Drivers’ inability to assess their level of alertness on monotonous highways

Decline of alertness constitutes a normal physiological phenomenon but could be aggravated when drivers operate in monotonous environments, even in rested individuals. Driving performance is impaired and this increases crash risk due to inattention. This paper aims to show that road characteristics - namely road design (road geometry) and road side variability (signage and buildings) – influence subjective assessment of alertness by drivers. This study used a driving simulator to investigate the drivers’ ability to subjectively detect periods of time when their alertness is importantly reduced by varying road geometry and road environment. Driver’s EEG activity is recorded as a reference to evaluate objectively driver's alertness and is compared to self-reported alertness by participants. Twenty-five participants drove on four different scenarios (varying road design and road environment monotony) for forty minutes. It was observed that participants were significantly more accurate in their assessment before the driving task as compared to after (90% versus 60%). Errors in assessment were largely underestimations of their real alertness rather than over-estimations. The ability to detect low alertness as assessed with an EEG was highly dependent on the road monotony. Scenarios with low roadside variability resulted in high overestimation of the real alertness, which was not observed on monotonous road design. The findings have consequences for road safety and suggest that countermeasures to lapses of alertness cannot rely solely on self-assessment from drivers and road design should reduce environments with low variability.

The future shape of digital cars

Background. Digital information is increasingly becoming available on all aspects of the urban landscape, anywhere and any time. Physical objects (c.f. the Internet of Things) and people (c.f. the Social Web) are increasingly infused with actuators, sensors and tagged with a wealth of digital information. Urban Informatics explores these emerging digital layers of the city. However, very little is known about the challenges and new opportunities that these developments may offer to road users. As we gradually spend more time using our mobile devices as well as our car, the tension between appeasing our craving for connectedness and road safety requirements grow farther apart. Objective. The aims of this paper are to identify (a) new opportunities that Urban Informatics research can offer to our future cars and (b) potential benefits to road safety. Methods. 14 Urban Informatics research experts were grouped into seven teams of two to participate in a guided ideation (idea creation) workshop in a driving simulator. They were immersed into different driving scenarios to brainstorm innovative Urban Informatics applications in different driving contexts. This qualitative study was then evaluated in the context of road safety. Outcomes. There is a lack of articulation between Urban Informatics and Road Safety research. Several Urban Informatics applications (e.g., to enhance social interaction between people in urban environments) may provide benefits, rather than threats, towards road safety, provided they are implemented ergonomically and safely. Conclusions. This research initiates a much-needed dialogue between Urban Informatics and Road Safety disciplines, in the context of Intelligent Transport Systems, before the fast approaching digital wave invades our cars. The dialogue will help to avoid driver distraction issues similar to mobile phones use in cars. As such, it provides valuable information for future regulators and policy makers in charge of shaping our future road transport landscape.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

An extensible simulation framework for critical infrastructure security

We introduce the Network Security Simulator (NeSSi2), an open source discrete event-based network simulator. It incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Compared to the predecessor NeSSi, it was extended with a three-tier plugin architecture and a generic network model to shift its focus towards simulation framework for critical infrastructures. We demonstrate the gained adaptability by different use cases

Does experience with one type of two-wheeler affect behaviours and attitudes to other types?

Failure to give way by motor vehicles is a factor in many collisions with both powered and unpowered two wheelers (TWs). Motor vehicle drivers often report that they did not see the TW, but research has shown that motor vehicle drivers who have experience riding a motorcycle are less likely to fail to detect motorcycles. The research reported here examines whether this phenomenon extends to detection of bicycles and whether car drivers who have experience with one mode of TW show improved detection of the other mode. A driving simulator study was conducted in an Australian urban setting which incorporated some of the most common car-TW crash scenarios. Participants with car-only, car plus motorcycle, car plus bicycle, and car plus bicycle plus motorcycle experience operated a car simulator. Their interactions with both types of TWs were measured in terms of visual detection, lateral distance and speed when approaching and passing. The effects of different levels of colour and lighting of the TWs on driver responses were also examined. The attitudes of participants towards TWs were measured in a questionnaire.

