## 4 Discussion  
As global trends in the transport industry focus on integrating more software into the products and using advanced computing power and equipment to evolve and optimize the basic concepts of functioning, the autonomous vehicle sector continues to grow further. Connected autonomous vehicles are showing up in various private and public applications, leading the way to more advanced and interconnected road networks. The work carried out now by emerging vehicles is paving the road to a future in which an increasing number of vehicle roles are taken over by autonomous cars (e.g., door-to-door delivery, cargo transport, people public transport, etc.). In fixed route scenarios, such as the ones considered in this paper, the deployment of autonomous vehicles proves to be beneficial in reducing the running costs of shuttle and bus services by eliminating the cost of the driver and exploiting the powertrains and vehicles as a whole in an optimized and safe manner. In 2021, [PERSON] et al. have analyzed the techno-economic implications of autonomous and electric shuttles, concluding that the economic savings of autonomous fleets are directly linked to the size of the shuttles, ranging from 72% for small vehicles down to 35% for extra-large examples [32]. One of the basic purposes of CAVs is to revolutionize the way we think about transport and optimize each sector and possible application. For a large number of those scenarios, MAVs are a feasible solution that needs to be explored in more detail. As large manufacturers express interest in self-driving and interconnected vehicles, it is just a matter of time for Modular Autonomous Vehicles to become more popular and used on a larger scale. Being a relatively new topic in the industry, the last two decades have opened the doors for rapid development in this area, as technology is more advanced and accessible than ever before. Benefiting from this accessibility are also the smaller companies or start-ups, which can pitch innovative ideas and concepts, leading to faster validation and implementation of the most fitting solutions. Considering the obtained data from the above-presented simulation actions and analysis, the below points can be considered for further research and studies on specific cases of MAV applications in existing public transport networks, but also in newly developed systems that can accommodate more easily the necessities and benefits of such vehicles:  
* The basic concept of using multiple modules with the combined capacity of an existing bus leads to a more efficient way of transporting passengers, as the capacity of the vehicles is used in an optimal way, considering the live demand of the network and external factors as well. Reducing times in which vehicles are riding empty is key to reducing the energy consumption of an entire fleet. * The study identified that weight distribution has a significant impact on energy consumption, with a front-weighted distribution using less energy than a rear-weighted configuration. When the weight was evenly distributed in the middle of each vehicle, the most advantageous scenario was noticed. It is important to note, however, that these findings may vary depending on traffic conditions and the placement of heavy components such as the battery pack or electric motor. Furthermore, weight distribution was discovered to influence parameters such as acceleration, braking, and cornering performance, emphasizing the interconnected nature of these variables. * Although the current results show impressive progress, there is still a promising opportunity for further improvement: the incorporation of independent electric motors in each wheel. This methodology shows potential for enhancing the efficiency, accuracy, and management of self-driving vehicles. The utilization of an individual motor in every wheel enhances the system's agility and response, leading to improved vehicle dynamics and efficiency while simultaneously reducing energy waste.