## 1 Introduction  
The report of the United Nations (\"Our Common Future\") defined sustainable development in 1987 as \"development that meets the needs of the present without compromising the ability of future generations to meet their own needs\" [1]. Our transport systems should also adopt this approach. In the light of this, our transport systems should be designed not only to meet the needs of the present, but also, where possible, to meet the needs of the future. This appears to be particularly challenging in areas where technology and societal expectations are in such a state of flux and rapid evolution that we can only estimate future needs with a high degree of variance. In such cases, we must try to ensure that the system has the flexibility to adapt easily to needs that may not be known today, or that may be able to be met with little effort, cost or loss. Based on [PERSON]'s definition [2], in self-organising transport, users and providers communicate in a peer-to-peer way, avoiding the negative effect of a third party acting as a coordinator. Of course, some services still need to be centrally organised (such as trip planning, car sharing, ride sharing, etc.). For those services where the coordinating actor needs to have a more detailed knowledge of the available information (such as the network, available vehicle types, etc. ), the role of the central components cannot be questioned. However, when mobility patterns (especially demand and supply) cannot be reliably estimated, centralised systems quickly reach their limits in providing a real-time dynamic representation of the real-world processes and in operating in an automated mode. In this case, self-organising networks can operate more efficiently [2]. So, we can see that the flexibility and adaptability of systems can be significantly improved if we take self-organising transport systems into account in the design. However,by basic definition, they differ from traditional public transport systems mainly in the relationship between user and provider. And this is where this article aims to contribute to the development of methodological tools in the field. It can be assumed that under certain circumstances and to a certain extent, in the case of an autonomous or highly automated transport system, the transport infrastructure can be considered as an adaptive actor among the other components that make up the transport system (e.g., the user or the service provider). But how can transport infrastructure adapt to changing needs? New access roads can be added to a core network element, new legs can be added to an intersection to meet demand, or a motorway lane can be removed to allow trees to grow quickly in its place when traffic is low. Unfortunately, as science stands today, we are not there yet. But it is no longer science fiction to allocate a lane to different directions throughout the day, depending on changing demand. Reflecting further on this example, we can find effective solutions by treating traffic engineering not as a static tool, but as a dynamic system that can adapt to changing needs. The highest level of flexibility, considering the dynamic nature of traffic engineering, would be achieved if traffic engineering could be instantly adapted to current needs. This can be illustrated with abstract examples such as a lane closure that suddenly disappears during a lane change manoeuvre, or a roundabout that opens to let a vehicle through on the opposite leg. Even if we do not want to give such abstract examples, we would like to explore how we can make our transport system more flexible by reconsidering the spatial representation models and improving their adaptability. The main contributions of our paper were highlighted in Section 2. In Section 3, the related literature is reviewed, focusing on the representation methods of transport network in highly automated transport systems.