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.

Prediction and measurement of multiuser MIMO-OFDM channel in rural Australia

Commonwealth Scientific and Industrial Research Organization (CSIRO) has recently conducted a technology demonstration of a novel fixed wireless broadband access system in rural Australia. The system is based on multi user multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM). It demonstrated an uplink of six simultaneous users with distances ranging from 10 m to 8.5 km from a central tower, achieving 20 bits s/Hz spectrum efficiency. This paper reports on the analysis of channel capacity and bit error probability simulation based on the measured MUMIMO-OFDM channels obtained during the demonstration, and their comparison with the results based on channels simulated by a novel geometric optics based channel model suitable for MU-MIMO OFDM in rural areas. Despite its simplicity, the model was found to predict channel capacity and bit error rate probability accurately for a typical MU-MIMO-OFDM deployment scenario.

Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

Multi-method, multi-theoretical, multi-level research in the learning sciences

We examine methodologies and methods that apply to multi-level research in the learning sciences. In so doing we describe how multiple theoretical frameworks informs the use of different methods that apply to social levels involving space-time relationships that are not accessible consciously as social life is enacted. Most of the methods involve analyses of video and audio files. Within a framework of interpretive research we present a methodology of event-oriented social science, which employs video ethnography, narrative, conversation analysis, prosody analysis, and facial expression analysis. We illustrate multi-method research in an examination of the role of emotions in teaching and learning. Conversation and prosody analyses augment facial expression analysis and ethnography. We conclude with an exploration of ways in which multi-level studies can be complemented with neural level analyses.

A fundamental numerical and theoretical study for the vibrational properties of nanowires

Based on the molecular dynamics (MD) simulation and the classical Euler-Bernoulli beam theory, a fundamental study of the vibrational performance of the Ag nanowire (NW) is carried out. A comprehensive analysis of the quality (Q)-factor, natural frequency, beat vibration, as well as high vibration mode is presented. Two excitation approaches, i.e., velocity excitation and displacement excitation, have been successfully implemented to achieve the vibration of NWs. Upon these two kinds of excitations, consistent results are obtained, i.e., the increase of the initial excitation amplitude will lead to a decrease to the Q-factor, and moderate plastic deformation could increase the first natural frequency. Meanwhile, the beat vibration driven by a single relatively large excitation or two uniform excitations in both two lateral directions is observed. It is concluded that the nonlinear changing trend of external energy magnitude does not necessarily mean a nonconstant Q-factor. In particular, the first order natural frequency of the Ag NW is observed to decrease with the increase of temperature. Furthermore, comparing with the predictions by Euler- Bernoulli beam theory, the MD simulation provides a larger and smaller first vibration frequencies for the clamped-clamped and clamped-free thin Ag NWs, respectively. Additionally, for thin NWs, the first order natural frequency exhibits a parabolic relationship with the excitation magnitudes. The frequencies of the higher vibration modes tend to be low in comparison to Euler-Bernoulli beam theory predictions. A combined initial excitation is proposed which is capable to drive the NW under a multi-mode vibration and arrows the coexistence of all the following low vibration modes. This work sheds lights on the better understanding of the mechanical properties of NWs and benefits the increasing utilities of NWs in diverse nano-electronic devices.

The experiences of learner drivers, provisional drivers and supervisors with graduated driver licensing in two Australian jurisdictions

