| 标题 |
 Enhancing VRUs Safety Through Mobility-Aware Workload Orchestration with Trajectory Prediction using Reinforcement Learning 使用强化学习进行轨迹预测，通过移动感知工作负载编排增强VRU安全性
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工作量
强化学习
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编配
计算机科学
人工智能
操作系统
天文
物理
艺术
视觉艺术
音乐剧
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| 网址 | |
| DOI | |
| 其它 | Vulnerable road users (VRUs) such as pedestrians, cyclists, motorcyclists, and animals are at the highest risk in the road traffic environment since they move in the environment without any protection. Various applications and architectures that are applicable to Intelligence Transportation Systems (ITS) must be designed by considering this regard. Task offloading is a well-known approach in various ITS applications. Task offloading in edge computing refers to the process of transferring certain computing tasks or workloads from a local device to edge nodes or servers located closer to the device. Orchestrating workload in an environment where both the task generator and destination device can be mobile is challenging while it is crucial for VRUs' safety. |
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