This paper introduces SynTraC, the first public image-based traffic signal control dataset, aimed at bridging the gap between simulated environments and real-world traffic management challenges. Unlike traditional datasets for traffic signal control which aim to provide simplified feature vectors like vehicle counts from traffic simulators, SynTraC provides real-style images from the CARLA simulator with annotated features, along with traffic signal states. This image-based dataset comes with diverse real-world scenarios, including varying weather and times of day. Additionally, SynTraC also provides different reward values for advanced traffic signal control algorithms like reinforcement learning. Experiments with SynTraC demonstrate that it is still an open challenge to image-based traffic signal control methods compared with feature-based control methods, indicating our dataset can further guide the development of future algorithms. The code for this paper can be found in \url{https://github.com/DaRL-LibSignal/SynTraC}.SynTraC
Traffic-Net: 3D Traffic Monitoring Using a Single Camera
Institute for Transport Studies, The University of Leeds（利兹大学交通研究所）；Qazvin University（加兹温大学）；Tehran Azad University, Science & Research Branch（德黑兰阿扎德大学科学与研究分院）
Intelligent ROI-Based Vehicle Counting Framework for Automated Traffic Monitoring
Electrical Engineering Dept., Faculty of Energy Engineering, Aswan University（能源工程学院电气工程系，阿斯旺大学）；Electrical Engineering Dept., Faculty of Engineering, Sohag University（工程学院电气工程系，索哈格大学）；Electrical Engineering Dept., Faculty of Engineering, Aswan University（工程学院电气工程系，阿斯旺大学）；Information Technology Dept., New Assiut Technological University (NATU)（新阿西乌特科技大学（NATU）信息科技系）；CEIEC Research Institute, Universidad Francisco de Vitoria（CEIEC研究机构，弗洛里亚努大学）
An Intelligent Monitoring System of Vehicles on Highway Traffic
University of Engineering and Technology Peshawar（白沙瓦工程技术大学）；University of Swabi（斯瓦比大学）；COMSATS University Islamabad（伊斯兰堡COMSATS大学）；Jessore University of Science and Technology（杰索尔科技大学）
VINEVI: A Virtualized Network Vision Architecture for Smart Monitoring of Heterogeneous Applications and Infrastructures
Institute of Exact and Technological Sciences (IEP), Federal University of Viçosa（维索萨联邦大学精确与技术科学研究所）；Faculty of Computing (FACOM), Federal University of Uberlândia（Uberlândia联邦大学计算学院）
SCOPE: A Lightweight-training LLM Framework for Air Traffic Control Readback Monitoring
Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology（香港科学与技术大学机械与航空航天工程系）；School of Electronic and Information Engineering, Beihang University（北航电子与信息工程学院）；State Key Laboratory of CNS/ATM（国家空管自动化系统实验室）
Video-to-Text Pedestrian Monitoring (VTPM): Leveraging Computer Vision and Large Language Models for Privacy-Preserve Pedestrian Activity Monitoring at Intersections
