# Toward Collaborative Intelligence in IoV Systems: Recent Advances and Open Issues
## 1 Introduction  
As the fourth industrial revolution, industry 4.0 has started an important development stage and academia, industry and management departments are making efforts to realize the intelligent ecology of industry 4.0 [1, 2]. As a necessary foundation of industry 4.0 and key use cases such as smart city and smart industry, Internet of Things (IoT) realizes the intelligent perception, recognition and management of objects and processes through the connection between things and things, and people and things. In recent years, Intelligent Transportation System (ITS) and Intelligent Vehicles (IV) are the research hotspots of many researchers and technology companies. As the most important application fields of the IoT, IoV is an essential key technology for the next generation of ITS, and also one of the most important breakthroughs. The realization of IoV can significantly improve the smart city and the sustainable development of energy. For example, the traffic management system in the environment of IoV and vehicles with autonomous driving function can reduce traffic congestion, traffic accidents, and environmental pollution. Vehicles under the networking of an intelligent vehicle system can provide users with more comprehensive and personalized mobile travel service, such as path planning, service recommendation, and intelligent parking to provide a safe, comfortable, intelligent, and efficient driving experience and transportation services, improving the efficiency of transportation. At the same time, they promote an intelligent level of transportation service for society. Applications of IoV are listed in Figure 1. IoV is not only applied to urban traffic, but also has many applications; for instance, internet of underwater vehicles and internet of aerial vehicles. Drones are used in intelligent logistics, oil and gas equipment inspection, environmental and traffic monitoring, disaster recovery and more scenarios. IoV has attracted a large number of researchers and companies due to its great research value and commercial interests. However, the development of the IoV system still needs to overcome many challenges before it can play a big role because of the above characteristics. These challenges include the following. To turn the \"Internet of Everything\" into reality in the future, there will be more and more network devices and access environments, resulting in entity heterogeneity, dynamic, data diversity and big data challenges. At the same time, a variety of high-quality new applications, such as autonomous driving and automated delivery and other advanced services, require high network, storage, and computing resources. Therefore, to meet the network requirements of low delay, large bandwidth, secure, and efficient computing requirements of the next generation of IoV, efficiently utilizing the existing limited resources to design the IoV system is a major challenge. To address these challenges, resource-efficient task processing architecture must to be built while effectively utilizing the limited resources at all levels, such as perception, transmission, and application of IoV. All of these demands drive us to research how these various entities might work together to optimize communication, caching, and computing resources between heterogeneous agents. In the past few decades, AI has developed rapidly and has been successfully applied in many research and application fields. Currently, in the field of IoV, there are many studies showing great interest in AI and collaborative intelligence methods. Collaborative intelligence(CI), also known as cooperative intelligence, is able to aggregate the capabilities and intelligence of multiple devices to achieve a common goal and intent [3]. CI can bring AI to the edge, such as vehicles and roadside units. The lack of sensing, computing, and storage capabilities of edges and endpoints can be solved.