Index-Based Mode Adjustment for Energy Saving of Service Vehicles and Robots in Vehicular Networks
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所属单位：School of Computer Science and Information Engineering, Hefei University of Technology
发表刊物：2023 9th International Conference on Computer and Communications
项目来源：National Natural Science Foundation of China with Grants 62371180, 61971176 and 62171474，National Ke
关键字：Vehicular networks, pedestrian flow, time series prediction, service mode adjustment, energy-saving
摘要：Vehicular networks with service robots and vehicles have been widely studied in the past few years, and a large number of these vehicles and robots may appear in people's lives, such as in science and technology park, university town, restaurant, and public transportation hub. Energy-saving in vehicular networks becomes a key issue in these scenarios for ensuring the endurance time of vehicles and robots, so it is useful to dynamically adjust their working modes based on the pedestrian flow density around them. In this paper, we predict the peaks and troughs of the pedestrian flow based on four technical indexes, and adjust between active and ordinary modes for the vehicles and robots to save their energy while still guaranteeing their services. Simulation results show that the used technical indexes can predict the peaks and troughs of a pedestrian flow, hence the proposal effectively reduces the energy consumption of the vehicular networks.
合写作者：Lusheng Wang,Caihong Kai,Min Peng
第一作者：Degao Yan
论文类型：论文集
学科门类：工学
文献类型：C
页面范围：1279-1285
是否译文：否
发表时间：2023-12-08
收录刊物：EI