The impact of co-locating regulatory and directional signs on driver performance

The use of intelligent transport systems is proliferating across the Australian road network, particularly on major freeways. New technology allows a greater range of signs and messages to be displayed to drivers. While there has been a long history of human factors analyses of signage, no evaluation has been conducted on this novel, sometimes dynamic, signage or potential interactions when co-located. The purpose of this driving simulator study was to investigate drivers’ behavioural changes and comprehension resulting from the co-location of Lane Use Management Systems with static signs and (Enhanced) Variable Message Signs on Queensland motorways. A section of motorway was simulated, and nine scenarios were developed which presented a combination of signage cases across levels of driving task complexity. Two higher-risk road user groups were targeted for this research on an advanced driving simulator: older (65+ years, N=21) and younger (18-22 years, N=20) drivers. Changes in sign co-location and task complexity had small effect on driver comprehension of the signs and vehicle dynamics variables, including difference with the posted speed limit, headway, standard deviation of lane keeping and brake jerks. However, increasing the amount of information provided to drivers at a given location (by co-locating several signs) increased participants’ gaze duration on the signs. With co-location of signs and without added task complexity, a single gaze was over 2s for more than half of the population tested for both groups, and up to 6 seconds for some individuals.

Driver sleepiness—Comparisons between young and older men during a monotonous afternoon simulated drive

Young men figure prominently in sleep-related road crashes. Non-driving studies show them to be particularly vulnerable to sleep loss, compared with older men. We assessed the effect of a normal night's sleep vs. prior sleep restricted to 5 h, in a counterbalanced design, on prolonged (2 h) afternoon simulated driving in 20 younger (av. 23 y) and 19 older (av. 67 y) healthy men. Driving was monitored for sleepiness related lane deviations, EEGs were recorded continuously and subjective ratings of sleepiness taken every 200 s. Following normal sleep there were no differences between groups for any measure. After sleep restriction younger drivers showed significantly more sleepiness-related deviations and greater 4–11 Hz EEG power, indicative of sleepiness. There was a near significant increase in subjective sleepiness. Correlations between the EEG and subjective measures were highly significant for both groups, indicating good self-insight into increasing sleepiness. We confirm the greater vulnerability of younger drivers to sleep loss under prolonged afternoon driving.

Effects of mobile phone distraction on drivers’ reaction times

Distraction resulting from mobile phone use whilst driving has been shown to increase the reaction times of drivers, thereby increasing the likelihood of a crash. This study compares the effects of mobile phone conversations on reaction times of drivers responding to traffic events that occur at different points in a driver’s field of view. The CARRS-Q Advanced Driving Simulator was used to test a group of young drivers on various simulated driving tasks including a traffic event that occurred within the driver’s central vision—a lead vehicle braking suddenly—and an event that occurred within the driver’s peripheral—a pedestrian entering a zebra crossing from a footpath. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), and while engaged in hands-free and handheld phone conversations. The drivers were aged between 21 to 26 years and split evenly by gender. Differences in reaction times for an event in a driver’s central vision were not statistically significant across phone conditions, probably due to a lower speed selection by the distracted drivers. In contrast, the reaction times to detect an event that originated in a distracted driver’s peripheral vision were more than 50% longer compared to the baseline condition. A further statistical analysis revealed that deterioration of reaction times to an event in the peripheral vision was greatest for distracted drivers holding a provisional licence. Many critical events originate in a driver’s periphery, including vehicles, bicyclists, and pedestrians emerging from side streets. A reduction in the ability to detect these events while distracted presents a significant safety concern that must be addressed.

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations

The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q Advanced Driving Simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver’s peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21 to 26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver’s age, license type (Provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.

Sleep-related eye symptoms and their potential for identifying driver sleepiness

The majority of individuals appear to have insight into their own sleepiness, but there is some evidence that this does not hold true for all, for example treated patients with obstructive sleep apnoea. Identification of sleep-related symptoms may help drivers determine their sleepiness, eye symptoms in particular show promise. Sixteen participants completed four motorway drives on two separate occasions. Drives were completed during daytime and night-time in both a driving simulator and on the real road. Ten eye symptoms were rated at the end of each drive, and compared with driving performance and subjective and objective sleep metrics recorded during driving. ‘Eye strain’, ‘difficulty focusing’, ‘heavy eyelids’ and ‘difficulty keeping the eyes open’ were identified as the four key sleep-related eye symptoms. Drives resulting in these eye symptoms were more likely to have high subjective sleepiness and more line crossings than drives where similar eye discomfort was not reported. Furthermore, drivers having unintentional line crossings were likely to have ‘heavy eyelids’ and ‘difficulty keeping the eyes open’. Results suggest that drivers struggling to identify sleepiness could be assisted with the advice ‘stop driving if you feel sleepy and/or have heavy eyelids or difficulty keeping your eyes open’.

