"Currently, we ensure safety on the roads by regulating the performance of the various mechanical systems of vehicles and by licensing drivers," said Alex John London, professor at Carnegie Mellon University in the US.
"When cars drive themselves we have no comparable system for evaluating the safety and reliability of their autonomous driving systems," said London.
Professor David Danks and London point to the US Department of Transportation's recent attempt to develop safety regulations for driverless cars as an example of traditional guidelines that do not adequately test and monitor the novel capabilities of autonomous systems.
"Self-driving cars and autonomous systems are rapidly spreading through every part of society, but their successful use depends on whether we can trust and understand them," said Danks.
"We, as a society, need to find new ways to monitor and guide the development and implementation of these autonomous systems," he said.
The phased process Danks and London propose would begin with "pre-clinical trials," or testing in simulated environments, such as self-driving cars navigating varied landscapes and climates.
Acceptable performance would permit the system to move on to "in-human" studies through a limited introduction into real-world environments with trained human "co-pilots."
Successful trials in these targeted environments would then lead to monitored, permit-based testing, and further easing of restrictions as performance goals were met.
Danks and London propose that this regulatory system should be modelled and managed similarly to how the US Food and Drug Administration (FDA) regulates the drug approval process.
Disclaimer: No Business Standard Journalist was involved in creation of this content
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