A simulator for connected car scenarios

Abstract

Internet of Things (IoT) is utilized in various industries to deal with problems and provide new features to customers. In addition, there is a trend that most devices are evolving into entities that have communication capacities. Mobility is a prominent aspect of our lives and industry, universities and companies in the automotive field keep in step with the trend. Internet of Vehicles (IoV) can be basically defined as a network of smart cars that are connected to other vehicles and infrastructure [STM18]. In this concept, vehicles gather various data internally and from the environment, refine the data and share it. Besides, data transmission among vehicles is a fundamental component of autonomous driving. Data flow steps of the Internet of Vehicles should be designed to create this kind of complex system. A digital twin is a substantial segment of the system. It is a digital replica of a thing or system that regularly communicates with the physical world and manipulates the actions of the physical part. The data loop specifies the data flow steps which are obtaining data, processing, and forwarding it to a digital twin and then back to the vehicle. The development of such an immense system, which has cyber and physical parts, on real vehicles is costly and arduous regarding testing. This master thesis aims to conceptualize and implement a simulator that provides a data generator for connected car scenarios and imitates the data loop. The generation of synthetic vehicle data is another objective of the thesis. A connected car simulator grounds existing vehicle simulators and technologies. It extends a suited simulation tool (MetaDrive) for creating Internet of Vehicle scenarios.