Experimental and numerical study of water-filled road safety barriers

Portable water-filled road barriers (PWFB) are roadside structures placed on temporary construction zones to separate work site from moving traffic. Recent changes in governing standards require PWFB to adhere to strict compliance in terms of lateral displacement of the road barriers and vehicle redirectionality. Actual road safety barrier test can be very costly, thus researchers resort to Finite Element Analysis (FEA) in the initial designs phase prior to real vehicle test. There has been many research conducted on concrete barriers and flexible steel barriers using FEA, however not many is done pertaining to PWFB. This research probes a new method to model joint mechanism in PWFB. Two methods to model the joining mechanism are presented and discussed in relation to its practicality and accuracy to real work applications. Moreover, the study of the physical gap and mass of the barrier was investigated. Outcome from this research will benefit PWFB research and allow road barrier designers better knowledge in developing the next generation of road safety structures.

Moderate sleep restriction in treated older male OSA participants: Greater impairment during monotonous driving compared with controls

Objectives To examine the effects on monotonous driving of normal sleep versus one night of sleep restriction in continuous positive airway pressure (CPAP) treated obstructive sleep apnoea (OSA) patients compared with age matched healthy controls. Methods Nineteen CPAP treated compliant male OSA patients (OSA-treated patients (OPs)), aged 50–75 years, and 20 healthy age-matched controls underwent both a normal night’s sleep and sleep restriction to 5 h (OPs remained on CPAP) in a counterbalanced design. All participants completed a 2 h afternoon monotonous drive in a realistic car simulator. Driving was monitored for sleepiness-related minor and major lane deviations, with ‘safe’ driving time being total time driven prior to first major lane deviation. EEGs were recorded continuously, and subjective sleepiness ratings were taken at regular intervals throughout the drive. Results After a normal night’s sleep, OPs and controls did not differ in terms of driving performance or in their ability to assess the levels of their own sleepiness, with both groups driving ‘safely’ for approximately 90 min. However, after sleep restriction, OPs had a significantly shorter (65 min) safe driving time and had to apply more compensatory effort to maintain their alertness compared with controls. They also underestimated the enhanced sleepiness. Nevertheless, apart from this caveat, there were generally close associations between subjective sleepiness, likelihood of a major lane deviation and EEG changes indicative of sleepiness. Conclusions With a normal night’s sleep, effectively treated older men with OSA drive as safely as healthy men of the same age. However, after restricted sleep, driving impairment is worse than that of controls. This suggests that, although successful CPAP treatment can alleviate potential detrimental effects of OSA on monotonous driving following normal sleep, these patients remain more vulnerable to sleep restriction.

Complex cognitive interactions in a badly designed world : Investigating the underlying causes of collisions between distinct road users

Collisions between distinct road users (e.g. drivers and riders, drivers and cyclists) make a substantial contribution to the road trauma burden. Although evidence suggests different road users interpret the same road situations contrarily, it is not clear how their situation awareness differs, nor is it clear which differences might lead to conflicts. This article presents the findings from an on-road study which was conducted to examine driver, cyclist and motorcyclist situation awareness in different road environments. The findings suggest that drivers, motorcyclists, and cyclists develop markedly different situational understandings even when operating in the same road environments. Examination of these differences indicate that they are likely to be compatible along arterial roads, shopping strips and at roundabouts, but that they may create conflicts between the different road users at intersections. The key role of road design in supporting compatible situation awareness and behaviour across different road users is discussed.

An isolated MOSFET gate driver

Traditional methods of isolated MOSFET/IGBT gate drive are presented, and their pros and cons assessed. The best options are chosen to meet our objective— a small, high speed, low cost, low power isolated gate drive module. Two small ferrite bead transformers are used for isolation, one transmits power at 2.5MHz, the other sends narrow set reset pulses. On the secondary these pulses drive a transistor totem pole to ensure high current drive, and the value is held by CMOS buffers with positive feedback. An alternative design for driving logic level devices uses only an HC buffer on the secondary. Double sided SMDconstruction (primary one side, secondary on the other) yields an upright module 40x18x5mm. Propagation delaywas 20ns, and rise/fall time 15ns with a 1nF load. The design places no limits on frequency of operation or duty cycle. Power supply requirementswere 5V@20mA for operation below 100kHz, dominated by magnetising current.

