# Research on Geometric Design Standards for Freeways under a Fully Autonomous Driving Environment
## 5 Discussion  
As a product of the development of Internet-of-vehicles technology, autonomous vehicles will change people's traditional concepts and methods of transportation. However, the current road design standards are formulated on the premise of manned driving, comprehensively considering various factors such as driver characteristics and vehicle characteristics. A driver's psychological and physiological factors will not be considered in the fully autonomous driving environment. This will inevitably lead to the phenomenon that the current design indicators are inconformity and uneconomical in the new driving environment. Therefore, the existing road geometric design standards need to be innovated to match the new requirements. Firstly, in this study, we examine how some design elements change in a fully autonomous driving environment. These design elements are the basis of road geometric design and are usually directly influenced by driver factors. Design speed is the most important indicator in freeway geometric design. Without the constraints of a driver, the design speed will be further improved. Sight distance is mainly affected by the driver's reaction time. With sensors replacing human eyes, autonomous vehicles can identify road conditions and make decisions faster. By analyzing and improving the sight distance calculation model, it is found that the sight distance demand for autonomous vehicles will \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Design Speed (km/h)** & **180** & **160** & **140** & **120** & **100** & **80** \\ \hline Width of right shoulder (m) & 3 & 3 & 3 & 1.5 & 1.5 & 1.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 18: Width of right shoulder in autonomous freeways (m). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Design Speed (km/h)** & **180** & **160** & **140** & **120** & **100** & **80** \\ \hline \multirow{2}{*}{Single Lane width (m)} & Small-sized vehicles & 3.75 & 3.5 & 3.5 & 3.5 & 3.5 & 3.5 \\ \cline{2-7}  & Large-sized vehicles & 3.75 & 3.75 & 3.75 & 3.5 & 3.5 & 3.5 \\ \hline Mixed lane width(m) & — & — & 3.75 & 3.5 & 3.5 & 3.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Autonomous driving freeway lane width (m). be reduced. After summarizing the autonomous driving projects of various companies, we found that the appearance and performance of autonomous vehicles are not much different from traditional vehicles. Accordingly, the vehicle design indicator can continue to use the current standard. Secondly, we study the horizontal and vertical alignment indicators. These indicators directly determine the shape of the road and affect the passenger experience and the economy of the construction. These alignment indicators are usually controlled by design speed, sight distance, and other indicators. Driver factors indirectly affect road alignment by influencing design elements. Unlike humans, an autonomous driving system has no visual illusion and will not overspeed or overtake frequently. The purpose of limiting the maximum length of straight lines and the maximum radius of curves is to avoid adverse effects on driver's physiology. In autonomous vehicles, there is no driver. Therefore, from the perspective of driving safety and passenger comfort, we recommend removing the restrictions on the maximum length of straight lines and the maximum radius of curves. The current standard only considers the vehicle force balance when calculating the radius of a horizontal curve. In order to avoid safety risks caused by communication system errors or information transmission delays, autonomous vehicles have higher requirements on the lateral clearance of curve sections. The calculation results show that under the condition of high design speed, the radius required to satisfy the lateral clearance is much larger than the radius required to satisfy vehicle force balance. According to this conclusion, designers should pay attention to the driving risk caused by the delay in updating the information of on-board sensors when the vehicle speed is fast.