The challenge of developing a fleet driving risk assessment tool: What can be learned from the process?

One of the riskiest activities in the course of a person's work is driving. By developing and testing a new work driving risk assessment measurement tool for use by organisations this research will contribute to the safety of those who drive for work purposes. The research results highlighted limitations associated with current self-report measures and provided evidence that the work driving environment is extremely complex and involves constant interactions between humans, vehicles, the road environment, and the organisational context.

Addressing the road trauma burden in China: Exploring attitudes, behaviours, risk perceptions and cultural uniqueness

As China continues to motorise rapidly, solutions are needed to reduce the burden of road trauma that is spread inequitably across the community. Little is currently known about how new drivers are trained to deal with on-road challenges, and little is also known about the perceptions, behaviours and attitudes of road users in China. This paper reports on a pilot study conducted in a driver retraining facility in one Chinese city where people who have had their licence suspended for accrual of 12 demerit points in a one year period must attend compulsory retraining in order to regain their licence. A sample of 239 suspended drivers responded to an anonymous questionnaire that sought information about preferred driving speeds and perceptions of safe driving speeds across two speed zones. Responses indicated that speeds higher than the posted limits were commonly reported, and that there was incongruence between preferred and safe speeds, such that a greater proportion of drivers reported preferred speeds that were substantially faster than what were reported as safe speeds. Participants with more driving experience reported significantly fewer crashes than newly licensed drivers (less than 2 years licensed) but no differences were found in offences when compared across groups with different levels of driving experience. Perceptions of risky behaviours were assessed by asking participants to describe what they considered to be the most dangerous on-road behaviours. Speeding and drink driving were the most commonly reported by far, followed by issues such as fatigue, ignoring traffic rules, not obeying traffic rules, phone use while driving, and non-use of seatbelts, which attracted an extremely low response which seems consistent with previously reported low belt wearing rates, unfavourable attitudes towards seatbelt use, and low levels of enforcement. Finally, observations about culturally specific considerations are made from previous research conducted by the authors and others. Specifically, issues of saving face and the importance and pervasiveness of social networks and social influence are discussed with particular regard to how any future countermeasures need to be informed by a thorough understanding of Chinese customs and culture.

Assessment of the risk of failure of high voltage substations due to environmental conditions and pollution on insulators

Pollution on electrical insulators is one of the greatest causes of failure of substations subjected to high levels of salinity and environmental pollution. Considering leakage current as the main indicator of pollution on insulators, this paper focus on establishing the effect of the environmental conditions on the risk of failure due to pollution on insulators and determining the significant change in the magnitude of the pollution on the insulators during dry and humid periods. Hierarchical segmentation analysis was used to establish the effect of environmental conditions on the risk of failure due to pollution on insulators. The Kruskal-Wallis test was utilized to determine the significant changes in the magnitude of the pollution due to climate periods. An important result was the discovery that leakage current was more common on insulators during dry periods than humid ones. There was also a higher risk of failure due to pollution during dry periods. During the humid period, various temperatures and wind directions produced a small change in the risk of failure. As a technical result, operators of electrical substations can now identify the cause of an increase in risk of failure due to pollution in the area. The research provides a contribution towards the behaviour of the leakage current under conditions similar to those of the Colombian Caribbean coast and how they affect the risk of failure of the substation due to pollution.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Crash risk perception of sleepy driving and its comparisons with drink driving and speeding: Which behavior is perceived as the riskiest?

- Objective Driver sleepiness is a major crash risk factor, but may be under-recognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding. - Methods In total, 300 Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants perception of crash risk was assessed for five different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, night-time) of driving. - Results The analysis confirmed that sleepy driving was considered a risky driving behavior, but not as risky as high levels of speeding (p < .05). Yet, the risk of crashing at 4 am was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky due to time of day/circadian influences were not reported as high risk. - Conclusions The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long distance driving and driver sleepiness. Further efforts are required to improve the community’s awareness of the impairing effects from sleepiness and in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.

