AbstrAct5G technologies present a new paradigm to provide connectivity to vehicles, in support of high data-rate services, complementing existing inter-vehicle communication standards based on IEEE 802.11p. As we argue, the specific signal characteristics of 5G communication turn out to be highly conducive for vehicle positioning. Hence, 5G can work in synergy with existing on-vehicle positioning and mapping systems to provide redundancy for certain applications, in particular automated driving. This article provides an overview of the evolution of cellular positioning and discusses the key properties of 5G as they relate to vehicular positioning. Open research challenges are presented.
requirements for VehiculAr PositioningWith the increase of automated driving in various forms (highway assistance driving, automatic cruise control, self-parking, up to fully autonomous driving) comes a need for precise positioning information. Positioning of vehicles is achieved through a variety of technologies, as illustrated in Fig. 1, including global navigation satellite-based systems (GNSS), radar, mono and stereo cameras, and laser scanners (lidar), which are fused to give the vehicle an understanding of the environment and its location within this environment. The environment is encoded through a map, which is either stored offline or computed online. The process of learning the environment and building detailed maps using onboard sensors is known as mapping. Different positioning applications have different requirements, which are expressed in terms of accuracy, latency, reliability, and cost. On one hand, standard vehicular navigation applications require only a few meters of absolute positioning accuracy, second-level latency, and low reliability (frequent outages are tolerable), but must rely on low-cost sensors. On the other hand, the safety-critical application of autonomous driving will require centimeter-level absolute and relative positioning accuracy, latencies on the order of tens of milliseconds, and high reliability, but can rely on a more expensive suite of sensors. An overview of the accuracy requirements for several key applications is shown in Table 1.GNSS, which has been the workhorse for vehicular absolute positioning in military, professional, and personal navigation, leads to uncertainties on the order of a few meters. Complemented by dedicated base stations, real-time kinematic GNSS further improves the accuracy down to the centimeter level. However, GNSS fails to work in certain common conditions, such as under tree canopies, in the presence of GNSS jammers, and in dense urban environments, due to the blocking of GNSS signals by buildings. Moreover, GNSS is limited by significant latency and low refresh rate, which are key requirements for guaranteeing safety.For relative positioning, onboard sensors such as cameras, radars, and lidars can generally operate well under these GNSS-challenged conditions, and provide very precise information. However, these sensors are costly in terms of computational ...