This thesis investigates approaches for the auralisation of traffic noise in an outdoor environment. A novel auralisation framework for multiple vehicle pass-bys using procedural audio methods is proposed. This includes sound source modelling of single vehicle pass-bys and traffic flow, sound propagation modelling, and HRTF processing for spatial audio reproduction. Compared to prior auralisation studies in which sound source recordings have been used, no pre-recorded sounds are used with a procedural audio approach. Instead, synthetic sounds created by programmatic rules form the basis of the auralisation framework proposed in this thesis.
Such an auralisation based on procedural audio gives greater freedom and range in the implementation and integration of vehicle pass-by sounds, with the advantage of high flexibility and variable computational cost for the algorithms defining the properties of any given audio objects. However, such synthetic sounds might not be perceived as being plausible when compared to their recorded counterparts, especially for the case of traffic noise where it is difficult to imitate the intrinsic rich and varied sound source content by artificial means. Therefore, two subjective listening tests are implemented to evaluate the plausibility of the proposed auralisation framework by comparing procedurally generated vehicle sounds to their counterparts created using a recording-based granular synthesis method.
Engine sounds, engine plus tyre sounds, and single vehicle pass-by sounds, all generated using a procedural audio approach, are compared with their counterparts created using a granular synthesis method, and evaluated in an ABX listening test. It is found that a similar level of plausibility is achieved by using either method for the auralisation of single vehicle pass-bys. Based on this validation, the plausibility of multiple vehicle pass-by sounds with engines synthesised using a procedural, a mix of procedural and granular, and granular approaches is evaluated in a MUSHRA test under various traffic flow conditions regarding different vehicle types, speeds, driving directions, and flow rates. It is found that a similar level of plausibility is achieved by using either method under most traffic flow conditions.
These results verify that the auralisation of traffic flow using procedural audio methods is comparable to recording-based approaches when considering the plausibility of the results obtained. Such an approach provides a solution for implementing the auralisation of environmental sounds that is both flexible and plausible, which is useful for communicating and demonstrating the important changes in our soundscape to the wider population, leading to a more holistic understanding of environmental sound
