Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

Bluetooth vehicle trajectory by fusing Bluetooth and loops : motorway travel time statistics

Loop detectors are widely used on the motorway networks where they provide point speed and traffic volumes. Models have been proposed for temporal and spatial generalization of speed for average travel time estimation. Advancement in technology provides complementary data sources such as Bluetooth MAC Scanner (BMS), detecting the MAC ID of the Bluetooth devices transported by the traveller. Matching the data from two BMS stations provides individual vehicle travel time. Generally, on the motorways loops are closely spaced, whereas BMS are placed few kilometres apart. In this research, we fuse BMSs and loops data to define the trajectories of the Bluetooth vehicles. The trajectories are utilised to estimate the travel time statistics between any two points along the motorway. The proposed model is tested using simulation and validated with real data from Pacific motorway, Brisbane. Comparing the model with the linear interpolation based trajectory provides significant improvements.

Improving safety for driverless city vehicles : real-time communication and decision making

This paper elaborates on the Cybercars-2 Wireless Communication Framework for driverless city vehicles, which is used for Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication. The developed framework improves the safety and efficiency of driverless city vehicles. Furthermore, this paper also elaborates on the vehicle control software architecture. On-road tests of both the communication framework and its application for real-time decision making show that the communication framework is reliable and useful for improving the safe operation of driverless city vehicles.

Public transport travel time variability definitions and monitoring

Public Transport Travel Time Variability (PTTV) is essential for understanding the deteriorations in the reliability of travel time, optimizing transit schedules and route choices. This paper establishes the key definitions of PTTV in which firstly include all buses, and secondly include only a single service from a bus route. The paper then analyzes the day-to-day distribution of public transport travel time by using Transit Signal Priority data. A comprehensive approach, using both parametric bootstrapping Kolmogorov-Smirnov test and Bayesian Information Creation technique is developed, recommends Lognormal distribution as the best descriptor of bus travel time on urban corridors. The probability density function of Lognormal distribution is finally used for calculating probability indicators of PTTV. The findings of this study are useful for both traffic managers and statisticians for planning and analyzing the transit systems.

Towards increased road safety : real-time decision making for driverless city vehicles

This work elaborates on the topic of decision making for driverless city vehicles, particularly focusing on the aspects on how to develop a reliable approach which meets the requirements of safe city traffic. Decision making in this context refers to the problem of identifying the most appropriate driving maneuver to be performed in a given traffic situation. The overall decision making problem is decomposed into two consecutive stages. The first stage is safety-crucial, representing the decision regarding the set of feasible driving maneuvers. The second stage represents the decision regarding the most appropriate driving maneuver from the set of feasible ones. The developed decision making approach has been implemented in C++ and initially tested in a 3D simulation environment and, thereafter, in real-world experiments. The real-world experiments also included the integration of wireless communication between vehicles.

Time course analysis of hypoxia, granulation tissue and blood vessel growth, and remodeling in healing rat cutaneous incisional primary intention wounds

Hypoxia and the development and remodeling of blood vessels and connective tissue in granulation tissue that forms in a wound gap following full-thickness skin incision in the rat were examined as a function of time. A 1.5 cm-long incisional wound was created in rat groin skin and the opposed edges sutured together. Wounds were harvested between 3 days and 16 weeks and hypoxia, percent vascular volume, cell proliferation and apoptosis, α-smooth muscle actin, vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 expression in granulation tissue were then assessed. Hypoxia was evident between 3 and 7 days while maximal cell proliferation at 3 days (123.6 ± 22.2 cells/mm 2, p < 0.001 when compared with normal skin) preceded the peak percent vascular volume that occurred at 7 days (15.83 ± 1.10%, p < 0.001 when compared with normal skin). The peak in cell apoptosis occurred at 3 weeks (12.1 ± 1.3 cells/mm 2, p < 0.001 when compared with normal skin). Intense α-smooth muscle actin labeling in myofibroblasts was evident at 7 and 10 days. Vascular endothelial growth factor receptor-2 and vascular endothelial growth factor-A were detectable until 2 and 3 weeks, respectively, while transforming growth factor-β 1 protein was detectable in endothelial cells and myofibroblasts until 3-4 weeks and in the extracellular matrix for 16 weeks. Incisional wound granulation tissue largely developed within 3-7 days in the presence of hypoxia. Remodeling, marked by a decline in the percent vascular volume and increased cellular apoptosis, occurred largely in the absence of detectable hypoxia. The expression of vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 is evident prior, during, and after the peak of vascular volume reflecting multiple roles for these factors during wound healing.

