Vehicle2Vehicle (V2V) is an emerging and fruitful area of research widely investigated in IoT and in the driverless setting, in particular. It allows cars to establish ad-hoc networks to cooperate in order to share information and therefore improve the safety of the drivers. A fundamental aspect in V2V is the positioning accuracy. While in several outdoor scenarios modern Global Navigation Satellite Systems (GNSS) are sufficiently precise, they are less reliable in indoor situations. This is

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... esirable as often cars move from outdoor to indoor scenarios and vice versa (think for example to cars leaving a box, or entering a tunnel). For this reason large research effort has been recently devoted to integrate GNSS systems in order to improve indoor positioning accuracy. In this paper we present Vehicle-2-Vehicle Elastic Network, a novel metodology that allows accurate vehicular indoor positioning based on a dead-reckoning technique via an Indoor Inertial Navigation System, aided by an elastic graph generated by a V2V-WiFi system. The received signal strength (RSS) from nearby cars is detected, and is used to improve the location via RSS-to distance information crowdsourcing.