Extracting Traffic Primitives Directly from Naturalistically Logged Data for Self-Driving Applications

11 Sep 2017 Wenshuo Wang Ding Zhao

Developing an automated vehicle, that can handle complicated driving scenarios and appropriately interact with other road users, requires the ability to semantically learn and understand driving environment, oftentimes, based on analyzing massive amounts of naturalistic driving data. An important paradigm that allows automated vehicles to both learn from human drivers and gain insights is understanding the principal compositions of the entire traffic, termed as traffic primitives... (read more)

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