Improving level crossing safety through enhanced data recording and reporting : The CRC for Rail Innovation’s Baseline Rail Level Crossing Video project

This paper describes the work being conducted in the baseline rail level crossing project, supported by the Australian rail industry and the Cooperative Research Centre for Rail Innovation. The paper discusses the limitations of near-miss data for analysis obtained using current level crossing occurrence reporting practices. The project is addressing these limitations through the development of a data collection and analysis system with an underlying level crossing accident causation model. An overview of the methodology and improved data recording process are described. The paper concludes with a brief discussion of benefits this project is expected to provide the Australian rail industry.

On the use of Bluetooth MAC Scanners for live reporting of the transport network

Recently there has been significant interest of researchers and practitioners on the use of Bluetooth as a complementary transport data. However, literature is limited with the understanding of the Bluetooth MAC Scanner (BMS) based data acquisition process and the properties of the data being collected. This paper first provides an insight on the BMS data acquisition process. Thereafter, it discovers the interesting facts from analysis of the real BMS data from both motorway and arterial networks of Brisbane, Australia. The knowledge gained is helpful for researchers and practitioners to understand the BMS data being collected which is vital to the development of management and control algorithms using the data.

A framework for cost-aware process management : cost reporting and cost prediction

Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.

Pre-crash traffic flow trend analysis on motorways

Crashes on motorway contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence reduce crashes will help address congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a Short time window around the time of crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques, that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists, and that this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with traffic flow data of one hour prior to the crash using an incident detection algorithm. Traffic flow trends (traffic speed/occupancy time series) revealed that crashes could be clustered with regards of the dominant traffic flow pattern prior to the crash. Using the k-means clustering method allowed the crashes to be clustered based on their flow trends rather than their distance. Four major trends have been found in the clustering results. Based on these findings, crash likelihood estimation algorithms can be fine-tuned based on the monitored traffic flow conditions with a sliding window of 60 minutes to increase accuracy of the results and minimize false alarms.

Pre-crash and non-crash traffic flow trends analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestions. Hence, reducing the frequency of crashes assists in addressing congestion issues (Meyer, 2008). Crash likelihood estimation studies commonly focus on traffic conditions in a short time window around the time of a crash while longer-term pre-crash traffic flow trends are neglected. In this paper we will show, through data mining techniques that a relationship between pre-crash traffic flow patterns and crash occurrence on motorways exists. We will compare them with normal traffic trends and show this knowledge has the potential to improve the accuracy of existing models and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding to traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash. Using the K-Means clustering method with Euclidean distance function allowed the crashes to be clustered. Then, normal situation data was extracted based on the time distribution of crashes and were clustered to compare with the “high risk” clusters. Five major trends have been found in the clustering results for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Based on these findings, crash likelihood estimation models can be fine-tuned based on the monitored traffic conditions with a sliding window of 30 minutes to increase accuracy of the results and minimize false alarms.

Context matters : Violence against women and reporting to police in rural, suburban and urban areas

Despite plentiful efforts to identify perpetrator, victim, and incident characteristics correlated with reporting violence against women to police, few studies have addressed the contexts that shape such reporting. Even fewer have examined variations in these contexts across geographic areas. Drawing upon National Crime Victimization Survey data from 1992 through 2009, this paper uses conjunctive analysis of case configurations to identify and investigate the dominant situational contexts of reporting of violence against women to police across rural, suburban, and urban areas. Our findings show that context matters and the importance of incident, perpetrator, and victim characteristics vary across geographic areas.

Random breath testing in Queensland and Western Australia : Examination of how the random breath testing rate influences alcohol related traffic crash rates

In this paper we explore the relationship between monthly random breath testing (RBT) rates (per 1000 licensed drivers) and alcohol-related traffic crash (ARTC) rates over time, across two Australian states: Queensland and Western Australia. We analyse the RBT, ARTC and licensed driver rates across 12 years; however, due to administrative restrictions, we model ARTC rates against RBT rates for the period July 2004 to June 2009. The Queensland data reveals that the monthly ARTC rate is almost flat over the five year period. Based on the results of the analysis, an average of 5.5 ARTCs per 100,000 licensed drivers are observed across the study period. For the same period, the monthly rate of RBTs per 1000 licensed drivers is observed to be decreasing across the study with the results of the analysis revealing no significant variations in the data. The comparison between Western Australia and Queensland shows that Queensland's ARTC monthly percent change (MPC) is 0.014 compared to the MPC of 0.47 for Western Australia. While Queensland maintains a relatively flat ARTC rate, the ARTC rate in Western Australia is increasing. Our analysis reveals an inverse relationship between ARTC RBT rates, that for every 10% increase in the percentage of RBTs to licensed driver there is a 0.15 decrease in the rate of ARTCs per 100,000 licenced drivers. Moreover, in Western Australia, if the 2011 ratio of 1:2 (RBTs to annual number of licensed drivers) were to double to a ratio of 1:1, we estimate the number of monthly ARTCs would reduce by approximately 15. Based on these findings we believe that as the number of RBTs conducted increases the number of drivers willing to risk being detected for drinking driving decreases, because the perceived risk of being detected is considered greater. This is turn results in the number of ARTCs diminishing. The results of this study provide an important evidence base for policy decisions for RBT operations.

