# Evaluating the Feasibility of Intelligent Blind Road Junction V2I Deployments
###### Abstract
In general, studies have shown that C-V2X can uphold QoS metrics [14, 15, 16, 17] to support more basic V2X communications use cases outlined by the 3 GPP [8, 18], such as traffic information, traffic flow management, infotainment and eCommerce services. Certain works specifically address the teleoperation type use case [14, 16, 19], often within the context of commercial cellular networks. The consensus among these investigations is that achieving an advanced use case like teleoperation is viable under ideal circumstances; however, challenges relating to cell coverage, handover performance, and congestion management pose significant obstacles, reducing feasibility considerably. These findings from studies in commercial cellular networks are further reinforced by those completed with private cellular networks. Several works demonstrate that in controlled scenarios LTE-V2X could uphold QoS metrics for advanced V2X use cases [20, 21]. Recent works studying NR-V2X and its enhancements [22, 23, 24, 25], also within private cellular networks, have shown very promising performance for the technology's capacity as a candidate wireless access technology for V2X communications. While C-V2X has significant potential as a V2X communications candidate, it is clear from previous studies that it is not yet ready to be deployed at scale for advanced use cases, such as teleoperation, due to the challenges associated with reliability in terms of upholding QoS metrics. Given these challenges associated with deployment at scale, it is reasonable to initially begin with developing V2X communications, both in technology and commerce, with smaller-scale implementations that have the most significant potential impact. Implementations of this calibre can benefit from a more predictable wireless channel and can be deployed in locations with existing infrastructure. As such, if conducted correctly, smaller-scale implementations can be used to focus on considerations for developing sufficient QoS for V2X communications applications and use cases at a larger scale. One such application that fits these criteria is that of the blind road junction or blind corner, wherein the view of significant portions of a junction or road is occluded by static obstructions. In automotive environments, these blind road junctions and blind corners represent a cohort of particularly hazardous scenarios that an intelligent vehicle must contend with. Convex mirrors [26] are often placed at these locations (see Figure 1) to allow drivers to see around the occlusions that render the junctions and corners blind. However, given the difficulty of detecting objects in the convex mirror itself [27, 28], the safety of these locations can likely be improved by the introduction of fixed sensors with V2I communications capabilities [29], also known as a Fixed Sensor Node (FSN), shown in Figure 2.  
Hazardous automotive scenarios such as occluded or blind road junctions have been considered by the research community for many years [30]. However, most of the research focuses on the motion planning aspect of navigating these scenarios. Some studies exclusively rely on the intelligent vehicle's own capabilities to safely navigate the hazardous scenario [31]. [PERSON] et al. [32] present a reinforcement learning algorithm trained on human data to determine how the intelligent vehicle should behave, whereas [PERSON] et al. [33] propose the use of mmWave radar with reflectors installed at the junction to allow the intelligent vehicle to see around corners. Other works take into consideration the use of external sensors via V2I communications to inform the motion planning of the intelligent vehicle [34, 35]. Fewer works address the communications perspective of this occluded  
Figure 1: Blind T-junction scenario with occlusions caused by foliage near the roadside. The occluded vehicle on the major road is revealed for the ego vehicle (red vehicle) by the convex mirror (red ellipse).