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Affiliation of Author(s):School of Computer Science and Information Engineering, Hefei University of Technology
Journal:2023 9th International Conference on Computer and Communications
Funded by:National Natural Science Foundation of China with Grants 62371180, 61971176 and 62171474，National Ke
Key Words:Vehicular networks, pedestrian flow, time series prediction, service mode adjustment, energy-saving
Abstract: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.
Co-author:Lusheng Wang,Caihong Kai,Min Peng
First Author:Degao Yan
Indexed by:Essay collection
Discipline:Engineering
Document Type:C
Page Number:1279-1285
Translation or Not:no
Date of Publication:2023-12-08
Included Journals:EI