Energy-Efficient Dynamic Street Lighting Optimization: Balancing Pedestrian Safety and Energy Conservation

Abstract

Residential street lighting plays a crucial role in enhancing the reassurance for pedestrians returning home late at night. However, street lighting is sometimes recommended and required to be kept at lower levels at night, due to problems such as light pollution, energy consumption, and negative economics. To solve these problems, this study designed a new Dynamic tracking lighting control mode capable of greater interactivity. Our study aimed to determine whether this new interactive lighting model can balance pedestrian safety with energy savings, compared with other lighting approaches used in low-light environments. In this experiment, 30 participants explored four lighting conditions in a simulated nighttime street environment through virtual reality (VR) and completed their assessment of each lighting mode. The statistical analysis of the results using the Friedman ANOVA test revealed that the Dynamic tracking lighting mode had advantages in improving the pedestrians’ reassurance compared with the other three lighting modes. Moreover, an additional recognition test experiment recorded the distance between each other whenever a participant recognized a stranger agent. The experimental results showed that this Dynamic tracking lighting mode can improve pedestrians’ ability to recognize others in low-light environments. These findings provide new strategies and ideas for urban energy conservation and environmental protection.