A review of road traffic noise indicators and their correlation with the LA10(18hour)

This paper outlines a study to determine the correlation between the LA10(18hour) and other road traffic noise indicators. It is based on a database comprising of 404 measurement locations including 947 individual days of valid noise measurements across numerous circumstances taken between November 2001 and November 2007. This paper firstly discusses the need and constraints on the indicators and their nature of matching a suitable indicator to the various road traffic noise dynamical characteristics. The paper then presents a statistical analysis of the road traffic noise monitoring data, correlating various indicators with the LA10(18hour) statistical indicator and provides a comprehensive table of linear correlations. There is an extended analysis on relationships across the night time period. The paper concludes with a discussion on the findings.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Evolution of traffic management measures on road traffic noise

Road traffic noise affects the quality of life in the areas adjoining the road. The effect of traffic noise on people is wide ranging and may include sleep disturbance and negative impact on work efficiency. To address the problem of traffic noise, it is necessary to estimate the noise level. For this, a number of noise estimation models have been developed which can estimate noise at the receptor points, based on simple configuration of buildings. However, for a real world situation we have multiple buildings forming built-up area. In such a situation, it is almost impossible to consider multiple diffractions and reflections in sound propagation from the source to the receptor point. An engineering solution to such a real world problem is needed to estimate noise levels in built-up area.

Reduced sampling efficiency causes degraded Vernier hyperacuity with normal aging: Vernier acuity in position noise

Vernier acuity, a form of visual hyperacuity, is amongst the most precise forms of spatial vision. Under optimal conditions Vernier thresholds are much finer than the inter-photoreceptor distance. Achievement of such high precision is based substantially on cortical computations, most likely in the primary visual cortex. Using stimuli with added positional noise, we show that Vernier processing is reduced with advancing age across a wide range of noise levels. Using an ideal observer model, we are able to characterize the mechanisms underlying age-related loss, and show that the reduction in Vernier acuity can be mainly attributed to the reduction in efficiency of sampling, with no significant change in the level of internal position noise, or spatial distortion, in the visual system.

A simulation study of unified GPS and roadside ranging technologies for vehicle positioning

The future vehicle navigation for safety applications requires seamless positioning at the accuracy of sub-meter or better. However, standalone Global Positioning System (GPS) or Differential GPS (DGPS) suffer from solution outages while being used in restricted areas such as high-rise urban areas and tunnels due to the blockages of satellite signals. Smoothed DGPS can provide sub-meter positioning accuracy, but not the seamless requirement. A disadvantage of the traditional navigation aids such as Dead Reckoning and Inertial Measurement Unit onboard vehicles are either not accurate enough due to error accumulation or too expensive to be acceptable by the mass market vehicle users. One of the alternative technologies is to use the wireless infrastructure installed in roadside to locate vehicles in regions where the Global Navigation Satellite Systems (GNSS) signals are not available (for example: inside tunnels, urban canyons and large indoor car parks). The examples of roadside infrastructure which can be potentially used for positioning purposes could include Wireless Local Area Network (WLAN)/Wireless Personal Area Network (WPAN) based positioning systems, Ultra-wide band (UWB) based positioning systems, Dedicated Short Range Communication (DSRC) devices, Locata’s positioning technology, and accurate road surface height information over selected road segments such as tunnels. This research reviews and compares the possible wireless technologies that could possibly be installed along roadside for positioning purposes. Models and algorithms of integrating different positioning technologies are also presented. Various simulation schemes are designed to examine the performance benefits of united GNSS and roadside infrastructure for vehicle positioning. The results from these experimental studies have shown a number of useful findings. It is clear that in the open road environment where sufficient satellite signals can be obtained, the roadside wireless measurements contribute very little to the improvement of positioning accuracy at the sub-meter level, especially in the dual constellation cases. In the restricted outdoor environments where only a few GPS satellites, such as those with 45 elevations, can be received, the roadside distance measurements can help improve both positioning accuracy and availability to the sub-meter level. When the vehicle is travelling in tunnels with known heights of tunnel surfaces and roadside distance measurements, the sub-meter horizontal positioning accuracy is also achievable. Overall, simulation results have demonstrated that roadside infrastructure indeed has the potential to provide sub-meter vehicle position solutions for certain road safety applications if the properly deployed roadside measurements are obtainable.

Study on road traffic noise prediction model taking into account the citywide network

For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

Noise detectives : design implications for mobile learning

In this paper, we present an account of children's interactions with a mobile technology prototype within the school context. The noise detectives trial was conducted in a school setting with the aim of better understanding the role of mobile resources as mediators within science and environmental learning activities. Over 80 children, aged between 10 and 12, completed an outdoor data-gathering activity, using a mobile learning prototype that included paper and software components. They measured and recorded noise levels in various locations throughout the school. We analysed the activity to determine how the components of the prototype were integrated into the learning activity, and to identify differences in behaviour that resulted from using these components. We present design implications that resulted from observed differences in prototype use and appropriation.

