Future vehicles will be very different from today's vehicles. Much of the change will be done using the IoT. The world will be very connected, sensors will be able to access data that most of us did not even know existed. More data also means more problems. Enormous amounts of data will be generated and distributed by the future's IoT devices, and this data needs to be analyzed and stored efficiently using Big data Principles. Fog computing is a development of Cloud technology that is suggested as a solution to many of the problems IoT suffer from. Are traditional storage and analysis tools sufficient for the huge volume of data that will be produced or are new technologies needed to support development?
This study will try to answer the question: "What problems and opportunities does the development of Fog computing in passenger cars have for consumers?" The question is answered by a systematic literature study. The objective of the systematic literature study is to identify and interpret previous literature and research. Analysis of the material has been done by using open coding where coding has been used to sort and categorize data. Results show that technologies like IoT, Big data and Fog computing are very integrated in each other. In the future vehicles there will be a lot of IoT devices that produce huge amounts of data. Fog computing will be an effective solution for managing the amount of data from IoT devices with a low latency. The possibilities will create new applications and systems that help improve traffic safety, the environment and information about the car's state and condition. There are several risks and problems that need to be resolved before a full-scale version can be used, such as data authentication, user integrity, and deciding on the most efficient mobility model.