Effects of driver familiarity and prolonged or intermittent right-side failure on level crossing safety

This paper investigates the adverse effects of familiarity and human factors issues associated with the reliability of low-cost warning devices at level crossings. The driving simulator study featured a repetitive, low workload, monotonous driving task in which there were no failures of the level crossing (control) or prolonged or intermittent right-side failures (where the device reverts to a safe failure mode). The results of the experiment provided mixed support for the familiarity hypothesis. Four of the 23 participants collided with the train when it first appeared on trial 10 but safety margins increased from the first train to the next presentation of a train (trial 12). Contrary to expectations, the safety margins decreased with repeated right-side failure only for the intermittent condition. The limited head movement data showed that participants in the prolonged failure condition were more likely to turn their head to check for trains in the right-side failure trials than in earlier trials where there was no signal and no train. Few control participants turned their head to check for trains when no signal was presented. This research highlights the need to consider repetitive tasks and workload in experimental design and accident investigation at railway level crossings.

Effect of mobile phone distraction on car-following behaviour

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18 to 26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 seconds in time headway when a driver is engaged in hands-free phone conversation and a 0.75 seconds increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Human factors evaluation of a novel Australian approach for activating railway level crossings

There are currently 23,500 level crossings in Australia, broadly divided active level crossings with flashing lights; and passive level crossings controlled by stop and give way signs. The current strategy is to annually upgrade passive level crossings with active controls within a given budget, but the 5,900 public passive crossings are too numerous to be upgraded all. The rail industry is considering alternative options to treat more crossings. One of them is to use lower cost equipment with reduced safety integrity level, but with a design that would fail to a safe state: in case of the impossibility for the system to know whether a train is approaching, the crossing changes to a passive crossing. This is implemented by having a STOP sign coming in front of the flashing lights. While such design is considered safe in terms of engineering design, questions remain on human factors. In order to evaluate whether such approach is safe, we conducted a driving simulator study where participants were familiarized with the new active crossing, before changing the signage to a passive crossing. Our results show that drivers treated the new crossing as an active crossing after the novelty effect had passed. While most participants did not experience difficulties with the crossing being turned back to a passive crossing, a number of participants experienced difficulties stopping in time at the first encounter of such passive crossing. Worse, a number of drivers never realized the signage had changed, highlighting the link between the decision to brake and stop at an active crossing to the lights flashing. Such results show the potential human factor issues of changing an active crossing to a passive crossing in case of failure of the detection of the train.

Translating road safety research on night-time visibility to the context of mining

In recent years a significant amount of research has been undertaken in collision avoidance and personnel location technology in order to reduce the number of incidents involving pedestrians and mobile plant equipment which are a high risk in underground coal mines. Improving the visibility of pedestrians to drivers would potentially reduce the likelihood of these incidents. In the road safety context, a variety of approaches have been used to make pedestrians more conspicuous to drivers at night (including vehicle and roadway lighting technologies and night vision enhancement systems). However, emerging research from our group and others has demonstrated that clothing incorporating retroreflective markers on the movable joints as well as the torso can provide highly significant improvements in pedestrian visibility in reduced illumination. Importantly, retroreflective markers are most effective when positioned on the moveable joints creating a sensation of “biological motion”. Based only on the motion of points on the moveable joints of an otherwise invisible body, observers can quickly recognize a walking human form, and even correctly judge characteristics such as gender and weight. An important and as yet unexplored question is whether the benefits of these retroreflective clothing configurations translate to the context of mining where workers are operating under low light conditions. Given that the benefits of biomotion clothing are effective for both young and older drivers, as well as those with various eye conditions common in those >50 years reinforces their potential application in the mining industry which employs many workers in this age bracket. This paper will summarise the visibility benefits of retroreflective markers in a biomotion configuration for the mining industry, highlighting that this form of clothing has the potential to be an affordable and convenient way to provide a sizeable safety benefit. It does not involve modifications to vehicles, drivers, or infrastructure. Instead, adding biomotion markings to standard retroreflective vests can enhance the night-time conspicuity of mining workers by capitalising on perceptual capabilities that have already been well documented.