

Self-driving cars and other vehicles are being increasingly demonstrated, released, and deployed on roads. Yet only a handful of special-case vehicles have obtained a permit to go fully driverless, and our passenger cars still require drivers at the steering wheel to correct the car if something goes wrong. Safety drivers, which operate autonomous vehicles in testing phases, upon occasions were unable to correct the faulty behavior of their vehicles, inducing accidents and, unfortunately, casualties. This article proposes a method to analyze the reliability of autonomous vehicles applying the classical reliability theory and software reliability growth models (SRGMs). This method is then applied to real-world data to get some predictions on what is really needed to safely remove the driver and go fully driverless. © 2009-2012 IEEE.
| Engineering controlled terms: | AccidentsAutonomous vehiclesISO StandardsSafety testingSoftware reliability |
|---|---|
| Engineering uncontrolled terms | Autonomous VehiclesDriverlessHardwareISO standardsReal-worldSoftware reliability growth modelsSteering wheelTesting phase |
| Engineering main heading: | Reliability theory |
Bjelica, M.Z.; Division of Extended Studies, University of California San Diego, San Diego, United States;
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