Newly licensed drivers on a provisional or intermediate licence have the highest crash risk when compared with any other group of drivers. In comparison, learner drivers have the lowest crash risk. Graduated driver licensing is one countermeasure that has been demonstrated to effectively reduce the crashes of novice drivers. This thesis examined the graduated driver licensing systems in two Australian states in order to better understand the behaviour of learner drivers, provisional drivers and the supervisors of learner drivers. By doing this, the thesis investigated the personal, social and environmental influences on novice driver behaviour as well as providing effective baseline data against which to measure subsequent changes to the licensing systems. In the first study, conducted prior to the changes to the graduated driver licensing system introduced in mid-2007, drivers who had recently obtained their provisional licence in Queensland and New South Wales were interviewed by telephone regarding their experiences while driving on their learner licence. Of the 687 eligible people approached to participate at driver licensing centres, 392 completed the study representing a response rate of 57.1 per cent. At the time the data was collected, New South Wales represented a more extensive graduated driver licensing system when compared with Queensland. The results suggested that requiring learners to complete a mandated number of hours of supervised practice impacts on the amount of hours that learners report completing. While most learners from New South Wales reported meeting the requirement to complete 50 hours of practice, it appears that many stopped practising soon after this goal was achieved. In contrast, learners from Queensland, who were not required to complete a specific number of hours at the time of the survey, tended to fall into three groups. The first group appeared to complete the minimum number of hours required to pass the test (less than 26 hours), the second group completed 26 to 50 hours of supervised practice while the third group completed significantly more practice than the first two groups (over 100 hours of supervised practice). Learner drivers in both states reported generally complying with the road laws and were unlikely to report that they had been caught breaking the road rules. They also indicated that they planned to obey the road laws once they obtained their provisional licence. However, they were less likely to intend to comply with recommended actions to reduce crash risk such as limiting their driving at night. This study also identified that there were relatively low levels of unaccompanied driving (approximately 15 per cent of the sample), very few driving offences committed (five per cent of the sample) and that learner drivers tended to use a mix of private and professional supervisors (although the majority of practice is undertaken with private supervisors). Consistent with the international literature, this study identified that very few learner drivers had experienced a crash (six per cent) while on their learner licence. The second study was also conducted prior to changes to the graduated driver licensing system and involved follow up interviews with the participants of the first study after they had approximately 21 months driving experience on their provisional licence. Of the 392 participants that completed the first study, 233 participants completed the second interview (representing a response rate of 59.4 per cent). As with the first study, at the time the data was collected, New South Wales had a more extensive graduated driver licensing system than Queensland. For instance, novice drivers from New South Wales were required to progress through two provisional licence phases (P1 and P2) while there was only one provisional licence phase in Queensland. Among the participants in this second study, almost all provisional drivers (97.9 per cent) owned or had access to a vehicle for regular driving. They reported that they were unlikely to break road rules, such as driving after a couple of drinks, but were also unlikely to comply with recommended actions, such as limiting their driving at night. When their provisional driving behaviour was compared to the stated intentions from the first study, the results suggested that their intentions were not a strong predictor of their subsequent behaviour. Their perception of risk associated with driving declined from when they first obtained their learner licence to when they had acquired provisional driving experience. Just over 25 per cent of participants in study two reported that they had been caught committing driving offences while on their provisional licence. Nearly one-third of participants had crashed while driving on a provisional licence, although few of these crashes resulted in injuries or hospitalisations. To complement the first two studies, the third study examined the experiences of supervisors of learner drivers, as well as their perceptions of their learner’s experiences. This study was undertaken after the introduction of the new graduated driver licensing systems in Queensland and New South Wales in mid- 2007, providing insights into the impacts of these changes from the perspective of supervisors. The third study involved an internet survey of 552 supervisors of learner drivers. Within the sample, approximately 50 per cent of participants supervised their own child. Other supervisors of the learner drivers included other parents or stepparents, professional driving instructors and siblings. For two-thirds of the sample, this was the first learner driver that they had supervised. Participants had provided an average of 54.82 hours (sd = 67.19) of supervision. Seventy-three per cent of participants indicated that their learners’ logbooks were accurate or very accurate in most cases, although parents were more likely than non-parents to report that their learners’ logbook was accurate (F (1,546) = 7.74, p = .006). There was no difference between parents and non-parents regarding whether they believed the log book system was effective (F (1,546) = .01, p = .913). The majority of the sample reported that their learner driver had had some professional driving lessons. Notwithstanding this, a significant proportion (72.5 per cent) believed that parents should be either very involved or involved in teaching their child to drive, with parents being more likely than non-parents to hold this belief. In the post mid-2007 graduated driver licensing system, Queensland learner drivers are able to record three hours of supervised practice in their log book for every hour that is completed with a professional driving instructor, up to a total of ten hours. Despite this, there was no difference identified between Queensland and New South Wales participants regarding the amount of time that they reported their learners spent with professional driving instructors (X2(1) = 2.56, p = .110). Supervisors from New South Wales were more likely to ensure that their learner driver complied with the road laws. Additionally, with the exception of drug driving laws, New South Wales supervisors believed it was more important to teach safety-related behaviours such as remaining within the speed limit, car control and hazard perception than those from Queensland. This may be indicative of more intensive road safety educational efforts in New South Wales or the longer time that graduated driver licensing has operated in that jurisdiction. However, other factors may have contributed to these findings and further research is required to explore the issue. In addition, supervisors reported that their learner driver was involved in very few crashes (3.4 per cent) and offences (2.7 per cent). This relatively low reported crash rate is similar to that identified in the first study. Most of the graduated driver licensing research to date has been applied in nature and lacked a strong theoretical foundation. These studies used Akers’ social learning theory