Index-Based Mode Adjustment for Energy Saving of Service Vehicles and Robots in Vehicular Networks

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.