When intelligent transportation systems sensing meets edge computing: Vision and challenges

X Zhou, R Ke, H Yang, C Liu - Applied Sciences, 2021 - mdpi.com
The widespread use of mobile devices and sensors has motivated data-driven applications
that can leverage the power of big data to benefit many aspects of our daily life, such as …

Vision-based traffic accident detection and anticipation: A survey

J Fang, J Qiao, J Xue, Z Li - … on Circuits and Systems for Video …, 2023 - ieeexplore.ieee.org
Traffic accident detection and anticipation is an obstinate road safety problem and
painstaking efforts have been devoted. With the rapid growth of video data, Vision-based …

Abductive Ego-View Accident Video Understanding for Safe Driving Perception

J Fang, L Li, J Zhou, J **ao, H Yu… - Proceedings of the …, 2024 - openaccess.thecvf.com
We present MM-AU a novel dataset for Multi-Modal Accident video Understanding. MM-AU
contains 11727 in-the-wild ego-view accident videos each with temporally aligned text …

Real-time driving risk assessment using deep learning with XGBoost

L Shi, C Qian, F Guo - Accident Analysis & Prevention, 2022 - Elsevier
Traffic crashes typically occur in a few seconds and real-time prediction can significantly
benefit traffic safety management and the development of safety countermeasures. This …

Efficient fusion decision system for predicting road crash events: a comparative simulator study for imbalance class handling

Z Elamrani Abou Elassad, M Ameksa… - Transportation …, 2024 - journals.sagepub.com
Road crash events are a fact of life. Although significant progress have been made in
adopting machine learning techniques for analyzing road crashes, there has been limited …

Two-stream video-based deep learning model for crashes and near-crashes

L Shi, F Guo - Transportation Research Part C: Emerging …, 2024 - Elsevier
The use of videos for effective crash and near-crash prediction can significantly enhance the
development of safety countermeasures and emergency response. This paper presents a …

Exploring event-driven dynamic context for accident scene segmentation

J Zhang, K Yang, R Stiefelhagen - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The robustness of semantic segmentation on edge cases of traffic scene is a vital factor for
the safety of intelligent transportation. However, most of the critical scenes of traffic accidents …

[HTML][HTML] Extracting dashcam telemetry data for predicting energy use of electric vehicles

GWM Hind, EEF Ballantyne, T Stincescu, R Zhao… - Transportation Research …, 2024 - Elsevier
Prior to the acquisition of an electric vehicle, pre-evaluation of vehicle energy use is
desirable to assess whether the intrinsic vehicle electrical storage capability is satisfactory …

CRS: A privacy-preserving two-layered distributed machine learning framework for IoV

R Liu, J Pan - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Nowadays, vehicles can provide many valuable data (such as the videos recorded by
dashcams) for analytical model building. Integrating vehicular ad hoc networks with the …

Attention r-cnn for accident detection

TN Le, S Ono, A Sugimoto… - 2020 IEEE intelligent …, 2020 - ieeexplore.ieee.org
This paper addresses accident detection where we not only detect objects with classes, but
also recognize their characteristic properties. More specifically, we aim at simultaneously …