Abstract
Unmanned ground vehicles (UGVs) are becoming the foremost part of rescue teams for protecting human lives from severe disasters and reducing human casualties by informing them about the risks ahead, such as mine detection and clearance. In mine detection, a centralized system is required so that the UGVs can communicate with each other efficiently to disseminate the mine detection messages (MDMs) to incoming vehicles of military and civilians. Therefore, in this piece of research, a novel unmanned ground and aerial vehicle (UGAV)-based mine-detection-vehicle routing (MDVR) protocol has been proposed, mainly for the mine detection and clearance teams using a vehicular ad hoc network (VANET). The protocol disseminates the MDMs using UGVs and unmanned aerial vehicles (UAVs) in combination to overcome the limitations of only inter-UGV communication. The proposed protocol performs cluster-based multicast communication in real time using UAVs so that the dynamic mobility of UGVs cannot affect the performance of MDM dissemination. Hence, the proposed scheme is adaptable because any failure in message delivery can cause a high level of destruction. The proposed cluster-based scheme can adapt to any real-time scenario by introducing the level-based cluster-head election scheme (LBCHE), which works concerning its assigned priority for reducing the delay incurred in MDMs dissemination. The simulation of the proposed protocol in the network simulator (NS) shows that the overhead and delay are reduced in MDMs dissemination. At the same time, the throughput, packet delivery ratio, and stability increased compared to the other competing protocols.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference63 articles.
1. Intelligent optimization for charging scheduling of electric vehicle using exponential Harris Hawks technique;Int. J. Intell. Syst.,2021
2. A novel intelligent transport system charging scheduling for electric vehicles using Grey Wolf Optimizer and Sail Fish Optimization algorithms;Energy Sources Part A Recover. Util. Environ. Eff.,2022
3. Rawashdeh, N.A., and Jasim, H.T. (2013, January 9–11). Multi-sensor input path planning for an autonomous ground vehicle. Proceedings of the 2013 9th International Symposium on Mechatronics and its Applications (ISMA), Amman, Jordan.
4. Scheidt, D., Stipes, J., and Neighoff, T. (2004, January 20–22). Cooperating unmanned vehicles. Proceedings of the AIAA 1st Intelligent Systems Technical Conference, Chicago, IL, USA.
5. Speed and Position Aware Dynamic Routing for Emergency Message Dissemination in VANETs;IEEE Access,2022
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献