INTRODUCTION

The Road Rage Reasoning (Gu-RRR-v1) Dataset is constructed by the I+ lab at the University of Electronic Science and Technology of China (UESTC). The “Gu-RRR-v1” dataset contains multiple external driving events recorded by dashcams, which pose dangers, aggression, or obstacles to the ego car, thereby eliciting varying degrees of anger in drivers.

The entire dataset comprises 81 videos (sampled at 2 frames per second, resulting in 2,299 images), covering 3 types of road rage scenarios and 9 types of road rage behaviors. The annotation information includes weather conditions, road types, road conditions, and more. Additionally, the dataset annotates the ego car and critical object (including pedestrian and vehicle) in the video that trigger anger, with detailed descriptions of actions and positions provided frame by frame. For details of the paper, see pdf.

The Gu-RRR-v1 dataset is now available for academic purposes only, distributed on a case-by-case basis. The I+ Lab at the UESTC serves as the constructor and distributor of the dataset and retains the copyright of all videos and images within the dataset. Any researcher requesting access to the Gu-RRR-v1 dataset must sign this agreement and thereby agrees to adhere to the restrictions outlined in this document.

DATASET STATISTIC

Overview:

Environment Description:

• weather: sunny, rainy, unknow.
• time: daytime, night, unknow.
• road type: highway, city road, township road.
• road condition: normal, busy, congested.

Object Description:

• number of lanes: integer.
• ego lane number: integer.
• ego lane condiiton: normal, congested.
• ego lane type: dashed lane, solid lane, dashed-solid lane, solid-dashed lane.
• ego motions: forward, stop, go ahead to the left, go ahead to the right.
• critical object description: like white car, red van, electric car, pedestrian and so on.
• critical object lane number: integer.
• critical object relative position: left, right, front, left front, right front.
• critical object distance: normal (safe distance to drive), relatively close (requires increased attention), dangerous (approaching or already in a collision).
• critical object motions can be described as (It can be a free combination of the following meta-actions. For vehicle, you need to describe them using genneral motions, vehicle motions and vehicle signals. For non-vehicle entity, you need to describe them using general motions and other motions):
  • general motions: forward, slow down, stop, go ahead to the left, go ahead to the right.
  • vehicle motions: overtake, pull into ego lane to the left, pull into ego lane to the right.
  • vehicle signals: no turn signal, brake.
  • other motions: crossing the street from left to right, crossing the street from right to left.

LICENSE

• The videos, images, and corresponding annotation results can only be used for ACADEMIC PURPOSES. NO COMMERCIAL USE is allowed.
• Copyright © I+ Lab, University of Electronic Science and Technology of China (UESTC). All rights reserved.

DOWNLOAD

You can download the agreement (pdf) from here. After filling it, please send the electrical version to our Email: 202411081538@std.uestc.edu.cn (Subject: Gu-RRR-v1-Agreement) .

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