# Development and Testing of an Active Noise Control System for Urban Road Traffic Noise
## 5 Discussion  
In active noise control tests for single- and dual-frequency noise, the system demonstrated significant noise reduction within the primary frequency range of road traffic noise. Moreover, it exhibited fast convergence, stable operation, and strong versatility. This paves the way for the potential application of active noise control technology in the realm of road traffic. In tests with actual road traffic noise, we did not observe significant noise reduction. However, it clearly identified the issues that need to be addressed in future research:  
(1) The active noise control system failed to achieve significant noise reduction when dealing with actual road traffic noise. This could be attributed to factors such as traffic  
Figure 12: Dual-frequency test results. (**a**) Comparison for 100 Hz + 1000 Hz. (**b**) Comparison for 200 Hz + 1000 Hz.  
volume, vehicle types, speed, etc., leading to the complexity of the primary and secondary path parameters and diversity in noise frequency components. For instance, heavy vehicles might produce more low-frequency noise, while motorcycles might generate more high-frequency noise. These variations could lead to changes in the primary path parameters, secondary path parameters, etc., and with each vehicle serving as a noise source, different noise sources might interfere with each other, making sound wave prediction and cancellation more complex.  
(2) It was found that the speakers and sensors had poorer frequency response to low-frequency noise, which may prevent the system from accurately generating and measuring low-frequency noise, thereby affecting the accuracy of noise reduction. Similarly, due to the hardware system's latency, real-time processing of high-frequency noise also faces challenges, potentially leading to phase shifts and noise increase.  
(3) In the active noise control system, electronic devices, wiring, and acoustical factors between the secondary source and the error sensor might cause latency issues. These issues have not been fully considered in the current LMS algorithm, thus affecting the noise reduction performance. Moreover, because road traffic noise is broadband noise with a wide frequency distribution, this leads to a situation in the LMS algorithm where the larger the frequency range of the input signal, the higher the signal correlation, and the slower the algorithm converges, thereby affecting the noise reduction effect.  
To adapt to the characteristics of road traffic noise, future research could be based on the theory of reference sub-band filtering to improve the algorithm's convergence speed and noise reduction effect by processing the input signal into several narrow-band noise signals. Consideration could also be given to enhancing the hardware performance of the sensors and speakers, such as improving the sensor signal-to-noise ratio, speaker frequency response characteristics, controller computational speed, system integration, and stability, especially assessing the active noise control performance of speakers in the low-frequency range. Further exploration of active noise control applications in the traffic domain can also be carried out, including a combination with passive technologies such as noise barriers and research into active noise control technology for vehicle tire-road noise.