Spontaneous and episodic volunteers: The legislative, insurance and risk management framework

Baby Boomers are a generation of life long association joiners, but following generations prefer spontaneous and episodic volunteering. This trend is apparent not only during natural disasters, but in most other spheres of volunteering. Legal liability for such volunteers is a growing concern, which unresolved, may dampen civic participation. We critically examine the current treatment of these liabilities through legislation, insurance and risk management.

Predicting occupant risk indicators for frontal impacts with redirective crash cushions

Crash cushions are devices deployed on the road network in order to shield fixed roadside hazards and the non-crashworthy ends of road safety barriers. However crash cushions vary in terms of configuration and operation, meaning that different devices may also vary in terms of ability to mitigate occupant risk. In this study, data derived from crash testing of eleven redirective crash cushions is used as the base input to a numerical procedure for calculation of occupant risk indicators Occupant Impact Velocity (OIV), Occupant Ridedown Acceleration (ORA) and longitudinal Acceleration Severity Index (ASI) for a range of simulated impacting vehicles (mass 800 kg to 2,500 kg) impacting each crash cushion at a range of impact speeds (18 m/s to 32 m/s). The results may be interpreted as demonstrating firstly that enhanced knowledge of the performance of a device over a range of impact conditions, i.e., beyond the crash testing, may assist in determining the crash cushion most suited to a particular application; secondly that a more appropriate conformance test for occupant risk would be a frontal impact by a small (light) vehicle travelling parallel to and aligned with the centreline of the crash cushion; and thirdly that current documented numerical procedures for calculating occupant risk indicators may require review.

Fatigued driving : prevalence, risk factors and groups, and the law

Fatigue and sleepiness are major causes of road traffic accidents. However, precise data is often lacking because a validated and reliable device for detecting the level of sleepiness (cf. the breathalyzer for alcohol levels) does not exist, nor does criteria for the unambiguous detection of fatigue/sleepiness as a contributing factor in accident causation. Therefore, identification of risk factors and groups might not always be easy. Furthermore, it is extremely difficult to incorporate fatigue in operationalized terms into either traffic or criminal law. The main aims of this thesis were to estimate the prevalence of fatigue problems while driving among the Finnish driving population, to explore how VALT multidisciplinary investigation teams, Finnish police, and courts recognize (and prosecute) fatigue in traffic, to identify risk factors and groups, and finally to explore the application of the Finnish Road Traffic Act (RTA), which explicitly forbids driving while tired in Article 63. Several different sources of data were used: a computerized database and the original folders of multidisciplinary teams investigating fatal accidents (VALT), the driver records database (AKE), prosecutor and court decisions, a survey of young male military conscripts, and a survey of a representative sample of the Finnish active driving population. The results show that 8-15% of fatal accidents during 1991-2001 were fatigue related, that every fifth Finnish driver has fallen asleep while driving at some point during his/her driving career, and that the Finnish police and courts punish on average one driver per day on the basis of fatigued driving (based on the data from the years 2004-2005). The main finding regarding risk factors and risk groups is that during the summer months, especially in the afternoon, the risk of falling asleep while driving is increased. Furthermore, the results indicate that those with a higher risk of falling asleep while driving are men in general, but especially young male drivers including military conscripts and the elderly during the afternoon hours and the summer in particular; professional drivers breaking the rules about duty and rest hours; and drivers with a tendency to fall asleep easily. A time-of-day pattern of sleep-related incidents was repeatedly found. It was found that VALT teams can be considered relatively reliable when assessing the role of fatigue and sleepiness in accident causation; thus, similar experts might be valuable in the court process as expert witnesses when fatigue or sleepiness are suspected to have a role in an accident’s origins. However, the application of Article 63 of the RTA that forbids, among other things, fatigued driving will continue to be an issue that deserves further attention. This should be done in the context of a needed attitude change towards driving while in a state of extreme tiredness (e.g., after being awake for more than 24 hours), which produces performance deterioration comparable to illegal intoxication (BAC around 0.1%). Regarding the well-known interactive effect of increased sleepiness and even small alcohol levels, the relatively high proportion (up to 14.5%) of Finnish drivers owning and using a breathalyzer raises some concern. This concern exists because these drivers are obviously more focused on not breaking the “magic” line of 0.05% BAC than being concerned about driving impairment, which might be much worse than they realize because of the interactive effects of increased sleepiness and even low alcohol consumption. In conclusion, there is no doubt that fatigue and sleepiness problems while driving are common among the Finnish driving population. While we wait for the invention of reliable devices for fatigue/sleepiness detection, we should invest more effort in raising public awareness about the dangerousness of fatigued driving and educate drivers about how to recognize and deal with fatigue and sleepiness when they ultimately occur.

