Noisy Vehicle Research Articles

AI-based method for determining vehicles with illegal muffler from pass-by noise

In Japan, illegal noisy vehicle is controlled by the result of a stationary noise test. The stationary noise test used does not have a simple correlation with pass-by noise due to differences in vehicle conditions. If illegal vehicles can be identified by pass-by noise, it will lead to more effective roadside inspections. Therefore, this study investigated whether it is possible to identify vehicles that exceed the limit value of the stationary noise test limit from pass-by noise using AI. First, we investigated the method using a single sound level meter, and then considered the use of a microphone array to make the method more effective in road traffic flow.

Contact point response-based indirect bridge health monitoring using robust empirical mode decomposition

Indirect bridge health monitoring (iBHM) has emerged as a promising technology for effective and inexpensive monitoring of bridge infrastructure. Driving speed, vehicle frequency, and bridge frequency are among the main contributors to vehicle response while it traverses over the bridge. The vehicle response is criticized as the presence of vehicle frequency can make the vehicle scanning method ineffective. On the other hand, the contact point (CP) response of the vehicle is free from vehicle frequency and can enable the extraction of more number of bridge frequencies. However, this approach suffers from accurate bridge condition assessment, including damage detection under real-life noisy vehicle measurements. In this study, the CP response of a vehicle is explored in tandem with a novel time-frequency decomposition method known as Robust Empirical Mode Decomposition (REMD) for the modal identification of bridges. A numerical study is undertaken to test the feasibility of the proposed method. The simulated parametric study involves parameters such as vehicle speed, measurement noise, and structural damage and their effect on the performance of the proposed method. Furthermore, a field application of the proposed method is verified using a full-scale study of a medium-span bridge. The CP response of a full-scale bridge is calculated from the vehicle response collected from a test vehicle. It shows that the statistical average of the results of the data collected using multiple passes of a test vehicle over the bridge can provide reasonably accurate results, similar to the direct BHM and thereby proving its capability of bridge condition assessment.

Data-Driven Robust Predictive Control for Mixed Vehicle Platoons Using Noisy Measurement

This paper investigates cooperative adaptive cruise control (CACC) for mixed platoons consisting of both human-driven vehicles (HVs) and automated vehicles (AVs). This research is critical because the penetration rate of AVs in the transportation system will remain unsaturated for a long time. Uncertainties and randomness are prevalent in human driving behaviours and highly affect the platoon safety and stability, which need to be considered in the CACC design. A further challenge is the difficulty to know the exact models of the HVs and the exact powertrain parameters of both AVs and HVs. To address these challenges, this paper proposes a data-driven model predictive control (MPC) that does not need the exact models of HVs or powertrain parameters. The MPC design adopts the technique of data-driven reachability to predict the future trajectory of the mixed platoon within a given horizon based on noisy vehicle measurements. Compared to the classic adaptive cruise control (ACC) and existing data-driven adaptive dynamic programming (ADP), the proposed MPC ensures satisfaction of constraints such as acceleration limit and safe inter-vehicular gap. With this salient feature, the proposed MPC has provably guarantee in establishing a safe and robustly stable mixed platoon despite of the velocity changes of the leading vehicle. The efficacy and advantage of the proposed MPC are verified through comparison with the classic ACC and data-driven ADP methods on both small and large mixed platoons.

Accurate and controled vehicle pass-by noise emission quantification in real life traffic

Noise emission from individual vehicle largely contributes to city pollution and has serious health impact. The standards towards vehicle manufactures consists in pass-by testing with specific acceleration conditions which are not representative of all real driving. For the 2015/996 EU directive, the vehicle source model is inspired of the preceding pass-by standard with derived data represented the propulsion and rolling noise sources. Anyhow, those sources are underestimated due to driving behavior, aged and modified vehicle, road surface, meteorological conditions... The true data collection of vehicle pass-by would be interesting. Moreover, some of the countries are reflecting on how to fight against those extremely noisy vehicle exceeding noise limit with efficient monitoring systems. This paper presents an innovative tool able to detect, identify and quantify the noise emission of individual pass-by vehicle in real life traffic. It is based on the combination of array and video processing. Compared to the state of the art and thanks to MEMs technology, the system is optimized and designed to quantify the individual noise vehicle emission regarding standard with controlled measurement and accurate processing. If the conditions are not respected to properly qualify the pass-by regarding the system limits, the data are ignored. It aims at constructing large and accurate database useful to determine average noise levels and/or acceptable noise limits per vehicle category.

