A Deep-Learning Approach to Detect and Classify Heavy-Duty Trucks in Satellite Images [0.03%]
基于深度学习的遥感影像重型卡车检测与分类方法研究
Xingwei Liu,Yiqiao Li,Langting Sizemore et al.
Xingwei Liu et al.
Heavy-duty trucks serve as the backbone of the supply chain and have a tremendous effect on the economy. However, they severely impact the environment and public health. This study presents a novel truck detection framework by combining sat...
Deep Reinforcement Learning Assisted Beam Tracking and Data Transmission for 5G V2X Networks [0.03%]
深度强化学习辅助的5G车联网波束跟踪和数据传输研究
Junliang Ye,Hamid Gharavi
Junliang Ye
Beam tracking is a core issue in 5G vehicle-to-everything (V2X) networks. Specifically, higher beamforming gain is required to compensate for the path loss at higher frequencies, e.g., 5G FR2, to realize high data rate vehicle-toinfrastruct...
Routing and Rebalancing Intermodal Autonomous Mobility-on-Demand Systems in Mixed Traffic [0.03%]
混合交通环境中联运自主出行需求的路由与再平衡算法研究
Salomón Wollenstein-Betech,Mauro Salazar,Arian Houshmand et al.
Salomón Wollenstein-Betech et al.
This paper studies congestion-aware route-planning policies for intermodal Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on-demand mobility jointly with public transit under mixed traffic cond...
Digital Twins in Unmanned Aerial Vehicles for Rapid Medical Resource Delivery in Epidemics [0.03%]
无人机数字孪生体在传染病疫情中快速投放医疗资源中的应用研究
Zhihan Lv,Dongliang Chen,Hailin Feng et al.
Zhihan Lv et al.
The purposes are to explore the effect of Digital Twins (DTs) in Unmanned Aerial Vehicles (UAVs) on providing medical resources quickly and accurately during COVID-19 prevention and control. The feasibility of UAV DTs during COVID-19 preven...
Tianhong Zhao,Wei Tu,Zhixiang Fang et al.
Tianhong Zhao et al.
The coronavirus disease 2019 (COVID-19) epidemic has spread worldwide, posing a great threat to human beings. The stay-home quarantine is an effective way to reduce physical contacts and the associated COVID-19 transmission risk, which requ...
Error Measures for Trajectories Estimations with Geo-tagged Mobility Sample Data [0.03%]
地理标签移动样本数据的轨迹估计误差度量方法研究
Mohsen Parsafard,Guangqing Chi,Xiaobo Qu et al.
Mohsen Parsafard et al.
Although geo-tagged mobility data (e.g., cell phone data and social media data) can be potentially used to estimate individual space-time travel trajectories, they often have low sample rates that only tell travelers' whereabouts at the spa...
Ejaz Ahmed,Hamid Gharavi
Ejaz Ahmed
With the remarkable progress of cooperative communication technology in recent years, its transformation to vehicular networking is gaining momentum. Such a transformation has brought a new research challenge in facing the realization of co...
Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques [0.03%]
基于重要性抽样技术的自动车辆换道场景安全评估方法研究
Ding Zhao,Henry Lam,Huei Peng et al.
Ding Zhao et al.
Automated vehicles (AVs) must be thoroughly evaluated before their release and deployment. A widely used evaluation approach is the Naturalistic-Field Operational Test (N-FOT), which tests prototype vehicles directly on the public roads. Du...
Gap Acceptance During Lane Changes by Large-Truck Drivers-An Image-Based Analysis [0.03%]
基于图像的大货车车道变换间隙接受行为分析研究
Kazutoshi Nobukawa,Shan Bao,David J LeBlanc et al.
Kazutoshi Nobukawa et al.
This paper presents an analysis of rearward gap acceptance characteristics of drivers of large trucks in highway lane change scenarios. The range between the vehicles was inferred from camera images using the estimated lane width obtained f...
Automatic Calibration Method for Driver's Head Orientation in Natural Driving Environment [0.03%]
自然驾驶环境下的驾驶员头姿自动标定方法
Xianping Fu,Xiao Guan,Eli Peli et al.
Xianping Fu et al.
Gaze tracking is crucial for studying driver's attention, detecting fatigue, and improving driver assistance systems, but it is difficult in natural driving environments due to nonuniform and highly variable illumination and large head move...