Drivers and pedestrians are expected to follow the road rules they learned in school but in reality, that is often not the case. Pedestrians cross against a red light if the road is clear. Drivers lose patience in slow traffic and cut into the next lane when they see an opening.
While today’s autonomous driving systems have made great progress in avoiding accidents by using sensors and cameras they are still a long way from being able to accurately anticipate what an unpredictable human being might do. Experts say that technical limitation will slow the widespread adoption of autonomous driving in urban and city environments.
Now a number of startups are trying to solve the problem by building human behavior data sets that help self-driving car systems predict and understand human behavior more accurately.
“A human behavior data set will be a great aid in the current development phase of self-driving cars,” said Li-Ta Hsu, assistant professor at the Hong Kong Polytechnic University, whose research work includes autonomous driving. “People spend [their first] 18 years learning social rules to be able to pass a driving test. Current autonomous cars don’t have that level of social understanding.”
Berlin-based Phantasma Lab, started by two entrepreneurs who became friends after they met at a talent investor program in the German city, is developing a human behavior data set using virtual simulations based on mathematical rules and is now in talks with Chinese self-driving car makers about adopting the technology.
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