# Steady-Speed Traffic Capacity Analysis for Autonomous and Human-Driven Vehicles
## 6 Conclusions  
Extensive empirical testing was carried out at the ZalaZONE proving ground and in Gyor City Road Networks, in Hungary, to delve into the dynamics of both ACC-equipped vehicles and conventional human-driven counterparts, scrutinizing their longitudinal driving effects on traffic flow and capacities. The experiment aimed to comprehensively explore the nuances of both driving scenarios through employing three distinct categories of ACC systems across various levels of driving speed. While the results underscored the ACC system's ability to maintain more consistent car-following distances, thereby enhancing safety in comparison to human drivers, a notable downside emerged in terms of their adverse impact on road capacities. The results indicate a mitigation in capacity percentages of 7.6%, 9.3%, and 15.6% for the three types of ACC, respectively, in comparison to human drivers. This underscores the intricate dynamics involved in human decision making and adaptability, ultimately contributing to higher traffic capacities in real-world driving scenarios. However, this study focused on collecting data under favorable conditions and did not assess the performance of the vehicles under adverse conditions.  
In general, while ACC systems can contribute to smoother traffic flow under certain conditions, human drivers' adaptability and communication abilities may still provide advantages in handling complex and unpredictable situations. As we navigate the landscape of automated driving technologies, understanding and addressing these differences will be crucial for the successful integration of such systems into diverse traffic environments. In addition, enabling vehicles to communicate and collaborate with each other through the use of cooperative adaptive cruise control (CACC) will allow vehicles to travel in closer proximity, capitalizing on real-time data exchange to synchronize speeds and maintain a smoother, more efficient traffic flow. Ultimately, the integration of cooperative elements empowers CACC to outperform its predecessors, leading to increased road capacities and a more streamlined driving experience.  
Conceptualization, B.H. and D.M.; methodology, B.H.; formal analysis, D.M.; investigation, D.M. and B.H.; writing--original draft preparation, D.M.; writing--review and editing, B.H.; visualization, D.M.; All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the interests of those providing the location and conditions of the measurement.  
We hereby thank the kind help and support of the staff members of the Vehicle Research Center at Szechenyi Istvan University located at the ZalaZone proving ground and the staff members of the Department of Transport at Szechenyi Istvan University for helping to perform the human-driven measures.  
The authors declare no conflicts of interest.  
The following abbreviations are used in this manuscript:  
Acc Adaptive Cruise Control