In-vehicle avatars to elicit social response and change driving behaviour

Social and psychological theories have provided a plethora of evidence showing that the physical difficulty to express appropriate social interactions between drivers expresses itself in aggression, selfish driving and anti-social behaviour. Therefore there is a need to improve interactions between drivers and allow clearer collective decision making between them. Personal characteristics and the driving situations play strong roles in driver’s aggression. Our approach is centered around the driving situation as opposed to focusing on personality characteristics. It examines aggression and manipulates contextual variables such as driver’s eye contact exchanges. This paper presents a new unobtrusive in-vehicle system that aims at communicating drivers��� intentions, elicit social responses and increasing mutual awareness. It uses eye gaze as a social cue to affect collective decision making with the view to contribute to safe driving. The authors used a driving simulator to design a case control experiment in which eye gaze movements are conveyed with an avatar. Participants were asked to drive through different types of intersections. An avatar representing the head of the other driver was displayed and driver behaviour was analysed. Significant eye gaze pattern difference where observed when an avatar was displayed. Drivers cautiously refer to the avatar when information is required on the intention of others (e.g. when they do not have the right of way). The majority of participants reported the perception of “being looked at”. The number of glances and time spent gazing at the avatar did not indicate an unsafe distraction by standards of in-vehicle device ergonomic design. Avatars were visually consulted primarily in less demanding driving situations, which underlines their non-distractive nature.

Head and eye movements and lane keeping in drivers with hemianopia and quadrantanopia compared to controls

Purpose: To compare the eye and head movements and lane-keeping of drivers with hemianopia and quadrantanopia with that of age-matched controls when driving under real world conditions. Methods: Participants included 22 hemianopes and 8 quadrantanopes (M age 53 yrs) and 30 persons with normal visual fields (M age 52 yrs) who were ≥ 6 months from the brain injury date and either a current driver or aiming to resume driving. All participants drove an instrumented dual-brake vehicle along a 14-mile route in traffic that included non-interstate city driving and interstate driving. Driving performance was scored using a standardised assessment system by two “backseat” raters and the Vigil Vanguard system which provides objective measures of speed, braking and acceleration, cornering, and video-based footage from which eye and head movements and lane-keeping can be derived. Results: As compared to drivers with normal visual fields, drivers with hemianopia or quadrantanopia on average were significantly more likely to drive slower, to exhibit less excessive cornering forces or acceleration, and to execute more shoulder movements off the seat. Those hemianopic and quadrantanopic drivers rated as safe to drive by the backseat evaluator made significantly more excursive eye movements, exhibited more stable lane positioning, less sudden braking events and drove at higher speeds than those rated as unsafe, while there was no difference between safe and unsafe drivers in head movements. Conclusions: Persons with hemianopic and quadrantanopic field defects rated as safe to drive have different driving characteristics compared to those rated as unsafe when assessed using objective measures of driving performance.

High Court changes position on standard of care of learner drivers

Since the High Court decision of Cook v Cook (1986) 162 CLR 376, a person who voluntarily undertakes to instruct a learner driver of a motor vehicle is owed a lower standard of care than that owed to other road users. The standard of care was still expressed to be objective; however, it took into account the inexperience of the learner driver. Therefore, a person instructing a learner driver was owed a duty of care the standard being that of a reasonable learner driver. This ‘special relationship’ was said to exist because of the passenger’s knowledge of the driver’s inexperience and lack of skill. On 28 August 2008 the High Court handed down its decision in Imbree v McNeilly [2008] HCA 40, overruling Cook v Cook.

Autonomous deployment and repair of a sensor network using an unmanned aerial vehicle

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or for command and control in emergency situations. We describe in detail the algorithms used for deployment and for measuring network connectivity and provide experimental data we collected from field trials. A particular focus is on determining gaps in connectivity of the deployed network and generating a plan for a second, repair, pass to complete the connectivity. This project is the result of a collaboration between three robotics labs (CSIRO, USC, and Dartmouth.).

Analysis and detection of cognitive load and frustration in drivers' speech

Non-driving related cognitive load and variations of emotional state may impact a driver’s capability to control a vehicle and introduces driving errors. Availability of reliable cognitive load and emotion detection in drivers would benefit the design of active safety systems and other intelligent in-vehicle interfaces. In this study, speech produced by 68 subjects while driving in urban areas is analyzed. A particular focus is on speech production differences in two secondary cognitive tasks, interactions with a co-driver and calls to automated spoken dialog systems (SDS), and two emotional states during the SDS interactions - neutral/negative. A number of speech parameters are found to vary across the cognitive/emotion classes. Suitability of selected cepstral- and production-based features for automatic cognitive task/emotion classification is investigated. A fusion of GMM/SVM classifiers yields an accuracy of 94.3% in cognitive task and 81.3% in emotion classification.