Application of a model to assess aflatoxin risk in peanuts.

When exposed to hot (22-35 degrees C) and dry climatic conditions in the field during the final 4-6 weeks of pod filling, peanuts (Arachis hypogaea L.) can accumulate highly carcinogenic and immuno-suppressing aflatoxins. Forecasting of the risk posed by these conditions can assist in minimizing pre-harvest contamination. A model was therefore developed as part of the Agricultural Production Systems Simulator (APSIM) peanut module, which calculated an aflatoxin risk index (ARI) using four temperature response functions when fractional available soil water was <0.20 and the crop was in the last 0.40 of the pod-filling phase. ARI explained 0.95 (P <= 0.05) of the variation in aflatoxin contamination, which varied from 0 to c. 800 mu g/kg in 17 large-scale sowings in tropical and four sowings in sub-tropical environments carried out in Australia between 13 November and 16 December 2007. ARI also explained 0.96 (P <= 0.01) of the variation in the proportion of aflatoxin-contaminated loads (>15 mu g/kg) of peanuts in the Kingaroy region of Australia during the period between the 1998/99 and 2007/08 seasons. Simulation of ARI using historical climatic data from 1890 to 2007 indicated a three-fold increase in its value since 1980 compared to the entire previous period. The increase was associated with increases in ambient temperature and decreases in rainfall. To facilitate routine monitoring of aflatoxin risk by growers in near real time, a web interface of the model was also developed. The ARI predicted using this interface for eight growers correlated significantly with the level of contamination in crops (r=095, P <= 0.01). These results suggest that ARI simulated by the model is a reliable indicator of aflatoxin contamination that can be used in aflatoxin research as well as a decision-support tool to monitor pre-harvest aflatoxin risk in peanuts.

ACIAR Feasibility of farmers managing climate related crop production risk in India

Validation of new Indian seasonal climate forecasting products. In the Indian state of Andhra Pradesh (AP) kharif crops are heavily dependent on summer monsoon rains, where the timing and intensity of the rains affects crop yield. The majority of farms in AP are small and marginal, making them very vulnerable to yield reductions. Farmers also lack access to relevant information that might enable them to respond to seasonal conditions. Enabling farmers to utilise seasonal climate forecasting would allow them to respond to seasonal variability. To do this, farmers need a forecasting system that indicates a specific management strategy for the upcoming season, and effective and timely communication of the forecast information. Current agro-meteorological advisories in AP are issued on a bi-weekly basis, and they are relevant to an agro-climatic zone scale which may not be sufficiently relevant at a village level. Also, the information in the advisories may not be necessarily packaged in way relevant to cropping decisions by farmers. The objectives of this project are to evaluate the skill of seasonal climate forecasts to be issued for the 2008 monsoon season, to assess crop management options in response to seasonal scenarios that capture the range of seasonal climatic variability, to develop and evaluate options for effective communication and adoption of climate forecasts and agricultural advisories, and to synthesise and report on options for future research investments into seasonal climate forecasting.

