LZ
L. Zhang
2 records found
1
One of the critical challenges in automated driving is ensuring safety of automated vehicles despite the unknown behavior of the other vehicles. Although motion prediction modules are able to generate a probability distribution associated with various behavior modes, their probab
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In this paper, we propose a novel behavior planner that combines game
theory with search-based planning for automated lane merging.
Specifically, inspired by human drivers, we model the interaction
between vehicles as a gap selection process. To overcome the challenge
of mult
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