The importance of reporting housing and husbandry in rat research

In 1963, the National Institutes of Health (NIH) first issued guidelines for animal housing and husbandry. The most recent 2010 revision emphasizes animal care “in ways judged to be scientifically, technically, and humanely appropriate” (National Institutes of Health, 2010, p. XIII). The goal of these guidelines is to ensure humanitarian treatment of animals and to optimize the quality of research. Although these animal care guidelines cover a substantial amount of information regarding animal housing and husbandry, researchers generally do not report all these variables (see Table ​Table1).1). The importance of housing and husbandry conditions with respect to standardization across different research laboratories has been debated previously (Crabbe et al., 1999; Van Der Staay and Steckler, 2002; Wahlsten et al., 2003; Wolfer et al., 2004; Van Der Staay, 2006; Richter et al., 2010, 2011). This paper focuses on several animal husbandry and housing issues that are particularly relevant to stress responses in rats, including transportation, handling, cage changing, housing conditions, light levels and the light–dark cycle. We argue that these key animal housing and husbandry variables should be reported in greater detail in an effort to raise awareness about extraneous experimental variables, especially those that have the potential to interact with the stress response.

Community night patrols in the Northern Territory : toward an improved performance and reporting framework

This Technical and Background Paper summarises the results of a Australian Government Attorney-General’s Department’s funded project. The project aimed to clarify the contribution of the community night patrol program in the Northern Territory (NT) to improving the community safety of Indigenous communities. The paper recommends an improved framework for monitoring performance and reporting. Community night patrols or similar services operate in many other areas of Australia and internationally. The paper concludes that the core business of community night patrols is (non-crisis) crime prevention not defacto policing. It also concludes that an unrecognised outcome of patrols is capturing and sharing local knowledge about community safety issues and solutions. Over time, community night patrols should focus on working with other services to reduce the need for repeat assistance to persons at risk and for risky incidents. The recently released Northern Territory Emergency Response Evaluation Report (2011) confirmed that communities and service providers surveyed largely support night patrols, but better data is required to more comprehensively assess their performance.

Consequences of introducing mandatory reporting legislation for child sexual abuse

To improve detection of child sexual abuse, many jurisdictions have enacted mandatory reporting laws requiring selected persons to report known and suspected cases. In Ireland, the Child First approach previously incorporated only a policy-based approach to reporting. Due to a perceived lack of efficacy, the Children First Bill was drafted in 2012 to shift this policy guidance to a legislative approach. What effects will the new legislative reporting duties have on numbers of reports, and outcomes of reports, of suspected child sexual abuse? This paper will shed light on these important questions by presenting results of analyses of the introduction of legislative reporting obligations in two Australian States. Three questions will be explored: 1. Does introducing reporting legislation result in enhanced detection of child sexual abuse? 2. Do different reporter groups have different patterns of reporting? 3. What do the patterns of report numbers and outcomes indicate for child protection systems and communities?

Elementary teachers’ knowledge of legislative and policy duties for reporting child sexual abuse

This study examined elementary school teachers’ knowledge of their legislative and policy-based reporting duties with respect to child sexual abuse. Data were collected from 470 elementary school teachers from urban and rural government and nongovernment schools in 3 Australian states, which at the time of the study had 3 different legislative reporting duties for teachers. Teachers completed the 8-part Teacher Reporting Questionnaire (TRQ). Multinomial logistic regression analysis was used to determine factors associated with (a) teachers’ legislation knowledge and (b) teachers’ policy knowledge. Teachers with higher levels of knowledge had a combination of pre- and in-service training about child sexual abuse and more positive attitudes toward reporting, held administration positions in their school, and had reported child sexual abuse at least once during their teaching career. They were also more likely to work in the state with the strongest legislative reporting duty, which had been in place the longest.

Development of the child abuse and neglect reporting self-efficacy questionnaire for nurses

Taiwan nurses are mandated to report known or suspected child abuse and neglect (CAN), and self-efficacy is known to have an important influence on professional behaviors. The aim of this study was to develop and test the CAN reporting self-efficacy (CANRSE) scale as a measure of nurses’ self-efficacy to report CAN. A sample of 496 nurses from Southern Taiwanese hospitals used the CANRSE scale. The psychometric evaluation of the scale included content validity, exploratory and confirmatory factor analyses, convergent validity, as well as Cronbach’s α and test−retest reliability. Satisfactory internal consistency (Cronbach’s α = 0.92) and test−retest reliability were demonstrated. Confirmatory factor analysis supported the proposed models as having acceptable model fit. Exploratory factor analysis and regression analyses showed that the CANRSE scale had good construct validity and criterion-related validity, respectively. Convergent validity was tested using the general self-efficacy scale and was found to be satisfactory (r = 0.53). The results indicate the CANRSE is reliable and valid, and further testing of its predictive validity is recommended. It can be used to examine the influence of professional self-efficacy in recognizing and reporting CAN cases and to evaluate the impact of training programs aimed at improving CAN reporting.