Safe, efficient, and comfortable velocity control based on reinforcement learning for autonomous driving

M Zhu, Y Wang, Z Pu, J Hu, X Wang, R Ke - Transportation Research Part …, 2020 - Elsevier
A model used for velocity control during car following is proposed based on reinforcement
learning (RL). To optimize driving performance, a reward function is developed by …

A survey of vehicle re-identification based on deep learning

H Wang, J Hou, N Chen - IEEE Access, 2019 - ieeexplore.ieee.org
Vehicle re-identification is one of the core technologies of intelligent transportation systems,
and it is crucial for the construction of smart cities. With the rapid development of deep …

Deep adaptive control: Deep reinforcement learning-based adaptive vehicle trajectory control algorithms for different risk levels

Y He, Y Liu, L Yang, X Qu - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
In this study, we explore the problem of adaptive vehicle trajectory control for different risk
levels. Firstly, we introduce a sliding window-based car-following scenario extraction …

The devil is in the details: Self-supervised attention for vehicle re-identification

P Khorramshahi, N Peri, J Chen… - Computer Vision–ECCV …, 2020 - Springer
In recent years, the research community has approached the problem of vehicle re-
identification (re-id) with attention-based models, specifically focusing on regions of a …

VehicleNet: Learning robust visual representation for vehicle re-identification

Z Zheng, T Ruan, Y Wei, Y Yang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
One fundamental challenge of vehicle re-identification (re-id) is to learn robust and
discriminative visual representation, given the significant intra-class vehicle variations …

Cooperative multi-camera vehicle tracking and traffic surveillance with edge artificial intelligence and representation learning

HF Yang, J Cai, C Liu, R Ke, Y Wang - Transportation research part C …, 2023 - Elsevier
Traffic surveillance cameras are the eyes of the Intelligent Transportation Systems (ITS).
However, they are currently isolated and can only extract information from each of their fixed …

Stripe-based and attribute-aware network: A two-branch deep model for vehicle re-identification

J Qian, W Jiang, H Luo, H Yu - Measurement Science and …, 2020 - iopscience.iop.org
Vehicle re-identification (Re-ID) has been attracting increasing interest in the field of
computer vision due to the growing utilization of surveillance cameras in public security …

Multi-domain learning and identity mining for vehicle re-identification

S He, H Luo, W Chen, M Zhang… - Proceedings of the …, 2020 - openaccess.thecvf.com
This paper introduces our solution for the Trcak2 in AI City Challenge 2020 (AICITY20). The
Track2 is a vehicle re-identification (ReID) task with both the real-world data and synthetic …

[PDF][PDF] The 2019 AI City Challenge.

M Naphade, Z Tang, MC Chang… - CVPR …, 2019 - openaccess.thecvf.com
Abstract The AI City Challenge has been created to accelerate intelligent video analysis that
helps make cities smarter and safer. With millions of traffic video cameras acting as sensors …

Multi-target multi-camera tracking of vehicles using metadata-aided re-id and trajectory-based camera link model

HM Hsu, J Cai, Y Wang, JN Hwang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we propose a novel framework for multi-target multi-camera tracking (MTMCT)
of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based …