## 1 Introduction  
The automotive industry is undergoing a revolution, driven by the advances in information and communication technologies and microelectronics, towards the deployment of intelligent transportation systems [1; 2]. Vehicular ad hoc networks (VANETs) are highly dynamic and self-organizing networks, formed by vehicles equipped with on-board units (OBUs) for direct short-range communications (DSRC) with other vehicles and roadside units (RSUs) [3]. DSRC standards were recently adopted by the European Parliament--to the detriment of the alternative model of cellular vehicle-to-everything (C-V2X) [4]--to enable specific solutions for increased road safety, traffic efficiency, driving assistance, crowdsensing, infotainment, and many others [5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17]. Managing the information required by these new services often goes beyond the capabilities and/or the incumbency of individual vehicles, e.g., because the amount of data exceeds the memory and CPU power of the OBUs, because a peer-to-peer model is not suitable for a given task, or due to privacy concerns. For example, in dealing with traffic accidents, insurance companies use as much information as possible about the circumstances to determine responsibilities and execute the contracts. Thus, they are interested in gathering telemetry data sensed by nearby nodes in the VANET, which they can consolidate and analyze in the cloud, and thereupon make the decision of whether to pay for the damages [18]. In general, it is necessary to create solutions in which the vehicles can collaborate to effectively augment their capabilities, by sharing processing/storage/sensing resources with other vehicles and establishing reliable communication paths to fixed RSUs, which may act as gateways to the Internet [19; 20] or carry out some processing in an _edge computing_ fashion [21; 22]. For the new services to work properly, it is necessary to address two challenges inherent to the vehicular environment: the instability of the communication links and the trustworthiness of the data generated/provided by the vehicles [23]. On the one hand, the rapid mobility and the variations of vehicle density lead to breakages of the communication links between pairs of vehicles, affecting any multi-hop communication paths established through them [19; 24]. On the other hand, due to the nature and sensitivity of the information exchanged in some services (e.g., geographic locations, license plates or any other form of identity, etc. ), there must be ways to prevent or hamper malicious behavior, dealing at least with data integrity and traceability, and assessing the reliability of the data sources according to consensus and reputation mechanisms [25; 26; 27; 28]. The notions of information quality and criticality described in [29] emerge, too, in order to quantify the importance level of the information that each source may contribute. In this paper, we present a framework that enables the desired VANET services by combining two technologies:  
* First, a virtualization layer sits on top of the TCP/IP protocol stack to have the vehicles emulate a reliable network of static virtual nodes for the communications. In particular, we use the VaNetLayer system [30], which has been shown to improve the performance of VANET communications in simulations of urban scenarios [31]. * Second, blockchain technology is used to enable features of data integrity, traceability, and reliability that cannot be furnished by the consensus and reputation mechanisms that have shown up in the literature of VANETs in recent years. Specifically, we adopt the principles of Ethereum because its widely supported implementation of _smart contracts_ provides suitable means for the definition of a range of service conditions. In our framework, called the VaNetChain, the entwining of these technologies turns the RSUs into entities responsible for executing an improved consensus and validation protocol.