Noise level based equivalency factors for different mobility options within heterogeneous traffic flow

This study employs a novel approach of comparing the effects of different types of mobility options on noise levels around arterials with the use of noise-level based passenger car unit (PCU) factors. The study area of this research was Karachi, Pakistan, although the methodology can be applied elsewhere. A regression model was developed for calculating PCUs based on noise level. To ensure maximum spread of data collection and variance in levels of traffic presence, the data was collected from five arterials of Karachi. Traffic volume count included mobility options of motorbikes, cars, pickup, rickshaws, buses, and trucks. It was found that the noise-based PCU factors differ greatly compared to those calculated based on traffic flow. Highest noise based PCU factor was for trucks, used for freight mobility, and lowest one was for rickshaws, a very common shared mobility option for passengers. These equivalency factors can provide a convenient approach for prediction of noise levels, along arterials, for transportation planners at the project development stage. Consequently, they can be utilized for planning and development of sustainable and healthy communities. Their importance is also justified on the basis of recent trend which includes introduction of various shared mobility options in Karachi, such as metro bus, online delivery, and ride-hiring services.