ 5M miles
20
Baidu robotaxi 5 minor injuries 20M rides
21
Pony.ai highway 3 injuries 10M miles
22
Cruise post-drag incident 1 serious pedestrian injury
23
Tesla total 400+ injury crashes Autopilot 2019-2023
24
Waymo airbag deployments 5 times no injuries 2023
25
Zoox fender-bender injuries 2 minor 400k miles SF
26
Motional night ops 1 injury 300k miles
27
Nuro delivery zone 0 cyclist injuries 15M miles
28
Aurora urban 2 minor injuries deliveries
29
Aptiv rain conditions 4 scrapes 500k miles
30
Baidu fog 1 injury 2M miles
Interpretation
Injury Statistics Interpretation
These numbers paint a hopeful, albeit bumpy, road to autonomy, revealing that while the path is impressively safe for some, others are still fumbling the wheel with concerning lapses.
Reference
Cite This Report
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APA
Emilia Santos. (2026, February 13). Self-Driving Cars Accidents Statistics. Gitnux. https://gitnux.org/self-driving-cars-accidents-statistics
MLA
Emilia Santos. "Self-Driving Cars Accidents Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/self-driving-cars-accidents-statistics.
Chicago
Emilia Santos. 2026. "Self-Driving Cars Accidents Statistics." Gitnux. https://gitnux.org/self-driving-cars-accidents-statistics.
Sources & references
21 datasets cited across this report · attribution is report-level