Integrating Vehicle Noise Emission Models into Eco-Routing for Smart Transportation: Implications in a Case Study

Road traffic noise is the second largest environmental threat in Europe after air pollution, with over a quarter of the population exposed to harmful noise levels. Consequently, significant efforts have been made to develop Road Traffic Noise Models (RTNMs) that can forecast noise levels. RTNMs consist of a Noise Emission Model (NEM) and a sound propagation model. NEMs provide vehicle noise emission curves, expressing the relationship between the sound power level (LW) and the instantaneous speed, while sound propagation models convert this information into equivalent sound pressure levels at receiver points. With the growth of smart cities, specific sensors have been installed to continuously monitor environmental noise and communicate with vehicles, collecting various types of information. However, there remains a lack of awareness among drivers about the potential noise emitted during a trip based on their vehicle characteristics, speed and acceleration profiles, and chosen routes. This represents a misalignment with other eco-routing strategies that optimize travel time and exhaust emissions, which this work aims to address. The starting point is the knowledge of the speed profile maintained during a trip. Based on this information, the average and total sound power levels (LW,ave and LW,tot) emitted during a trip can be computed using noise emission curves. This approach was tested on two different routes (respectively encompassing a national road and a highway) connecting the same origin-destination points, using noise emission curves previously tailored for two test vehicles with different motorizations (diesel and bi-fuel). Results show that there is a difference in noise emissions between the two paths due to the associated speed profiles. Moreover, there exists a significant difference between LW,tot and LW,ave computed using noise emission curves from traditional NEMs and those directly calibrated on the test vehicles, which cannot be neglected. This suggests the need to differentiate noise emission curves based on motorization for effective noise eco-routing strategies.