# Intelligent Total Transportation Management System for Future Smart Cities
## 5 Conclusions  
This study presents an intelligent total transportation management system for future smart cities. Such a system uses the IoT to integrate vehicles with infrastructure, to apply big data survey of demands, to apply required sub-model developments for safe and optimized transport management, and to implement highly automated total management. The urban total transportation system may include very different transportation vehicles and solutions, such as users, service providers, transport managing, infrastructure, nature/built environments, regulations, competence and knowledge centers, supporting sub-systems and passive and active interactions with other essential systems. By introducing the autonomous vehicles in the everyday operations and reaching a highly automated traffic management system, the operator roles will be shifted from active control to passive observation and, thus, only make active control in case of exceptional or emergency cases. This study presented the classification of the transportation segments which partly used a hierarchical concept, including passive or non-cooperating vehicles, semi-active or simple cooperating, active or cooperating, connecting vehicles, contract-based vehicles, priority transport, and supporting partners. A developed optimization method to solve the traffic optimization problem was also presented in this study. This approach can be applied to optimize the energy used by the vehicles during their operation from the departure till the arrival point. This research summarizes three essential sub-model developments, including (i) a new car-following model for traffic safety investigation, (ii) a drone formation to avoid obstacles in smart cities, and (iii) a total transportation managing system in smart cities. These sub-models can be applied as solutions for the intelligent total transportation management system operated as a single system. Although this study presented the intelligent total transportation management system for future smart cities, the development of the concept, the methodology, and the required sub-model, more details and justifications must be provided, especially on the limitations holding back the rapid utilization of this methodology. Seeing this, four classes of limitations could be defined:  
* constraints supporting the solving of the optimization problem (1) even in the case of using a simple and understandable constraint such as a door-door speed for moderate traveling distance, the constraint depends, e.g., on the size of the city, social habits, economic developments. Thus, the constraints must be adapted to the given system
* system composition--the ratio of non-cooperative vehicles, a lack of sensing sub-system, and insufficiency in supporting systems like energy support or the information on parking vehicles
* acceptance by the stakeholders--legal control, acceptance of high-level automation, acceptance of control and commands from the operational centers, and acceptance of operating conditions like the delivery of product to shops at night time
* requirements in further developments--as possible dynamic optimization depending on the real transportation, size, intensity, and disasters or developing a special artificial intelligent classification of the non-cooperative vehicles  
The solution to these problems caused by the limitations might generalize the proposed intelligent total transportation management. The intelligent total transportation management introduced in this paper can be implemented in the described form, while it needs further studies and developments to increase its effectiveness.