The Green Falcon - Solar Powered Unmanned Aerial Vehicle

In recent months the extremes of Australia’s weather have affected, killed a good number of people and millions of dollars lost. Contrary to a manned aircraft or a helicopter; which have restricted air time, a UAS or a group of UAS could provide 24 hours coverage of the disaster area and be instrumented with infrared cameras to locate distressed people and relay information to emergency services. The solar powered UAV is capable of carrying a 0.25Kg payload consuming 0.5 watt and fly continuously for at low altitude for 24 hrs ,collect the data and create a special distribution . This system, named Green Falcon, is fully autonomous in navigation and power generation, equipped with solar cells covering its wing, it retrieves energy from the sun in order to supply power to the propulsion system and the control electronics, and charge the battery with the surplus of energy. During the night, the only energy available comes from the battery, which discharges slowly until the next morning when a new cycle starts. The prototype airplane was exhibited at the Melbourne Museum form Nov09 to Feb 2010.

The risky behaviour of young drivers : developing a measurement tool

The contribution of risky behaviour to the increased crash and fatality rates of young novice drivers is recognised in the road safety literature around the world. Exploring such risky driver behaviour has led to the development of tools like the Driver Behaviour Questionnaire (DBQ) to examine driving violations, errors, and lapses [1]. Whilst the DBQ has been utilised in young novice driver research, some items within this tool seem specifically designed for the older, more experienced driver, whilst others appear to asses both behaviour and related motives. The current study was prompted by the need for a risky behaviour measurement tool that can be utilised with young drivers with a provisional driving licence. Sixty-three items exploring young driver risky behaviour developed from the road safety literature were incorporated into an online survey. These items assessed driver, passenger, journey, car and crash-related issues. A sample of 476 drivers aged 17-25 years (M = 19, SD = 1.59 years) with a provisional driving licence and matched for age, gender, and education were drawn from a state-wide sample of 761 young drivers who completed the survey. Factor analysis based upon a principal components extraction of factors was followed by an oblique rotation to investigate the underlying dimensions to young novice driver risky behaviour. A five factor solution comprising 44 items was identified, accounting for 55% of the variance in young driver risky behaviour. Factor 1 accounted for 32.5% of the variance and appeared to measure driving violations that were transient in nature - risky behaviours that followed risky decisions that occurred during the journey (e.g., speeding). Factor 2 accounted for 10.0% of variance and appeared to measure driving violations that were fixed in nature; the risky decisions being undertaken before the journey (e.g., drink driving). Factor 3 accounted for 5.4% of variance and appeared to measure misjudgment (e.g., misjudged speed of oncoming vehicle). Factor 4 accounted for 4.3% of variance and appeared to measure risky driving exposure (e.g., driving at night with friends as passengers). Factor 5 accounted for 2.8% of variance and appeared to measure driver emotions or mood (e.g., anger). Given that the aim of the study was to create a research tool, the factors informed the development of five subscales and one composite scale. The composite scale had a very high internal consistency measure (Cronbach’s alpha) of .947. Self-reported data relating to police-detected driving offences, their crash involvement, and their intentions to break road rules within the next year were also collected. While the composite scale was only weakly correlated with self-reported crashes (r = .16, p < .001), it was moderately correlated with offences (r = .26, p < .001), and highly correlated with their intentions to break the road rules (r = .57, p < .001). Further application of the developed scale is needed to confirm the factor structure within other samples of young drivers both in Australia and in other countries. In addition, future research could explore the applicability of the scale for investigating the behaviour of other types of drivers.

