With rising interest in autonomous vehicles, developing radio access technologies (RATs) that enable reliable and low latency vehicular communications has become of paramount importance. Dedicated Short Range Communications (DSRC) and Cellular V2X (C-V2X) are two present-day technologies that are capable of supporting day-1 vehicular applications. However, these RATs fall short of supporting communication requirements of many advanced vehicular applications, which are believed to be critical in enabling fully autonomous vehicles. Both DSRC and C-V2X are undergoing extensive enhancements in order to support advanced vehicular applications that are characterized by high reliability, low latency and high throughput requirements. These RAT evolutions-IEEE 802.11bd for DSRC and NR V2X for C-V2X-can supplement today's vehicular sensors in enabling autonomous driving. In this paper, we briefly describe the two present-day vehicular RATs. In doing so, we highlight their inability to guarantee quality of service requirements of many advanced vehicular applications. We then look at the two RAT evolutions, i.e., IEEE 802.11bd and NR V2X and outline their objectives, describe their salient features and provide an in-depth description of key mechanisms that enable these features. While both, IEEE 802.11bd and NR V2X, are in their initial stages of development, we shed light on their preliminary performance projections and compare and contrast the two evolutionary RATs with their respective predecessors.

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Vehicle-to-Vehicle (V2V) communication networks enable safety applications via periodic broadcast of Basic Safety Messages (BSMs) or safety beacons. Beacons include time-critical information such as sender vehicle's location, speed and direction. The vehicle density may be very high in certain scenarios and such V2V networks suffer from channel congestion and undesirable level of packet collisions; which in turn may seriously jeopardize safety application reliability and cause collision risky situations. In this work, we perform experimental analysis of safety application reliability (in terms of collision risks), and conclude that there exists a unique beacon rate for which the safety performance is maximized, and the optimal beacon rate is unique for varying vehicle densities. The collision risk of a certain vehicle is computed using a simple kinematics-based model, and is based on tracking error, defined as the difference between vehicle's actual position and the perceived location of that vehicle by its neighbors (via most-recent beacons). Furthermore, we analyze the interconnection between the collision risk and two well-known network performance metrics, Age of Information (AoI) and throughput. Our experimentation shows that AoI has a strong correlation with the collision risk and AoI-optimal beacon rate is similar to the safety-optimal beacon rate, irrespective of the vehicle densities, queuing sizes and disciplines. Whereas throughput works well only under higher vehicle densities.

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