## 1 Introduction
The application of artificial intelligence techniques for the automatic management of the actuators ofthe vehicle enables driver assistance systems and autonomous driving systems to perform management in a similar way to human drivers while improving safety and comfort [32]. Some obstacle identification-based collision avoidance applications which fall within the pre-collision systems group are the ones presented in [20,33] to avoid accidents with pedestrians, and the theoretical proposal in [34] for overtaking slow-moving vehicles. On the other hand, it is clear that the information retrieved by a vehicle provided only by its local sensors should be enough to prevent near accidents or to reduce the effects of a certain accident. However, new vehicle applications require additional information on the moving traffic environment from the other vehicles as well as from the infrastructure. This means that an external source of information is necessary in the vehicle itself in order to provide the necessary information to guarantee a proper performance of these assistance systems [35]. Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications cover the gap of providing information to the Advanced Driver Assistance Systems (ADAS) from the surroundings of a vehicle [22]. Thus, a distinction is made between two generations of systems: autonomous systems and cooperative systems (vehicle-to-vehicle communications) [36]. The former are based on sensors and intravehicle communications. Cooperative systems are ones that are based on communications and an information exchange between vehicles or between vehicles and the infrastructure. This information enables the horizon that can be \"seen\" to be broadened so that actions can be taken [37]. The main qualitative leap between the autonomous vehicle and the connected vehicle in a cooperative environment lies in the fact that, apart from its possessing its own data and perceiving its surroundings through onboard sensors, it can receive information from other vehicles, from the infrastructure or traffic control centres. In addition, the said vehicle could, at the same time, be a source of information that could be transmitted to the outside. In this way, two-way communications are established. The potential for communications in the field of transport has become firmly established with the setting up of ambitious research programmes throughout the world, such as the European eSafety initiative, European projects such as CVIS, SAFESPOT and COOPERS, the American programmes derived from the Intelligent Vehicle Initiative and the Japanese InternetITS and Advanced Highway Systems (AHS) programmes [38]. The ongoing research and development work usually falls within one of the two groups. However, there are very few applications that encompass both aspects. The work presented in this paper is motivated by the fact that if we combine vehicles equipped with sensors and non-instrumented ones, we can generate cooperative perception systems that may extend the range of applicability of the standalone ADAS. We present an autonomous collision avoidance system, extended to other vehicles through vehicular wireless communications in order to perform cooperative perception. This ADAS perceives the environment of a leading automated car using a laser scanner and transmits the perception information to a tailing car using a Vehicular Mesh Wireless Sensor Network (WSN), whose communication technology has been specifically designed to behave as a Mesh Network, following IEEE 802.15.4 standard. This system has been designed, implemented and tested using real vehicles in the facilities of the University Institute for Automobile Research (INSIA) of the Technical University of Madrid.