Parsing Parking Instructions for Self-driving Cars into Spatial Semantic Descriptions

This study is motivated by an attempt to develop a system that can control a self-driving car by words. To achieve this, the verbal instructions we provide to the car must be grounded onto the real-world phenomena. With this background, in this study, we extend the framework of semantic description clause (SDC) proposed by We developed a pipeline of a CCG parser, a reranker of parse trees and a converter from parse trees into SDCs. The result of parsing the instructions with the extended CCG grammar shows 84.7% accuracy on 6,019 various Japanese driving instructions. We finally convert the parse trees into SDCs using conversion rules, resulting in 90.4% accuracy on 5,638 parse trees.