Street lighting plays a crucial role in a city’s night landscape and in urban traffic management, influencing users’ comfort and safety. To contain costs of public street lighting systems and to avoid energy waste, illuminance levels on road surfaces must be adequate to fit actual traffic volumes, as prescribed by regulations. This is true not only for motorized roads but also for sidewalks, paths, and pedestrian areas. Regulations in force establish a relationship between road traffic volumes and minimum illuminance levels through the lighting classes selection procedure. Lighting classes selection is based on various para meters among which traffic volume is the most difficult to evaluate because traffic volumes are generally estimated or measured by a traffic observation campaign. In this paper, an alternative method for classes association which is based on a space syntax approach, is described. The method was applied to the case study town of Pontedera (Italy) for the analysis of the pedestrian and motorized traffic and it shows a good correlation between measured and estimated traffic volumes, demonstrating how the methodology, with a precise and quick estimation of traffic volumes, can help lead to a suitable design of the lighting infrastructure, aiming to reduce energy waste and to avoid oversized lighting systems.
A study on urban traffic distribution applying Space Syntax: Focusing on Yeoui-dong