Connecting people to their resource consumption through real-time data visualisations

Combining human-computer interaction and urban informatics, this design research developed and tested novel interfaces offering users real-time feedback on their paper and energy consumption. Findings from deploying these interfaces in both domestic and office environments in Australia, the UK, and Ireland, will innovate future generations of resource monitoring technologies. The study draws conclusions with implications for government policy, the energy industry, and sustainability researchers.

Time pressure and coworker support mediate the curvilinear relationship between age and occupational well-being

As the proportion of older employees in the workforce is growing, researchers have become increasingly interested in the association between age and occupational well-being. The curvilinear nature of relationships between age and job satisfaction and between age and emotional exhaustion is well-established in the literature, with employees in their late 20s to early 40s generally reporting lower levels of occupational well-being than younger and older employees. However, the mechanisms underlying these curvilinear relationships are so far not well understood due to a lack of studies testing mediation effects. Based on an integration of role theory and research from the adult development and career literatures, this study examined time pressure, work–home conflict, and coworker support as mediators of the relationships between age and job satisfaction and between age and emotional exhaustion. Data came from 771 employees between 17 and 74 years of age in the construction industry. Results showed that employees in their late 20s to early 40s had lower job satisfaction and higher emotional exhaustion than younger and older employees. Time pressure and coworker support fully mediated both the U-shaped relationship between age and job satisfaction and the inversely U-shaped relationship between age and emotional exhaustion. These findings suggest that organizational interventions may help increase the relatively low levels of occupational well-being in certain age groups.

An application of an extended theory of planned behaviour to understand drivers' compliance with the school zones speed limit in Australia and Malaysia

This research investigated individual and situational factors that influence driver compliance with the school zones speed limit in Australia and Malaysia. Despite all the countermeasures implemented in these two countries, driver compliance with the speed limit in school zones is still poor. The findings of the research provided support for the application of the Theory of Planned Behaviour to understand and therefore influence drivers' intention to comply with the school zones speed limit in both Australia and Malaysia. The research also revealed that mindfulness, a construct rarely used in road safety before, directly influenced Australian drivers' intention to comply, while habit influenced intention to comply in Malaysia. The research raised important theoretical and cross-cultural issues for future research and highlighted the need to increase the visibility of school zones with the use of more noticeable traffic control devices.

The impacts of variable speed limit on speed variation and headway distribution

This thesis investigates the impacts of variable speed limit on motorway speed variation and headway distribution. Initiative techniques of traffic flow categorisation study contribute in analysing the effects of variable speed limit on various traffic states. The project focuses on the speed harmonisation impacts within and across lanes as well as the uniformity of headway spread in the application of variable speed limit.