Field Evaluation of a Portable Whispering Gallery Mode Accelerometer.

An accelerometer utilising the optomechanical coupling between an optical whispering gallery mode (WGM) resonance and the motion of the WGM cavity itself was prototyped and field-tested on a vehicle. We describe the assembly of this portable, battery operated sensor and the field-programmable gate array automation. Pre-trial testing using an electrodynamic shaker demonstrated linear scale-factors with <0.3% standard deviation ( g range where g = 9.81 ms), and a strong normalised cross-correlation coefficient (NCCC) of r when compared with an integrated circuit piezoelectric (ICP) accelerometer. A noise density of 40 g Hz was obtained for frequencies of 2–7 kHz, increasing to 130 g Hz at 200 Hz, and 250 g Hz at 100 Hz. A reduction in the cross-correlation was found during the trial, r = 0.36, which we attribute to thermal fluctuations, mounting differences, and the noisy vehicle environment. The deployment of this hand-fabricated sensor, shown to operate and survive during ±60 g shocks, demonstrates important steps towards the development of a chip-scale device.

Noisy vehicle surveillance camera: A system to deter noisy vehicle in smart city

With the increase in urbanization in modern cities, major roads and highways are built nearer to residential areas. Due to some inconsiderate driving behaviors, like accelerating and racing; illegal tailpipe modification; and aging vehicles, traffic noise is creating a nuisance to residents staying near highway, especially during late night or early morning. Unfortunately, these noisy vehicles often cannot be caught on the spot, unless traffic police is stationed at a certain place with their sound pressure level meter and camera. This latter approach is often not sustainable and incurs costly manpower resource. An automatic Noisy vehicle surveillance Camera (NoivelCam) system, which can be deployed in overhead structure across major highways near residential buildings, is being designed to capture noise level generated from passing vehicles and triggers a high-speed camera to capture the number plate of offending vehicles that exceed a certain noise level. Therefore, the proposed system provides time stamp, number plate, sound pressure level, audio, and video evidence of the offending vehicle and a means to issue an inspection notice to the owner of the vehicle. This paper provides a description of the NoivelCam, and some of its features to pinpoint noise generated from passing vehicle. An initial in-situ deployment of this system has been carried out in Singapore to test out its effectiveness in monitoring vehicle noise pressure level in a single lane on a highway.

Extraction of Bridge Frequencies from a Moving Test Vehicle by Stochastic Subspace Identification

The technique for extracting bridge frequencies from a moving vehicle was proposed only recently. However, its efficacy may be reduced by road-surface roughness. To this end, the stochastic subspace identification (SSI) is modified to deal with the present time-variant coupled noisy vehicle–bridge interaction system. First, the governing equations for the vehicle and bridge are expressed in state space, including the effects of road roughness and multiple vehicles. Then, they are discretized and transformed to a form suitable for SSI by separating the known from the unknown parameters. Using the Hankel matrix along with the orthogonal projection theorem and singular value decomposition, the observability matrix derived with the vehicle effect suppressed can be used to identify the bridge dynamic properties. It is demonstrated that (1) the proposed SSI approach is more effective for identifying bridge frequencies below 20 Hz for the cases studied, compared with conventional approaches; (2) adding a little damping to the test vehicle can help suppress the vehicle frequency using the proposed approach; and (3) the ongoing traffic is beneficial for amplifying the frequencies of bridges with rough surface.

