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Future vehicles will be increasingly connected to enable new applications and improve safety, traffic efficiency and comfort, through the use of several wireless access technologies, ranging from vehicle-to-everything (V2X) connectivity to automotive radar sensing and Internet of Things (IoT) technologies for intra-car wireless sensor networks. These technologies span the radiofrequency (RF) range, from a few hundred MHz as in intra-car network of sensors to hundreds of GHz as in automotive radars used for in-vehicle occupant detection and advanced driver assistance systems. Vehicle occupants and road users in the vicinity of the connected vehicle are thus daily immersed in a multi-source and multi-band electromagnetic field (EMF) generated by such technologies. This paper is the first comprehensive and specific survey about EMF exposure generated by the whole ensemble of connectivity technologies in cars. For each technology we describe the main characteristics, relevant standards, the application domain, and the typical deployment in modern cars. We then extensively describe the EMF exposure scenarios resulting from such technologies by resuming and comparing the outcomes from past studies on the exposure in the car. Results from past studies suggested that in no case EMF exposure was above the safe limits for the general population. Finally, open challenges for a more realistic characterization of the EMF exposure scenario in the connected car are discussed.

Recently, 3GPP has added new features to long term evolution (LTE) that allow vehicles to communicate directly with each other and with surrounding objects. These short-range communications will play a key role in the so-called cellular vehicle-to-anything (C-V2X). As a particular service, which will be the basis of most applications for automated and connected cars, each vehicle will periodically broadcast information on its identity, status, and movements through short-range vehicle-to-vehicle (V2V) communications. Given the importance of this service, great attention has been given to the associated resource allocation procedures and the number of vehicles that can be simultaneously communicating in the network. However, little attention has been paid to handling messages of different sizes, which is actually foreseen in practice in order to transmit static information with a reduced periodicity. With this in mind, we evaluate the number of vehicles that can be allocated when parameters are optimized for messages of different sizes. This objective is pursued taking into account the numerous constraints imposed by the standard, through the formalization and solution of a combinatorial optimization problem. Example results, based on 3GPP indications, show that, with respect to the optimization of the allocation based on the larger packets, it is possible to obtain an increase that varies between 10% and 30%, depending on the conditions, with peaks above 150% in specific cases.

In the latest years, 3GPP has added short-range cellular-vehicle-to-anything (C-V2X) to the features of LTE and 5G to allow vehicles, roadside devices, and vulnerable users to directly exchange information using the same chipset as for classical long-range connections. C-V2X is based on the use of advanced physical layer techniques and orthogonal resources, and one of the main aspects affecting its performance is the way resources are allocated. Allocations can be either managed by the network or in a distributed way, directly by the nodes. The latter case, called Mode 4, is required in those situations where the network cannot be involved in the scheduling process, for example, due to a lack of coverage, but could also be adopted in order to reduce the processing burden of eNodeB. An algorithm, defined in the standards, makes nodes sense the medium, and identify the best time-frequency combination to allocate their messages. Focusing on C-V2X Mode 4, in this paper, we analyze the parameters of the algorithm designed by 3GPP and their impact on the system performance. Through simulations in different large-scale scenarios, we show that modifying some parameters have negligible effect, that the proper choice of others can indeed improve the quality of service, and that a group of parameters allows to tradeoff reliability with update delay. The provided results can also be exploited to guide the future work.