Human-Computer Interaction in IoT-driven Autonomous Vehicle Environments

Abstract

The environment has been designed to receive various signals and information conducted with different technologies such as Long-term evolution (LTE), ZigBee, Vehicular Ad-hoc Network (VANET), WLAN (IEEE 802.11a/g), Google Glass, Android-based tablet, and Car Multimedia. The information received by AVN is processed by a novel application of Avatar–Environment Interaction (AEI) protocol [1]. The experimental results revealed that jointly utilizing connected autonomous vehicles (CAVs) and non-authonomous vehicles (NAVs) signals would enhance road safety by improving navigation in a traffic scenario through applications download-based security threats, telephony and networking threats, three-dimensional printing threats, cloud-to-vehicle (C2V) communication threats, denial of service (DoS) and distributed Denial of Service (DDoS).

Various modern technologies have been incorporated in IoT-driven autonomous vehicle environments, leading to their operation becoming almost effortless [2]. These technologies yield efficient human-computer interaction (HCI) systems capable of making navigation through IoT-driven autonomous vehicle environments user friendly. The design of HCI systems calls for technologies requiring low computational resources for their implementation, for real-time response in signal communication between autonomous vehicles (AVs) and non-autonomous vehicles (NAVS), and last but not least for cost-effectiveness to be affordable for civilians. The design of the IoT-driven autonomous vehicle environments is accomplished by applying many technologies required to perform sensing, communication, decision-making, and actuation tasks.