Safe, efficient, and comfortable velocity control based on reinforcement learning for autonomous driving
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 …
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 …
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
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 …
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
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 …
identification (re-id) with attention-based models, specifically focusing on regions of a …
VehicleNet: Learning robust visual representation for vehicle re-identification
One fundamental challenge of vehicle re-identification (re-id) is to learn robust and
discriminative visual representation, given the significant intra-class vehicle variations …
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
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 …
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
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 …
computer vision due to the growing utilization of surveillance cameras in public security …
Multi-domain learning and identity mining for vehicle re-identification
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 …
Track2 is a vehicle re-identification (ReID) task with both the real-world data and synthetic …
[PDF][PDF] The 2019 AI City Challenge.
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 …
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
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 …
of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based …