Analysis of collaborative wireless vehicular technologies under realistic conditions

Abstract

Reliable communications are essential to provide intelligent services to connected cars. For operational services, connected vehicles in VANET (Vehicle Ad hoc Networks) regularly transfer large amounts of data related to vehicular safety. Similarly, V2X (Vehicle-to-Everything) communications include vehicles exchanging information with each other and with infrastructure that is, Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V). This paper has analyzed the performance of IEEE 802.11p and 5G test network in a collaborative manner under realistic conditions. For performance analysis the exchange of safety-critical road weather and traffic information has been performed to enhance the traffic safety and traffic efficiency in the domain of intelligent transportation system (ITS). The vehicular connectivity is provided in V2V and V2I scenarios by utilizing short-range IEEE 802.11 standard or cellular approaches, such as the 5G network. Here, we consider combining these technologies in a cooperative manner to exploit jointly their advantages. In this cooperative heterogeneous network, the IEEE 802.11p supports safety-related pilot use cases while the provision of non-safety-related pilot use cases are supported by the 5G test network. The performance analysis revealed that the IEEE 802.11p performs quite reasonably well with restricted mobility in contrast of 5G test network in a collaborative manner to avoid road accidents.

Connected Vehicles: V2V and V2I Road Weather and Traffic Communication Using Cellular Technologies

“…Table 3 together with Figure 7 and Figure 8 reveal that during the start of the test measurements, there were more packet losses which ultimately led to an increase in network latency. However, as a whole, the LTE and 5GTN performances were satisfactory for fulfilling the minimum requirements to deliver the safety messages in the V2V and V2I scenarios (<100 ms) [ 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ].…”

“…State-of-the-art devices and sensors were used in the field measurements including a Teconer WCM 411 and a Teconer RCM 411 (i.e., vehicles); RWS sensors included the Vaisala PWD-22, DSC-111, Zavio B-7210 FHD camera, and the 2D Ultrasonic Anemometer. The telematics data from the vehicles’ CAN buses were also used for informational content about the vehicles [ 21 , 22 , 23 , 24 ]. The used sensors and collected data are presented in Table 2 , and some of the IoT sensors (weather sensors, visibility sensors, road state sensors) were installed on the test track with the RWS, which are also illustrated in Figure 5 .…”

Effect of Waiting Time and Number of Slots on Vehicular Networking Employing Slotted ALOHA Protocol

“…Figs. [2][3][4][5][6][7][8][9][10][11] show the relationship between the delivered numbers of frames as a function of waiting time, with N=20000. Figure . 12 Relationship between maximum successfully transmitted frames and waiting time Fig.…”

“…Vehicular networks and vehicular communication is an effective contributor to improve road safety and traffic management efficiency [1][2][3]. It is an important component of intelligent transportation systems (ITS), which embodies many applications such as intelligent driving, emergency message and basic safety message (BSM) transmission assistance.…”

Vulnerable Road Users and Connected Autonomous Vehicles Interaction: A Survey

“…In this context, packet delivery ratio, bit error rate, delay and connection duration have been analyzed in [20]. Some authors have discussed architectural issues and wireless technologies that support inter-vehicular communication, discussing outstanding challenges for enabling the deployment and adoption of inter-vehicular communication technology and how to combine these technologies in a cooperative way to exploit the advantages and cover the limitations of each of them [21][22][23][24].…”