@inproceedings{7ec378da4c264760abc21c0978243356,
title = "AC3R: automatically reconstructing car crashes from police reports",
abstract = "Autonomous driving carries the promise to drastically reduce car accidents, but recently reported fatal crashes involving self-driving cars suggest that the self-driving car software should be tested more thoroughly. For addressing this need, we introduce AC3R (Automatic Crash Constructor from Crash Report) which elaborates police reports to automatically recreate car crashes in a simulated environment that can be used for testing self-driving car software in critical situations. AC3R enables developers to quickly generate relevant test cases from the massive historical dataset of recorded car crashes. We demonstrate how AC3R can generate simulations of different car crashes and report the findings of a large user study which concluded that AC3R simulations are accurate. A video illustrating AC3R in action is available at: https://youtu.be/V708fDG_ux8.",
keywords = "Natural language processing, Self-driving cars, Test case generation",
author = "Tri Huynh and Alessio Gambi and Gordon Fraser",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.",
year = "2019",
month = may,
day = "31",
doi = "10.1109/ICSE-Companion.2019.00031",
language = "English",
series = "Proceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering: Companion, ICSE-Companion 2019",
publisher = "IEEE / ACM",
pages = "31--34",
editor = "Atlee, {Joanne M.} and Tevfik Bultan and Jon Whittle",
booktitle = "Proceedings - 2019 IEEE/ACM 41st International Conference on Software Engineering",
}