Predicting effects of monotony on driver’s vigilance

Monotony has been identified as a contributing factor to road crashes. Drivers��� ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks, such as driving on Australian rural roads, many of which are monotonous by nature. Highway design in particular attempts to reduce the driver’s task to a merely lane-keeping one. Such a task provides little stimulation and is monotonous, thus affecting the driver’s attention which is no longer directed towards the road. Inattention contributes to crashes, especially for professional drivers. Monotony has been studied mainly from the endogenous perspective (for instance through sleep deprivation) without taking into account the influence of the task itself (repetitiveness) or the surrounding environment. The aim and novelty of this thesis is to develop a methodology (mathematical framework) able to predict driver lapses of vigilance under monotonous environments in real time, using endogenous and exogenous data collected from the driver, the vehicle and the environment. Existing approaches have tended to neglect the specificity of task monotony, leaving the question of the existence of a “monotonous state” unanswered. Furthermore the issue of detecting vigilance decrement before it occurs (predictions) has not been investigated in the literature, let alone in real time. A multidisciplinary approach is necessary to explain how vigilance evolves in monotonous conditions. Such an approach needs to draw on psychology, physiology, road safety, computer science and mathematics. The systemic approach proposed in this study is unique with its predictive dimension and allows us to define, in real time, the impacts of monotony on the driver’s ability to drive. Such methodology is based on mathematical models integrating data available in vehicles to the vigilance state of the driver during a monotonous driving task in various environments. The model integrates different data measuring driver’s endogenous and exogenous factors (related to the driver, the vehicle and the surrounding environment). Electroencephalography (EEG) is used to measure driver vigilance since it has been shown to be the most reliable and real time methodology to assess vigilance level. There are a variety of mathematical models suitable to provide a framework for predictions however, to find the most accurate model, a collection of mathematical models were trained in this thesis and the most reliable was found. The methodology developed in this research is first applied to a theoretically sound measure of sustained attention called Sustained Attention Response to Task (SART) as adapted by Michael (2010), Michael and Meuter (2006, 2007). This experiment induced impairments due to monotony during a vigilance task. Analyses performed in this thesis confirm and extend findings from Michael (2010) that monotony leads to an important vigilance impairment independent of fatigue. This thesis is also the first to show that monotony changes the dynamics of vigilance evolution and tends to create a “monotonous state” characterised by reduced vigilance. Personality traits such as being a low sensation seeker can mitigate this vigilance decrement. It is also evident that lapses in vigilance can be predicted accurately with Bayesian modelling and Neural Networks. This framework was then applied to the driving task by designing a simulated monotonous driving task. The design of such task requires multidisciplinary knowledge and involved psychologist Rebecca Michael. Monotony was varied through both the road design and the road environment variables. This experiment demonstrated that road monotony can lead to driving impairment. Particularly monotonous road scenery was shown to have the most impact compared to monotonous road design. Next, this study identified a variety of surrogate measures that are correlated with vigilance levels obtained from the EEG. Such vigilance states can be predicted with these surrogate measures. This means that vigilance decrement can be detected in a car without the use of an EEG device. Amongst the different mathematical models tested in this thesis, only Neural Networks predicted the vigilance levels accurately. The results of both these experiments provide valuable information about the methodology to predict vigilance decrement. Such an issue is quite complex and requires modelling that can adapt to highly inter-individual differences. Only Neural Networks proved accurate in both studies, suggesting that these models are the most likely to be accurate when used on real roads or for further research on vigilance modelling. This research provides a better understanding of the driving task under monotonous conditions. Results demonstrate that mathematical modelling can be used to determine the driver’s vigilance state when driving using surrogate measures identified during this study. This research has opened up avenues for future research and could result in the development of an in-vehicle device predicting driver vigilance decrement. Such a device could contribute to a reduction in crashes and therefore improve road safety.

Driver distractions: Characteristics underlying drivers' risk perceptions

Driver distraction is a research area that continues to receive considerable research interest but the drivers��� perspective is less well documented. The current research focuses on how drivers perceive the risks associated with a range of driver distractions with the aim of identifying features that contribute to their risk perception judgements. Multidimensional scaling analysis was employed to better understand drivers��� risk perceptions for 15 in-vehicle and external distractions. Results identify both salient qualitative characteristics that underpin drivers��� risk perceptions, such as the probability of a crash, as well as identify other features inherent in the distractions that may also contribute to risk perceptions. The implications of the results are discussed for better understanding drivers��� perceptions of distractions and the potential for improving road safety messages related to distracted driving.

Profiling the offence patterns of disqualified drink drivers in Queensland, Australia.

While unlicensed driving does not play a direct causative role in road crashes, it represents a major problem for road safety. A particular subgroup of concern is those offenders who continue to drive after having their licence disqualified for drink driving. Surveys of disqualified drivers suggest that driving among this group is relatively common. Method This paper reports findings from an analysis of the driving records of over 545,000 Queensland drivers who experienced a licence sanction between January 2003 and December 2008. The sample included drivers who were disqualified by a court (e.g., for drink driving); those who licence had been suspended administratively (e.g., for accumulation of demerit points); and those who were placed on a restricted licence. Results Overall, 95,461 of the drivers in the sample were disqualified from driving for a drink driving offence. During the period, these drivers were issued with a total of 2,644,619 traffic infringements with approximately 12% (n = 8, 095) convicted of a further drink driving offence while disqualified. Other traffic offences detected during this period including unlicensed driving (18%), driving an unregistered vehicle (27%), speeding (21%), dangerous driving (36%), mobile phone use (35%), non-restraint use (32%), and other moving violation (23%). Offending behaviour was more common among men than women. Conclusions While licence disqualification has previously been shown to be a relatively effective sanction for managing the behaviour of drink driving offenders, the results of the current study highlight that it is a far from perfect tool since many offenders continue to commit both drink driving and other traffic offences while disqualified. As such, this study highlights the ongoing need to enhance the detection of disqualified and unlicensed driving in order to deter this behaviour.