to explore the self-reported behaviour of novice drivers and their supervisors. This theory was selected as it has previously been found to provide a relatively comprehensive framework for explaining a range of driver behaviours including novice driver behaviour. Sensation seeking was also used in the first two studies to complement the non-social rewards component of Akers’ social learning theory. This program of research identified that both Akers’ social learning theory and sensation seeking were useful in predicting the behaviour of learner and provisional drivers over and above socio-demographic factors. Within the first study, Akers’ social learning theory accounted for an additional 22 per cent of the variance in learner driver compliance with the law, over and above a range of socio-demographic factors such as age, gender and income. The two constructs within Akers’ theory which were significant predictors of learner driver compliance were the behavioural dimension of differential association relating to friends, and anticipated rewards. Sensation seeking predicted an additional six per cent of the variance in learner driver compliance with the law. When considering a learner driver’s intention to comply with the law while driving on a provisional licence, Akers’ social learning theory accounted for an additional 10 per cent of the variance above socio-demographic factors with anticipated rewards being a significant predictor. Sensation seeking predicted an additional four per cent of the variance. The results suggest that the more rewards individuals anticipate for complying with the law, the more likely they are to obey the road rules. Further research is needed to identify which specific rewards are most likely to encourage novice drivers’ compliance with the law. In the second study, Akers’ social learning theory predicted an additional 40 per cent of the variance in self-reported compliance with road rules over and above socio-demographic factors while sensation seeking accounted for an additional five per cent of the variance. A number of Aker’s social learning theory constructs significantly predicted provisional driver compliance with the law, including the behavioural dimension of differential association for friends, the normative dimension of differential association, personal attitudes and anticipated punishments. The consistent prediction of additional variance by sensation seeking over and above the variables within Akers’ social learning theory in both studies one and two suggests that sensation seeking is not fully captured within the non social rewards dimension of Akers’ social learning theory, at least for novice drivers. It appears that novice drivers are strongly influenced by the desire to engage in new and intense experiences. While socio-demographic factors and the perception of risk associated with driving had an important role in predicting the behaviour of the supervisors of learner drivers, Akers’ social learning theory provided further levels of prediction over and above these factors. The Akers’ social learning theory variables predicted an additional 14 per cent of the variance in the extent to which supervisors ensured that their learners complied with the law and an additional eight per cent of the variance in the supervisors’ provision of a range of practice experiences. The normative dimension of differential association, personal attitudes towards the use of professional driving instructors and anticipated rewards were significant predictors for supervisors ensuring that their learner complied with the road laws, while the normative dimension was important for range of practice. This suggests that supervisors who engage with other supervisors who ensure their learner complies with the road laws and provide a range of practice to their own learners are more likely to also engage in these behaviours. Within this program of research, there were several limitations including the method of recruitment of participants within the first study, the lower participation rate in the second study, an inability to calculate a response rate for study three and the use of self-report data for all three studies. Within the first study, participants were only recruited from larger driver licensing centres to ensure that there was a sufficient throughput of drivers to approach. This may have biased the results due to the possible differences in learners that obtain their licences in locations with smaller licensing centres. Only 59.4 per cent of the sample in the first study completed the second study. This may be a limitation if there was a common reason why those not participating were unable to complete the interview leading to a systematic impact on the results. The third study used a combination of a convenience and snowball sampling which meant that it was not possible to calculate a response rate. All three studies used self-report data which, in many cases, is considered a limitation. However, self-report data may be the only method that can be used to obtain some information. This program of research has a number of implications for countermeasures in both the learner licence phase and the provisional licence phase. During the learner phase, licensing authorities need to carefully consider the number of hours that they mandate learner drivers must complete before they obtain their provisional driving licence. If they mandate an insufficient number of hours, there may be inadvertent negative effects as a result of setting too low a limit. This research suggests that logbooks may be a useful tool for learners and their supervisors in recording and structuring their supervised practice. However, it would appear that the usage rates for logbooks will remain low if they remain voluntary. One strategy for achieving larger amounts of supervised practice is for learner drivers and their supervisors to make supervised practice part of their everyday activities. As well as assisting the learner driver to accumulate the required number of hours of supervised practice, it would ensure that they gain experience in the types of environments that they will probably encounter when driving unaccompanied in the future, such as to and from education or work commitments. There is also a need for policy processes to ensure that parents and professional driving instructors communicate effectively regarding the learner driver’s progress. This is required as most learners spend at least some time with a professional instructor despite receiving significant amounts of practice with a private supervisor. However, many supervisors did not discuss their learner’s progress with the driving instructor. During the provisional phase, there is a need to strengthen countermeasures to address the high crash risk of these drivers. Although many of these crashes are minor, most involve at least one other vehicle. Therefore, there are social and economic benefits to reducing these crashes. If the new, post-2007 graduated driver licensing systems do not significantly reduce crash risk, there may be a need to introduce further provisional licence restrictions such as separate night driving and peer passenger restrictions (as opposed to the hybrid version of these two restrictions operating in both Queensland and New South Wales). Provisional drivers appear to be more likely to obey some provisional licence laws, such as lower blood alcohol content limits, than others such as speed limits. Therefore, there may be a need to introduce countermeasures to encourage provisional drivers to comply with specific restrictions. When combined, these studies provided significant information regarding graduated driver licensing programs. This program of research has investigated graduated driver licensing utilising a cross-sectional and longitudinal design in order to develop our understanding of the experiences of novice drivers that progress through the system in order to help reduce crash risk once novice drivers commence driving by themselves.

