# Development and Testing of an Active Noise Control System for Urban Road Traffic Noise  
[PERSON]  
1 Highway School, Chang'an University, Xi'an 710054, China; [EMAIL_ADDRESS]  
2  
[PERSON]  
3 National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, China; [EMAIL_ADDRESS] (J.Y. ); [EMAIL_ADDRESS] (Z.Y. ); [EMAIL_ADDRESS] (S.Y.) [PERSON]  
3 National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, China; [EMAIL_ADDRESS] (J.  
field of road traffic, active noise control technology is widely used in vehicle noise control: [PERSON] et al. used a convolutional neural network to classify road surfaces, improving the vehicle noise reduction by adjusting the LMS algorithm based on the road type [19]. [PERSON] et al. experimented with using ANC inside vehicles, using algorithms like TF-FxLMS and SFxLMS to lower the computational efforts and compare the algorithm complexities [20]. [PERSON] et al. developed a multichannel adaptive algorithm to control the engine noise in vehicles, especially those with prominent harmonic noise [21]. [PERSON]'s group enhanced the SPSA algorithm for ANC in vehicles, targeting low-frequency noise near the driver's head, reducing the interior noise by an average of 10 dB [22]. [PERSON] proposed a method for grouping virtual reference signals in vehicle road noise control systems, cutting the computational complexity by about 24.4% and reducing noise by up to 4.48 dB in the roar frequency band [23]. The current active noise control technology has a good noise reduction effect in closed space environments, but the noise reduction effect in open space environments with multiple sound sources needs to be improved [24]. As road traffic noise is affected by many factors such as traffic flow, speed, and vehicle position, it is non-stationary noise, and vehicles are mobile sound sources with a Doppler effect. It is much more difficult to achieve active noise control in a spacious open environment than in a closed space [25]. Controlling roadside traffic noise with active noise control (ANC) techniques presents significant challenges. Researchers have explored various solutions, focusing on different aspects of noise control in real-world settings. One approach is to use ANC in confined spaces like tunnels. For instance, [PERSON] developed an ANC device for highway tunnels, achieving up to 10.48 dB noise reduction, though the test was limited to a fixed noise source [26]. [PERSON] et al. expanded on this by testing an ANC device in a tunnel model with a more complex noise source, showing a reduction of 4-15 dB [27]. However, in typical road traffic environments, the noise from moving vehicles is often distant from ANC systems, leading to unstable signals. To address this, [PERSON] et al. proposed using a fixed coefficient feedforward ANC system with a pseudo-noise source, demonstrating the feasibility of this approach [28]. Combining active and passive noise reduction techniques has also been explored. [PERSON] et al. showed that mounting ANC systems onto sound barriers can significantly cut down the low-frequency noise [29; 30]. Similarly, [PERSON] et al. combined sound barriers with ANC systems to identify effective noise reduction strategies, including the placement and number of microphones and secondary sound sources [31]. Tire-road noise is another area of focus. [PERSON] et al. suggested installing ANC systems near the tire-road contact point, acknowledging the challenges and research needs with this method [32]. [PERSON] et al. explored the effect of ANC in small openings, finding that effective broadband noise control is possible even in limited spaces [33]. In summary, applying active noise control (ANC) to roadside traffic noise is challenging and currently at the research stage. This paper aims to advance the application of ANC in this field. Our approach includes analyzing the road traffic noise characteristics and developing an ANC prototype system.