A roadside survey of unlicensed driving in Queensland

Unlicensed driving remains a serious problem in many jurisdictions, and while it does not play a direct causative role in road crashes, it undermines driver licensing systems and is linked to other high risk driving behaviours. Roadside licence check surveys represent the most direct means of estimating the prevalence of unlicensed driving. The current study involved the Queensland Police Service (QPS) checking the licences of 3,112 drivers intercepted at random breath testing operations across Queensland between February and April 2010. Data was matched with official licensing records from Transport and Main Roads (TMR) via the drivers’ licence number. In total, 2,914 (93.6%) records were matched, with the majority of the 198 unmatched cases representing international or interstate licence holders (n = 156), leaving 42 unknown cases. Among the drivers intercepted at the roadside, 20 (0.6%) were identified as being unlicensed at the time, while a further 11 (0.4%) were driving unaccompanied on a Learner Licence. However, the examination of TMR licensing records revealed that an additional 9 individuals (0.3%) had a current licence sanction but were not identified as unlicensed by QPS. Thus, in total 29 of the drivers were unlicensed at the time, representing 0.9% of all the drivers intercepted and 1% of those for whom their licence records could be checked. This is considerably lower than the involvement of unlicensed drivers in fatal and serious injury crashes in Queensland, which is consistent with other research confirming the increased crash risk of the group. However, the number of unmatched records suggest that it is possible the on-road survey may have under-estimated the prevalence of unlicensed driving, so further development of the survey method is recommended.

Low rank Runge-Kutta methods, symplecticity and stochastic Hamiltonian problems with additive noise

In this paper we extend the ideas of Brugnano, Iavernaro and Trigiante in their development of HBVM($s,r$) methods to construct symplectic Runge-Kutta methods for all values of $s$ and $r$ with $s\geq r$. However, these methods do not see the dramatic performance improvement that HBVMs can attain. Nevertheless, in the case of additive stochastic Hamiltonian problems an extension of these ideas, which requires the simulation of an independent Wiener process at each stage of a Runge-Kutta method, leads to methods that have very favourable properties. These ideas are illustrated by some simple numerical tests for the modified midpoint rule.

Large area noise evaluation

A software tool (DRONE) has been developed to evaluate road traffic noise in a large area with the consideration of network dynamic traffic flow and the buildings. For more precise estimation of noise in urban network where vehicles are mainly in stop and go running conditions, vehicle sound power level (for acceleration/deceleration cruising and ideal vehicle) is incorporated in DRONE. The calculation performance of DRONE is increased by evaluating the noise in two steps of first estimating the unit noise database and then integrating it with traffic simulation. Details of the process from traffic simulation to contour maps are discussed in the paper and the implementation of DRONE on Tsukuba city is presented.

Abstraction as noise : enhancing the poetic

Abstraction in its resistance to evident meaning has the capacity to interrupt or at least provide tools with which to question an overly compliant reception of the information to which we are subject. It does so by highlighting a latency or potentiality inherent in materiality that points to the possibility of a critical resistance to this ceaseless flow of sound/image/data. This resistance has been remarked on in differing ways by a number of commentators such as Lyotard, in his exploration of the avant-garde and the sublime for example. This joint paper will initially map the collaborative project by Daniel Mafe and Andrew Brown, Affecting Interference which conjoins painting with digital sound and animations into a single, large scale, immersive exhibition/installation. The work acts as an interstitial point between contrasting approaches to abstraction: the visual and aural, the digital and analogue. The paper will then explore the ramifications of this through the examination of abstraction as ‘noise’, that is as that raw inassimilable materiality, within which lays the creative possibility to forge and embrace the as-yet-unthought and almost-forgotten. It does so by establishing a space for a more poetic and slower paced critical engagement for the viewing and receiving information or data. This slowing of perception through the suspension of easy recognition runs counter to our current ‘high performance’ culture, and it’s requisite demand for speedy assimilation of content, representing instead the poetic encounter with a potentiality or latency inherent in the nameless particularity of that which is.

A safe system-based approach to selection of clear zones, safety barriers and other roadside treatments

On average, 560 fatal run-off-road crashes occur annually in Australia and 135 in New Zealand. In addition, there are more than 14,000 run-off-road crashes causing injuries each year across both countries. In rural areas, run-off-road casualty crashes constitute 50-60% of all casualty crashes. Their severity is particularly high with more than half of those involved sustaining fatal or serious injuries. This paper reviews the existing approach to roadside hazard risk assessment, selection of clear zones and hazard treatments. It proposes a modified approach to roadside safety evaluation and management. It is a methodology based on statistical modelling of run-off-road casualty crashes, and application of locally developed crash modification factors and severity indices. Clear zones, safety barriers and other roadside design/treatment options are evaluated with a view to minimise fatal and serious injuries – the key Safe System objective. The paper concludes with a practical demonstration of the proposed approach. The paper is based on findings from a four-year Austroads research project into improving roadside safety in the Safe System context.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

A self-tuning feedforward active noise control system

This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.