Theoretical perspectives on motorcycle training: reducing risk taking

Little past empirical support has been found for the efficacy of motorcycle rider training as a road safety countermeasure. However, it has been argued that rider training should focus more particularly on the psychosocial factors that influence risk taking behaviour in addition to the traditional practice of developing vehicle-handling skills. This paper examines how rider training to reduce risk taking could be guided by appropriate theories. Two fundamental perspectives are examined: firstly training can be considered in terms of behaviour change, and secondly in terms of adult learning. Whilst behaviour change theories assume some pre-existing level of dysfunctional behaviour, an adult learning perspective does not necessarily carry this assumption. This distinction in perspectives conceptually aligns with the notions of intervention and prevention (respectively), with possible implications for specific target groups for pre-licence and post-licence training. The application of the Theory of Reasoned Action (Ajzen & Fishbein, 1975, 1980) and Transformative Learning Theory (Mezirow, 1997) to a pre-licence rider training program in Queensland, Australia is discussed.

Modeling random effect and excess zeros in road traffic accident prediction

Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

Bayesian hierarchical analysis on crash prediction models

Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records. This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

Experimental and theoretical investigation of ligand effects on the synthesis of ZnO nanoparticles

ZnO nanoparticles with highly controllable particle sizes(less than 10 nm) were synthesized using organic capping ligands in Zn(Ac)2 ethanolic solution. The molecular structure of the ligands was found to have significant influence on the particle size. The multi-functional molecule tris(hydroxymethyl)-aminomethane (THMA) favoured smaller particle distributions compared with ligands possessing long hydrocarbon chains that are more frequently employed. The adsorption of capping ligands on ZnnOn crystal nuclei (where n = 4 or 18 molecular clusters of(0001) ZnO surfaces) was modelled by ab initio methods at the density functional theory (DFT) level. For the molecules examined, chemisorption proceeded via the formation of Zn...O, Zn...N, or Zn...S chemical bonds between the ligands and active Zn2+ sites on ZnO surfaces. The DFT results indicated that THMA binds more strongly to the ZnO surface than other ligands, suggesting that this molecule is very effective at stabilizing ZnO nanoparticle surfaces. This study, therefore, provides new insight into the correlation between the molecular structure of capping ligands and the morphology of metal oxide nanostructures formed in their presence.