A-Eye: Driving with the Eyes of AI for Corner Case Generation

02/22/2022
by   Kamil Kowol, et al.
0

The overall goal of this work is to enrich training data for automated driving with so called corner cases. In road traffic, corner cases are critical, rare and unusual situations that challenge the perception by AI algorithms. For this purpose, we present the design of a test rig to generate synthetic corner cases using a human-in-the-loop approach. For the test rig, a real-time semantic segmentation network is trained and integrated into the driving simulation software CARLA in such a way that a human can drive on the network's prediction. In addition, a second person gets to see the same scene from the original CARLA output and is supposed to intervene with the help of a second control unit as soon as the semantic driver shows dangerous driving behavior. Interventions potentially indicate poor recognition of a critical scene by the segmentation network and then represents a corner case. In our experiments, we show that targeted enrichment of training data with corner cases leads to improvements in pedestrian detection in safety relevant episodes in road traffic.

READ FULL TEXT

page 2

page 5

research
05/23/2023

survAIval: Survival Analysis with the Eyes of AI

In this study, we propose a novel approach to enrich the training data f...
research
12/09/2021

Does Redundancy in AI Perception Systems Help to Test for Super-Human Automated Driving Performance?

While automated driving is often advertised with better-than-human drivi...
research
06/09/2022

What should AI see? Using the Public's Opinion to Determine the Perception of an AI

Deep neural networks (DNN) have made impressive progress in the interpre...
research
12/02/2021

"Just Drive": Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving

Biases can filter into AI technology without our knowledge. Oftentimes, ...
research
09/20/2019

AIBA: An AI Model for Behavior Arbitration in Autonomous Driving

Driving in dynamically changing traffic is a highly challenging task for...
research
12/15/2020

Artificial Dummies for Urban Dataset Augmentation

Existing datasets for training pedestrian detectors in images suffer fro...
research
10/17/2022

Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving

Trajectory data analysis is an essential component for highly automated ...

Please sign up or login with your details

Forgot password? Click here to reset