S0505-2-5 道路交通騒音の常時監視に向けた複合型音源定位法(車両・機体・流体機械に関連した騒音問題へのアプローチと対策(2))

We aim to develop a noise source localization apparatus to detect the noisy vehicle from road traffic noise. This apparatus is consisted of microphone array, camera and processing computer. The microphone array is set upside of running vehicles. Now various types of vehicle pass-by noise exist in traffic flow. Therefore traffic noise is broadband acoustic noise. Hence, wide frequency range is required for source localization method. Though, present methods can't cover such a wide frequency range by itself When we try to locate traffic noise source by present method, it is required too big microphone array to install on the street. This paper proposes a technique that is a hybrid of the beamforming method and the sound intensity method. In order to study the effectiveness of this technique, we performed a test using actual vehicles driven on the test grounds.

Intelligent ventilator positioning via acoustic feedback

A possible solution for the conflict between natural ventilation and passive noise control is presented by introducing a knowledge-based noise classification and position control system. The system controls the position of windows or ventilators as it recognizes an approaching aircraft or noisy vehicle. The level of intrusive transportation noise into the building can be controlled by activating a knowledge-based controller using acoustic feedback. Fuzzy logic and rule-based algorithms are implemented in three major steps: training, source classification and control. To identify an approaching noise source, estimated parameters of a second order autoregressive model AR(2), the dominant peaks of short-time Fourier transform (STFT) and the cross-correlation between output data from indoor and outdoor microphones, are used. If the dominant indoor noise is from transportation sources, the noise level is used as acoustic feedback in a rule-based control loop. Training software is employed to update the detection and classification thresholds and to generate the triangle membership functions with three linguistic variables for decision making and control scenario.

Evaluation of a rapid environment adaptation algorithm in adverse environments

This paper reports results for a rapid environment adaptation algorithm in adverse car environments. It is known that the difference between training and testing environments degrades speech recognition performance. This degradation becomes serious especially in applications such as telephone speech recognition and speech recognition inside a running vehicle, where the testing environment may drastically change. To solve this problem, a rapid environmental adaptation method (hereafter referred to as REALISE) is proposed and its performance is measured in telephone speech recognition. REALISE estimates the differences in multiplicative and additional noise in the spectral domain between the training and testing environments and uses them to adapt acoustic features of reference patterns to the testing environment. Utterances in a car were also recorded to investigate the performance of REALISE under more severe conditions. The testing data were 100 city names uttered by three males and three females under three running conditions (idling, 50 kph, and 100 kph). Whereas the average recognition rate achieved by a conventional spectral subtraction technique was 75.6%, REALISE achieved 85.7%. This result proves the effectiveness of REALISE in a very noisy vehicle environment.

“Swing Low, Sweet Cadillac”: White Supremacy, Antiblack Racism, and the New Historicism

By Paul Gilroy Harvard University Press, 1993 In the first volume of his autobiography (published in 1971), Chester Himes recalls how his African-American family offended their white neighbors in rural Mississippi at the end of World War I by becoming the first owners of a private automobile in their county. The sight of a black family riding around in such a modern, expensive, and noisy vehicle (loud enough to frighten their neighbors' mule teams) outraged white farmers to such a degree that they secured the dismissal of Himes's father from his job at Alcorn A&M University and then forced the family to leave the state. Writing from a distance of more than 50 years and in the aftermath of the passage of major civil rights legislation ending de jure segregation, Himes insisted on the enduring relevance of his childhood memory, explaining ... I must confess I find white people just the same today, everywhere I have been, if a black man owns a big and expensive car they will hate him for (8). The story serves as an appropriate introduction to Himes's autobiography, which at every turn emphasizes the ceaseless and unremitting pressure of white racism on the author's life. But his story is one of a man who relishes resistance as well as a man who suffers repression. Immediately after detailing the incident about that car, Himes concedes that part of the hostility that it