Risky driving or risky drivers? Exploring driving and crash histories of illegal street racing offenders

Illegal street racing has received increased attention in recent years from road safety professionals and the media as jurisdictions in Australia, Canada, and the United States have implemented laws to address the problem, which primarily involves young male drivers. Although some evidence suggests that the prevalence of illegal street racing is increasing, obtaining accurate estimates of the crash risk of this behavior is difficult because of limitations in official data sources. Although crash risk can be explored by examining the proportion of incidents of street racing that result in crashes, or the proportion of all crashes that involve street racing, this paper reports on the findings of a study that explored the riskiness of involved drivers. The driving histories of 183 male drivers with an illegal street racing conviction in Queensland, Australia, were compared with a random sample of 183 male Queensland drivers with the same age distribution. The offender group was found to have significantly more traffic infringements, license sanctions, and crashes than the comparison group. Drivers in the offender group were more likely than the comparison group to have committed infringements related to street racing, such as speeding, "hooning," and offenses related to vehicle defects or illegal modifications. Insufficient statistical capacity prevented full exploration of group differences in the type and nature of earlier crashes. It was concluded, however, that street racing offenders generally can be considered risky drivers who warrant attention and whose risky behavior cannot be explained by their youth alone.

Social influences on drivers in China

China is one of Asia’s many rapidly-motorising nations and recent increases in private-vehicle ownership have been coupled with an escalation in novice drivers. Several pieces of road safety legislation have been introduced in recent decades in China. While managing the legal aspects of road use is important, social influences on driver behaviour may offer alternative avenues to alter behaviour, particularly in a culture where such factors carry high importance. This paper reports qualitative research with Beijing drivers to investigate social influence factors that have, to date, received little attention in the literature. Findings indicated that family members, friends, and driving instructors appear influential on driver behaviour and that some newly licensed drivers seek additional assistance to facilitate the transition from learning to drive in a controlled environment to driving on the road in complex conditions. Strategies to avoid detection and penalties for inappropriate road use were described, many of which involved the use of a third person. These findings indicate potential barriers to implementing effective traffic enforcement and highlight the importance of understanding culturally-specific social factors relating to driver behaviour.

Real-time evaluation of driver’s alertness on highways

Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.

How consistent are drivers in their driving? A driver training perspective

The value and effectiveness of driver training as a means of improving driver behaviour and road safety continues to fuel research and societal debates. Knowledge about what are the characteristics of safe driving that need to be learnt is extensive. Research has shown that young drivers are over represented in crash statistics. The encouraging fact is that novice drivers have shown improvement in road scanning pattern after training. This paper presents a driver behaviour study conducted on a closed circuit track. A group of experienced and novice drivers performed repeated multiple manoeuvres (i.e. turn, overtake and lane change) under identical conditions Variables related to the driver, vehicle and environment were recorded in a research vehicle equipped with multiple in-vehicle sensors such as GPS accelerometers, vision processing, eye tracker and laser scanner. Each group exhibited consistently a set of driving pattern characterising a particular group. Behaviour such as the indicator usage before lane change, following distance while performing a manoeuvre were among the consistent observed behaviour differentiating novice from experienced drivers. This paper will highlight the results of our study and emphasize the need for effective driver training programs focusing on young and novice drivers.

Car ownership, mileage, and risky driving among young intermediate drivers

Introduction: Young drivers are at greatest risk of injury or death from a car crash in the first six months of independent driving. In Queensland, the graduated driver licensing (GDL) program was extensively modified in July 2007 and aims to minimise this risk. Increased mileage and car ownership have been found to play a role in risky driving, offences and crashes; however GDL programs typically do not consider these variables. The paper explores the mileage and car ownership characteristics of young newly-licensed intermediate (Provisional) drivers and their relation to risky driving, crashes and offences. Methods: Drivers (n = 1032) aged 17-19 years recruited from across Queensland for longitudinal research completed Survey 1 exploring pre-licence and Learner experiences and sociodemographic characteristics. Survey 2 explored the same variables with a subset of these drivers (n = 341) after they had completed their first six months of independent driving. Results: At Survey 2, most young drivers owned their vehicle. Novices who drove more kilometres and who spent more hours each week driving were more likely to report risky driving. These drivers were also more likely to report being detected by Police for a driving-related offence. Conclusions: GDL programs should incorporate education for the parent and novice driver regarding the increased risks associated with increased driving exposure, particularly where the novices own their vehicle. Parents should be encouraged to delay exclusive access to a vehicle for the novice driver.