# HCL Control Strategy for an Adaptive Roadway Lighting Distribution
## 4 Discussion  
The engineering design requirements of roadway lighting usually take both the road surface illuminance and the luminance conditions into consideration. Among them, road surface luminance is highly related to the visual experience of the road users. Hence, road surface luminance performance has been regulated around the world as an important evaluation index. Since the luminance value is inseparable from the reflection characteristics of the pavement material, if the scattering characteristics of the road surface change it would also cause a significant visual difference. Hence, the luminance value of the roadway lighting should be adjusted according to the road conditions. For example, the reflectivity of wet and slippery roads in rainy days is higher than that of dry roads where uneven reflection spots on the road are likely to cause indirect glare or poor uniformity, which contribute to the degrees of risk while driving. \begin{table}
\begin{tabular}{|l|r|r|r|r|} \hline \multirow{2}{*}{**September**} & \multicolumn{2}{c|}{**Sect. 3 of Gaotie South Road**} & \multicolumn{2}{c|}{**Sect. 5 of Gaotie South Road**} \\ \cline{2-5}  & **High Level** & **Low Level** & **High Level** & **Low Level** \\ \hline
**Average** & 0.798 & 0.631 & 0.781 & 0.608 \\ \hline
**Stand deviation** & & & & \\ (individual) & 0.039638646 & 0.25896911 & 0.033194712 & 0.272890902 \\ \hline
**Stand deviation** & & & & \\ (month) & & 0.185251481 & & 0.194385356 \\ \hline \end{tabular}
\end{table} 
Table 8: The standard deviation of luminance longitude uniformity. Figure 23: The lighting conditions in Sect. 5 of Gaotie South Road: (**a**) Type A lens on a dry road surface; (**b**) Type A lens on a wet road surface; (**c**) Type B lens on a wet road surface. Traditional roadway lighting optics are all designed with fixed light distribution. Usually, the road surface material is preset to R3 pavement characteristics as the standard parameter when evaluating the luminance distribution. Therefore, it is relatively difficult for traditional lighting to adapt to various environmental conditions. In situations where the weather or road surface conditions change abruptly, drivers will be exposed to poor lighting quality since the uniformity of the light distribution is usually designed for standard road surface conditions. Hence, when it comes to bad road conditions, the visual uniformity will drop drastically also. This paper proposes a LED human-centric roadway lighting system that can adapt to different road conditions, hoping to provide drivers with a safer road environment at all times. In this paper, an imaging luminance meter (ILM) is used for detecting and monitoring the luminance uniformity of road lighting. During 2007, due to the increasing awareness for energy saving and safety, one study [38] used an ILM to measure and analyze the luminance level of different kinds of road surface and of intelligent street lighting. In that particular article, measurement results of different road surface conditions including dry, wet and snow-covered roads are proposed. The results show that the luminance of the snow-covered roads is significantly higher than that of dry and wet roads. In addition, dry roads and snow-covered surfaces are less susceptible to height and distance when measuring and the standard deviation of luminance is around 0.03 and 0.02 respectively. While the measurement result of the wet road is much more susceptible to the observation point, which leads to a different measurement value. Therefore, when comparing the luminance level measured from the driver's position with the installation point of the ILM, the luminance values of dry roads are relatively close while the luminance level of wet roads can reach a difference of more than 10%, which is close to the results of this paper. However, they did not mention the road pavement materials in their study.