# Research on Geometric Design Standards for Freeways under a Fully Autonomous Driving Environment
## 3 Elements of Design
### Stopping Sight Distance
#### 3.3.2 Models and Calculations  
Different countries have different models for calculating the stopping sight distance. According to the relevant literature [27; 29], the calculation models of stopping sight distance in several representative countries have been summarized, as shown in Table 3. The calculation models of stopping sight distances in various countries are similar. There are only slight differences in the values of some parameters in the model. * Reaction time  
In a fully autonomous driving environment, because of the high speed, autonomous vehicles can travel long distances in a short time. Thus, the process of the system reaction cannot be simply ignored. Combined with relevant research, based on the principle of safety first, it is recommended to take the system reaction time of the autonomous vehicle as 0.5s when calculating the freeway stopping sight distance. * Initial speed  
_A POLICY on GEOMETRIC DESIGN of HIGHWYS and STREETS_ shows that many drivers do not greatly reduce their speed when the road is wet [30]. Thus, when calculating the stopping sight distance, the U.S. changed the initial speed during braking from the driving speed to the design speed. It can be seen from Table 3 that, like the United States, the initial speed in the French stopping sight distance model is also the design speed. Like Japan, China uses 85% of the design speed as the initial speed. In a fully autonomous driving environment, the vehicle's sensor systems are less affected by the weather [10; 31]. The driving speed is not limited by rainy weather and wet \begin{table}
\begin{tabular}{c c c} \hline \hline
**Country** & **Calculation Model** & **Description** \\ \hline U.S. & \(SSD\)= 0.2780\(Vt\)+0.039\(\frac{V^{2}}{a}\) & \(SSD\) is stopping sight distance; \(V\) is design speed (km/h); \(t\) is reaction time; \(a\) is average deceleration. \\ \hline France & \(d_{\text{s}}\)= \(2V+\frac{V^{2}}{2g\psi(v)}\) & \(d_{\text{s}}\) is stopping sight distance; \(V\) is design speed (km/h); \(\psi(v)\) is average deceleration (m/s\({}^{2}\)); \(g\) is the acceleration of gravity (m/s\({}^{2}\)). \\ \hline China & \(S_{\text{sd}}\) is stopping sight distance; \(V_{0}\) is driving speed (85\% of design speed); \(f_{1}\) is longitudinal friction coefficient; \(g\) is the acceleration of gravity (m/s\({}^{2}\)). \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Calculation model of stopping sight distance in different countries. and dry conditions of the pavement. At the same time, autonomous vehicles are expected to travel in line (at the same speed and a certain safe distance). This will greatly reduce frequent overtaking and lane changing behavior between vehicles. With the support of technologies such as the Internet of vehicles, CPUs, and high-precision maps, autonomous vehicles can globally plan driving routes in advance, so as to ensure driving speed and traffic efficiency. According to research [26], under the premise of road conditions and traffic regulations, autonomous vehicles can drive at the maximum speed. So, the initial braking speed is recommended to be taken as the design speed of a freeway. * Deceleration In the Chinese stopping sight distance calculation model, the value of braking deceleration considers the longitudinal friction coefficient between pavement and tires. However, research has shown that [27; 32; 33] the accurate measurement of the longitudinal friction coefficient needs to consider driving speed. During the measurement, the vehicle is fully braked, and the wheels are locked, which obviously does not correspond to the real braking process. With the advent of new pavement materials, tires, and ABS anti-lock braking systems, the longitudinal friction coefficient can no longer accurately reflect the real situation of emergency braking.