DeepCrashTest: Turning Dashcam Videos into Virtual Crash Tests for Automated Driving Systems

• URL: http://arxiv.org/abs/2003.11766v1
• Date: Thu, 26 Mar 2020 07:03:45 GMT
• Title: DeepCrashTest: Turning Dashcam Videos into Virtual Crash Tests for Automated Driving Systems
• Authors: Sai Krishna Bashetty, Heni Ben Amor, Georgios Fainekos
• Abstract summary: We use dashcam crash videos uploaded to the internet to extract valuable collision data. We tackle the problem of extracting 3D vehicle trajectories from videos recorded by an unknown and uncalibrated monocular camera source.
• Score: 9.17424462858218
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The goal of this paper is to generate simulations with real-world collision scenarios for training and testing autonomous vehicles. We use numerous dashcam crash videos uploaded on the internet to extract valuable collision data and recreate the crash scenarios in a simulator. We tackle the problem of extracting 3D vehicle trajectories from videos recorded by an unknown and uncalibrated monocular camera source using a modular approach. A working architecture and demonstration videos along with the open-source implementation are provided with the paper.

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