On-road driving studies to understand why drivers behave as they do at regional rail level crossings

Improving safety at rail level crossings is an important part of both road and rail safety strategies. While low in number, crashes between vehicles and trains at level crossings are catastrophic events typically involving multiple fatalities and serious injuries. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles with eye and head tracking, provide researchers with the opportunity to further understand driver behaviour at such crossings in ways not previously possible. This paper describes a study conducted to further understand the factors that shape driver behaviour at rail level crossings using instrumented vehicles. Twenty-two participants drove an On-Road Test Vehicle (ORTeV) on a predefined route in regional Victoria with a mix of both active (flashing lights with/without boom barriers) and passively controlled (stop, give way) crossings. Data collected included driving performance data, head checks, and interview data to capture driver strategies. The data from an integrated suite of methods demonstrated clearly how behaviour differs at active and passive level crossings, particularly for inexperienced drivers. For example, the head check data clearly show the reliance and expectancies of inexperienced drivers for active warnings even when approaching passively controlled crossings. These studies provide very novel and unique insights into how level crossing design and warnings shape driver behaviour.

Building an augmented map for road risk assessment

Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

The consistency of crash involvement recall across time

Introduction Road safety researchers rely heavily on self-report data to explore the aetiology of crash risk. However, researchers consistently acknowledge a range of limitations associated with this methodological approach (e.g., self-report bias), which has been hypothesised to reduce the predictive efficacy of scales. Although well researched in other areas, one important factor often neglected in road safety studies is the fallibility of human memory. Given accurate recall is a key assumption in many studies, the validity and consistency of self-report data warrants investigation. The aim of the current study was to examine the consistency of self-report data of crash history and details of the most recent reported crash on two separate occasions. Materials & Method A repeated measures design was utilised to examine the self-reported crash involvement history of 214 general motorists over a two month period. Results A number of interesting discrepancies were noted in relation to number of lifetime crashes reported by the participants and the descriptions of their most recent crash across the two occasions. Of the 214 participants who reported having been involved in a crash, 35 (22.3%) reported a lower number of lifetime crashes as Time 2, than at Time 1. Of the 88 drivers who reported no change in number of lifetime crashes, 10 (11.4%) described a different most recent crash. Additionally, of the 34 reporting an increase in the number of lifetime crashes, 29 (85.3%) of these described the same crash on both occasions. Assessed as a whole, at least 47.1% of participants made a confirmed mistake at Time 1 or Time 2. Conclusions These results raise some doubt in regard to the accuracy of memory recall across time. Given that self-reported crash involvement is the predominant dependent variable used in the majority of road safety research, this issue warrants further investigation. Replication of the study with a larger sample size that includes multiple recall periods would enhance understanding into the significance of this issue for road safety methodology.

The wrong tool for the job? The predictive powers of the DBQ in a sample of Queensland motorists

Introduction This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours (e.g., speeding, errors & aggressive manoeuvres) and predict crash involvement among a sample of general Queensland motorists. Material and Methods Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results A factor analysis revealed a three factor solution for the DBQ which was consistent with previous Australian-based research. It accounted for 40.5% of the total variance, although some cross-loadings were observed on nine of the twenty items. The internal reliability of the DBQ was satisfactory. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement or demerit point loss e.g. violation notices. Rather, exposure to the road was found to be predictive of crashes, although speeding did make a small contribution to those who recently received a violation notice. Conclusions Taken together, the findings contribute to a growing body of research that raises questions about the predictive ability of the most widely used driving assessment tool globally. Ongoing research (which also includes official crash and offence outcomes) is required to better understand the actual contribution that the DBQ can make to understanding and improving road safety. Future research should also aim to confirm whether this lack of predictive efficacy originates from broader issues inherent within self-report data (e.g., memory recall problems) or issues underpinning the conceptualisation of the scale.

Awesome foursome? The compatibility of situation awareness across drivers, riders, cyclists, and pedestrians

Collisions between distinct road users (e.g. drivers and motorcyclists) make a substantial contribution to the road trauma burden. Although evidence suggests distinct road users interpret the same road situations differently, it is not clear how road users’ situation awareness differs, nor is it clear which differences might lead to conflicts. This article presents the findings from an on-road study which examined driver, cyclist, motorcyclist and pedestrian situation awareness at intersections. The findings suggest that situation awareness at intersection is markedly different across the four road user groups studied, and that some of these differences may create conflicts between the different road users. The findings also suggest that the causes of the differences identified relate to road design and road user experience. In closing, the key role of road design and training in supporting safe interactions between distinct road users is discussed.

