# Smart Mobility and Aspects of Vehicle-to-Infrastructure: A Data Viewpoint
## 5 HD Maps
### Network Occupancy of Updating HD Maps  
In the section \"Introduction\", we showed estimates of data difficulty for vehicles of lower and medium levels of autonomy. The estimated information consisted of statistics from the United States of America. The AECC has produced its own estimates, including the processing and updating of HD maps, which they consider to be a key aspect of autonomous management. Certain constants, such as the total length of journeys and the number of illegally parked vehicles are obtained from Tokyo.  
The individual indicators that are included in the calculation of the estimate of the total amount of data transferred according to pattern B are:  
* Data Upload/Download Frequency--A frequency defined as the number of detected changes in the Transient Dynamic Layer and HD map updates.
* Upload/Download Data Volume (per vehicle system)--represents the total amount of data transferred between the vehicle and MSP Edge/Cloud Server.
* Upload/Download Data Volume (in total)--represents the total amount of transmitted data, categorized according to the number and type of connected vehicle.
* Latency--Latency is defined as the time it takes to transfer information from the sensor to update the HD map [28].  
The estimate includes two types of vehicles--Economy Model Cars and Mid-range Model Cars. Economy Cars are vehicles that are commonly available and contain several cameras and radars. Mid-range vehicles have more sensors than the Economy model (for example LiDAR).  
The calculated data are categorized based on the number of Economy Model Cars (EMC) and Mid-range Model Cars (MRMC), where they focus on the total amount of data transmitted from the Upload/Download perspective, as in Figure 10. On the left side, we can see the total amount of data sent to the MSP Edge/Central Server, where the estimated generated data by 2022 represents a value of approximately 10.8 Petabytes per day. In terms of data received, it is 123 Terabytes per day. The idea of generating data in the next ten years is about 1/10 of the total data production of the world's population, which is growing every year, and the latest estimates show that this value will increase rapidly [29].  
Figure 10: The calculated amount of transferred data based on [28].  
These values already show a significant amount of data for transmission as well as processing for the various car manufacturers involved in advancing autonomous driving. The challenge for transport leaders as well as the professional community is to achieve reliability and meet the required hardware need to store the necessary data in the vehicle. However, we already know that traditional database systems such as relational databases and data processing in data warehouses, as well as data storage and analysis in these systems, are not sufficient [29]. Likewise, it is questionable whether systems (Hadoop, NoSQL, MapReduce and others), which are designed to process Big Data, are sufficient for storing, processing and transmitting data depending on efficiency and time.  
Those estimates and the calculated constants are an integral part of autonomous vehicles. However, for autonomous vehicles to be integrated into road infrastructure, they need to be able to communicate with infrastructure as well as other V2X communication stakeholders. It should not be forgotten that it is necessary to design and implement the most suitable way of storing and transmitting information together with the analyzed estimates with sensors and information about HD maps. This means that the total amount of data transferred and processed will increase even more, and the need to know how to process Big Data in real time will increase even more. We have also failed to include the division of data into structured and unstructured, where the mentioned values in unstructured similarly require enormous computing power and sophisticated processing, for the purpose of deciding an autonomous vehicle on which the overall future of autonomous shared driving will depend in the Smart Mobility concept.