Potential Distribution and Risk Assessment of an Invasive Plant Species: A Case Study of Hymenachne amplexicaulis in Australia

Given the limited resources available for weed management, a strategic approach is required to give the best bang for your buck. The current study incorporates: (1) a model ensemble approach to identify areas of uncertainty and commonality regarding a species invasive potential, (2) current distribution of the invaded species, and (3) connectivity of systems to identify target regions and focus efforts for more effective management. Uncertainty in the prediction of suitable habitat for H. amplexicaulis (study species) in Australia was addressed in an ensemble-forecasting approach to compare distributional scenarios from four models (CLIMATCH; CLIMEX; boosted regression trees [BRT]; maximum entropy [Maxent]). Models were built using subsets of occurrence and environmental data. Catchment risk was determined through incorporating habitat suitability, the current abundance and distribution of H. amplexicaulis, and catchment connectivity. Our results indicate geographic differences between predictions of different approaches. Despite these differences a number of catchments in northern, central, and southern Australia were identified as high risk of invasion or further spread by all models suggesting they should be given priority for the management of H. amplexicaulis. The study also highlighted the utility of ensemble approaches in indentifying areas of uncertainty and commonality regarding the species invasive potential.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Option-Implied Preferences Adjustments and Risk-Neutral Density Forecasts

The main objective of this paper is to analyse the value of information contained in prices of options on the IBEX 35 index at the Spanish Stock Exchange Market. The forward looking information is extracted using implied risk-neutral density functions estimated by a mixture of two-lognormals and three alternative risk-adjustments: the classic power and exponential utility functions and a habit-based specification that allows for a counter-cyclical variation of risk aversion. Our results show that at four-week horizon we can reject the hypothesis that between October 1996 and March 2000 the risk-neutral densities provide accurate predictions of the distributions of future realisations of the IBEX 35 index at a four-week horizon. When forecasting through risk-adjusted densities the performance of this period is statistically improved and we no longer reject that hypothesis. All risk-adjusted densities generate similar forecasting statistics. Then, at least for a horizon of four-weeks, the actual risk adjustment does not seem to be the issue. By contrast, at the one-week horizon risk-adjusted densities do not improve the forecasting ability of the risk-neutral counterparts.

Wind-driven desertification: process modeling, remote monitoring, and forecasting

Arid and semiarid landscapes comprise nearly a third of the Earth's total land surface. These areas are coming under increasing land use pressures. Despite their low productivity these lands are not barren. Rather, they consist of fragile ecosystems vulnerable to anthropogenic disturbance.

The purpose of this thesis is threefold: (I) to develop and test a process model of wind-driven desertification, (II) to evaluate next-generation process-relevant remote monitoring strategies for use in arid and semiarid regions, and (III) to identify elements for effective management of the world's drylands.

In developing the process model of wind-driven desertification in arid and semiarid lands, field, remote sensing, and modeling observations from a degraded Mojave Desert shrubland are used. This model focuses on aeolian removal and transport of dust, sand, and litter as the primary mechanisms of degradation: killing plants by burial and abrasion, interrupting natural processes of nutrient accumulation, and allowing the loss of soil resources by abiotic transport. This model is tested in field sampling experiments at two sites and is extended by Fourier Transform and geostatistical analysis of high-resolution imagery from one site.

Next, the use of hyperspectral remote sensing data is evaluated as a substantive input to dryland remote monitoring strategies. In particular, the efficacy of spectral mixture analysis (SMA) in discriminating vegetation and soil types and detennining vegetation cover is investigated. The results indicate that hyperspectral data may be less useful than often thought in determining vegetation parameters. Its usefulness in determining soil parameters, however, may be leveraged by developing simple multispectral classification tools that can be used to monitor desertification.

Finally, the elements required for effective monitoring and management of arid and semiarid lands are discussed. Several large-scale multi-site field experiments are proposed to clarify the role of wind as a landscape and degradation process in dry lands. The role of remote sensing in monitoring the world's drylands is discussed in terms of optimal remote sensing platform characteristics and surface phenomena which may be monitored in order to identify areas at risk of desertification. A desertification indicator is proposed that unifies consideration of environmental and human variables.