Interactions between cars and motorcycles testing underlying concepts through integration of on-road and simulator studies

We conducted on-road and simulator studies to explore the mechanisms underpinning driver-rider crashes. In Study 1 the verbal protocols of 40 drivers and riders were assessed at intersections as part of a 15km on-road route in Melbourne. Network analysis of the verbal transcripts highlighted key differences in the situation awareness of drivers and riders at intersections. In a further study using a driving simulator we examined in car drivers the influence of acute exposure to motorcyclists. In a 15 min simulated drive, 40 drivers saw either no motorcycles or a high number of motorcycles in the surrounding traffic. In a subsequent 45-60 min drive, drivers were asked to detect motorcycles in traffic. The proportion of motorcycles was manipulated so that there was either a high (120) or low (6) number of motorcycles during the drive. Those drivers exposed to a high number of motorcycles were significantly faster at detecting motorcycles. Fundamentally, the incompatible situation awareness at intersections by drivers and riders underpins the conflicts. Study 2 offers some suggestion for a countermeasure here, although more research around schema and exposure training to support safer interactions is needed.

Sleepiness : how a biological drive can influence other risky road user behaviours

The Safe System approach to road safety utilises a holistic view of the interactions among vehicles, roads and road users. Yet, the contribution of each of these factors to crashes is vastly different. The role of road users is widely acknowledged as an overwhelming contributor to road crashes. Substantial gains have been made with improvements to vehicle and roads over a number of years. However, improvements of the road user’s behaviour has been (in some cases) less substantial. A road user behaviour that is relatively unregulated is driver sleepiness, which is part of the ‘fatal five’ of risky road user behaviours. The effect of sleepiness is ubiquitous – sleepiness is a state that most, if not all drivers on our roads has experienced, and is habitually exposed to. The quality and quantity of daily sleep is integral to our level of neurobehavioural performance during wakefulness and as such can have a compounding effect on a number of other risky driving behaviours. This paper will discuss the potential influence of sleepiness as an interceding factor for a number of risky driving behaviours. Little effort has been given to increasing awareness of the deleterious and wide ranging effects that sleepiness has on road safety. Given the wide ranging influence of sleepiness, improvements of ‘sleep health’ as a protective factor at the community or individual level could lead to significant reductions in road trauma and increases of general well being. A discussion of potential actions to reduce sleepiness is required if reductions of road trauma are to continue.

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.

Efficacy of proxy definitions for identification of fatigue/sleep-related crashes : an Australian evaluation

Fatigue/sleepiness is recognised as an important contributory factor in fatal and serious injury road traffic incidents (RTIs), however, identifying fatigue/sleepiness as a causal factor remains an uncertain science. Within Australia attending police officers at a RTI report the causal factors; one option is fatigue/sleepiness. In some Australian jurisdictions police incident databases are subject to post hoc analysis using a proxy definition for fatigue/sleepiness. This secondary analysis identifies further RTIs caused by fatigue/sleepiness not initially identified by attending officers. The current study investigates the efficacy of such proxy definitions for attributing fatigue/sleepiness as a RTI causal factor. Over 1600 Australian drivers were surveyed regarding their experience and involvement in fatigue/sleep-related RTIs and near-misses during the past five years. Driving while fatigued/sleepy had been experienced by the majority of participants (66.0% of participants). Fatigue/sleep-related near misses were reported by 19.1% of participants, with 2.4% being involved in a fatigue/sleep-related RTI. Examination of the characteristics for the most recent event (either a near miss or crash) found that the largest proportion of incidents (28.0%) occurred when commuting to or from work, followed by social activities (25.1%), holiday travel (19.8%), or for work purposes (10.1%). The fatigue/sleep related RTI and near-miss experience of a representative sample of Australian drivers does not reflect the proxy definitions used for fatigue/sleepiness identification. In particular those RTIs that occur in urban areas and at slow speeds may not be identified. While important to have a strategy for identifying fatigue/sleepiness related RTIs proxy measures appear best suited to identifying specific subsets of such RTIs.