Impact of roadside distributed photovoltaic systems on driver glare

With the widespread application of photovoltaic technology in transportation infrastructure, the potential threat to driving safety posed by glare generated by roadside distributed photovoltaic systems has become a concern. This study aims to evaluate the varying degrees of glare caused by the azimuth(Orient), tilt angle (Tilt), observation point height (Height), and vehicle position on the photovoltaic section (Distance).

The Transformer attention mechanism was used to weight the input features, explore the correlation and importance between features, and the extracted features were concatenated with the original features to form a new feature set. The concatenated feature data were used to train Random Forest (RF) and Gradient Boosting Decision Tree (GBDT) models.

The RF model after feature processing achieved Coefficient of determination (R²) values of 0.831 and 0.907 on the test sets, respectively, with lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) indicators, showing better overall performance. Therefore, the improved RF model was selected for predicting driver glare duration.

It was found that Orient is the most important feature affecting glare, which should be prioritized in the installation of photovoltaic systems. For highway photovoltaic installations, priority should be given to Orient, which can alleviate the situation during periods of high glare. Moreover, Tilt adjustment balances power generation and reduces glare. In addition, the directional offset from the lane at curves or exits further ensures driving safety.