Duty in the time of epidemics : what China and Zimbabwe teach us

In November 2002, a man with ‘atypical pneumonia’ treated in Foshan hospital, Guangdong Province, in the People's Republic of China, was the first known case of Severe Acute Respiratory Syndrome (SARS). However, it was not until April 2003 that the Chinese government admitted to the full scale of ‘atypical pneumonia’ cases infected with SARS, two months after the disease had rapidly spread across the world with initial infections in Hong Kong and Vietnam sourced to Guangdong. In 2008, Zimbabwe experienced one of the biggest outbreaks of cholera ever recorded. By February 2009, the disease had spread across all of Zimbabwe's 10 provinces and to neighbouring countries—Botswana, South Africa, Zambia and Mozambique—causing thousands of infections amongst their populations. This article seeks to examine what duties the Chinese and Zimbabwe states had to protect their citizens and the international community from these outbreaks. The article refers to the findings of the International Law Commission's study into the role of states and international organisations in protecting persons in the event of a disaster to consider whether there is an international duty to protect persons from epidemics. The article concludes that both cases reveal a growing concept of protection that entails an international duty to assist individuals when an affected state proves unwilling or unable to assist its own population in the event of a disease outbreak.

Overexpression of the kiwifruit SVP3 gene affects reproductive development and suppresses anthocyanin biosynthesis in petals, but has no effect on vegetative growth, dormancy, or flowering time

SVP-like MADS domain transcription factors have been shown to regulate flowering time and both inflorescence and flower development in annual plants, while having effects on growth cessation and terminal bud formation in perennial species. Previously, four SVP genes were described in woody perennial vine kiwifruit (Actinidia spp.), with possible distinct roles in bud dormancy and flowering. Kiwifruit SVP3 transcript was confined to vegetative tissues and acted as a repressor of flowering as it was able to rescue the Arabidopsis svp41 mutant. To characterize kiwifruit SVP3 further, ectopic expression in kiwifruit species was performed. Ectopic expression of SVP3 in A. deliciosa did not affect general plant growth or the duration of endodormancy. Ectopic expression of SVP3 in A. eriantha also resulted in plants with normal vegetative growth, bud break, and flowering time. However, significantly prolonged and abnormal flower, fruit, and seed development were observed, arising from SVP3 interactions with kiwifruit floral homeotic MADS-domain proteins. Petal pigmentation was reduced as a result of SVP3-mediated interference with transcription of the kiwifruit flower tissue-specific R2R3 MYB regulator, MYB110a, and the gene encoding the key anthocyanin biosynthetic step, F3GT1. Constitutive expression of SVP3 had a similar impact on reproductive development in transgenic tobacco. The flowering time was not affected in day-neutral and photoperiod-responsive Nicotiana tabacum cultivars, but anthesis and seed germination were significantly delayed. The accumulation of anthocyanin in petals was reduced and the same underlying mechanism of R2R3 MYB NtAN2 transcript reduction was demonstrated.

A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples

A new test of hypothesis for classifying stationary time series based on the bias-adjusted estimators of the fitted autoregressive model is proposed. It is shown theoretically that the proposed test has desirable properties. Simulation results show that when time series are short, the size and power estimates of the proposed test are reasonably good, and thus this test is reliable in discriminating between short-length time series. As the length of the time series increases, the performance of the proposed test improves, but the benefit of bias-adjustment reduces. The proposed hypothesis test is applied to two real data sets: the annual real GDP per capita of six European countries, and quarterly real GDP per capita of five European countries. The application results demonstrate that the proposed test displays reasonably good performance in classifying relatively short time series.

Polarization of forecast densities : a new approach to time series classification

Time series classification has been extensively explored in many fields of study. Most methods are based on the historical or current information extracted from data. However, if interest is in a specific future time period, methods that directly relate to forecasts of time series are much more appropriate. An approach to time series classification is proposed based on a polarization measure of forecast densities of time series. By fitting autoregressive models, forecast replicates of each time series are obtained via the bias-corrected bootstrap, and a stationarity correction is considered when necessary. Kernel estimators are then employed to approximate forecast densities, and discrepancies of forecast densities of pairs of time series are estimated by a polarization measure, which evaluates the extent to which two densities overlap. Following the distributional properties of the polarization measure, a discriminant rule and a clustering method are proposed to conduct the supervised and unsupervised classification, respectively. The proposed methodology is applied to both simulated and real data sets, and the results show desirable properties.