Michael G. Lenné

Time of day variations in driving performance

Numerous factors may contribute to the 24-hour pattern of automobile accidents. One factor may be a time of day variation in driving ability. In the present study, 11 male subjects operated a driving simulator for 30 minutes at six times of day. Subjects were instructed to maintain a stable position in the left-hand lane and to drive at a constant speed of 80 km/hour. In addition subjects performed a secondary reaction time task. Subjective mood was measured at the beginning and end of each session. Driving performance was measured in terms of the mean and standard deviation of lateral position and speed. The mean and standard deviation of speed varied significantly across the day for both curved and straight segments. Reaction time was also affected by time of day. Performance was more impaired at 0600 and 0200 hours, with improvements in driving performance between 1000 and 2200 hours and an early afternoon dip. These results suggest that driving performance is subject to diurnal variations. Of particular importance is the result that impairments in driving performance in the early afternoon are of a similar magnitude to those occurring in the late evening and early morning.

Predicting driver drowsiness using vehicle measures: recent insights and future challenges.

INTRODUCTION Driver drowsiness is a significant contributing factor to road crashes. One approach to tackling this issue is to develop technological countermeasures for detecting driver drowsiness, so that a driver can be warned before a crash occurs. METHOD The goal of this review is to assess, given the current state of knowledge, whether vehicle measures can be used to reliably predict drowsiness in real time. RESULTS Several behavioral experiments have shown that drowsiness can have a serious impact on driving performance in controlled, experimental settings. However, most of those studies have investigated simple functions of performance (such as standard deviation of lane position) and results are often reported as averages across drivers, and across time. CONCLUSIONS Further research is necessary to examine more complex functions, as well as individual differences between drivers. IMPACT ON INDUSTRY A successful countermeasure for predicting driver drowsiness will probably require the setting of multiple criteria, and the use of multiple measures.

The effects of cannabis and alcohol on simulated arterial driving: Influences of driving experience and task demand

This study compared the effects of three doses of cannabis and alcohol (placebo, low and high doses), both alone and in combination, on the driving performance of young, novice drivers and more experienced drivers. Alcohol was administered as ethanol (95%) mixed with orange juice in doses of approximately 0, 0.4 and 0.6g/kg. Cannabis was administered by inhalation of smoke from pre-rolled cannabis cigarettes (supplied by the National Institute of Drug Abuse, USA). Active cigarettes contained 19 mg delta-9-THC. Using a counterbalanced design, the simulated driving performance of 25 experienced and 22 inexperienced drivers was tested under the nine different drug conditions in an arterial driving environment during which workload was varied through the drive characteristics as well as through the inclusion of a secondary task. High levels of cannabis generally induced greater impairment than lower levels, while alcohol at the doses used had few effects and did not produce synergistic effects when combined with cannabis. Both cannabis and alcohol were associated with increases in speed and lateral position variability, high dose cannabis was associated with decreased mean speed, increased mean and variability in headways, and longer reaction time, while in contrast alcohol was associated with a slight increase in mean speed. Given the limitations of the study, it is of great interest to further explore the qualitative impairments in driving performance associated with cannabis and alcohol separately and how these impairments may manifest in terms of crash characteristics.

A systems approach to accident causation in mining: An application of the HFACS method

This project aimed to provide a greater understanding of the systemic factors involved in mining accidents, and to examine those organisational and supervisory failures that are predictive of sub-standard performance at operator level. A sample of 263 significant mining incidents in Australia across 2007-2008 were analysed using the Human Factors Analysis and Classification System (HFACS). Two human factors specialists independently undertook the analysis. Incidents occurred more frequently in operations concerning the use of surface mobile equipment (38%) and working at heights (21%), however injury was more frequently associated with electrical operations and vehicles and machinery. Several HFACS categories appeared frequently: skill-based errors (64%) and violations (57%), issues with the physical environment (56%), and organisational processes (65%). Focussing on the overall system, several factors were found to predict the presence of failures in other parts of the system, including planned inappropriate operations and team resource management; inadequate supervision and team resource management; and organisational climate and inadequate supervision. It is recommended that these associations deserve greater attention in future attempts to develop accident countermeasures, although other significant associations should not be ignored. In accordance with findings from previous HFACS-based analyses of aviation and medical incidents, efforts to reduce the frequency of unsafe acts or operations should be directed to a few critical HFACS categories at the higher levels: organisational climate, planned inadequate operations, and inadequate supervision. While remedial strategies are proposed it is important that future efforts evaluate the utility of the measures proposed in studies of system safety.

Objective and subjective measures of sleepiness, and their associations with on-road driving events in shift workers

To assess the relationships between sleepiness and the incidence of adverse driving events in nurses commuting to and from night and rotating shifts, 27 rotating and permanent night shift‐working nurses were asked to complete daily sleep and duty logs, and wear wrist‐activity monitors for 2 weeks (369 driving sessions). During all commutes, ocular measures of drowsiness, including the Johns Drowsiness Scale score, were assessed using the Optalert™ system. Participants self‐reported their subjective sleepiness at the beginning and end of each drive, and any events that occurred during the drive. Rotating shift nurses reported higher levels of sleepiness compared with permanent night shift nurses. In both shift‐working groups, self‐reported sleepiness, drowsiness and drive events were significantly higher during commutes following night shifts compared with commutes before night shifts. Strong associations were found between objective drowsiness and increased odds of driving events during commutes following night shifts. Maximum total blink duration (mean = 7.96 s) during the drive and pre‐drive Karolinska Sleepiness Scale (mean = 5.0) were associated with greater incidence of sleep‐related events [OR, 5.35 (95% CI, 1.32, 21.60), OR, 1.69 (95% CI, 1.04, 2.73), respectively]. Inattention was strongly associated with a Johns Drowsiness Scale score equal to or above 4.5 [OR, 4.58 (95% CI, 1.26–16.69)]. Hazardous driving events were more likely to occur when drivers had been awake for 16 h or more [OR, 4.50 (95% CI, 1.81, 11.16)]. Under real‐world driving conditions, shift‐working nurses experience high levels of drowsiness as indicated by ocular measures, which are associated with impaired driving performance following night shift work.

Systems-based accident analysis in the led outdoor activity domain: application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussens risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management frameworks predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain. Statement of Relevance: Accidents represent a significant problem within the led outdoor activity domain. This article presents an evaluation of a risk management framework that can be used to understand such accidents and to inform the development of accident countermeasures and mitigation strategies for the led outdoor activity domain.

Sounding the warning bells: The need for a systems approach to understanding behaviour at rail level crossings

Collisions at rail level crossings are an international safety concern and have been the subject of considerable research effort. Modern human factors practice advocates a systems approach to investigating safety issues in complex systems. This paper describes the results of a structured review of the level crossing literature to determine the extent to which a systems approach has been applied. The measures used to determine if previous research was underpinned by a systems approach were: the type of analysis method utilised, the number of component relationships considered, the number of user groups considered, the number of system levels considered and the type of model described in the research. None of research reviewed was found to be consistent with a systems approach. It is recommended that further research utilise a systems approach to the study of the level crossing system to enable the identification of effective design improvements.

Look Who's Talking! A Roadside Survey of Drivers’ Cell Phone Use

Objective: The objective of this study was to quantify Melbourne drivers’ rates of handheld and hands-free phone use and the driver, vehicle, site, and time characteristics associated with phone use. Additionally, this study sought to examine any change in the prevalence of handheld cell phone use by Melbourne drivers between 2006 and 2009. Method: Observational survey of vehicle drivers at various times of the day and week at 3 sites across metropolitan Melbourne during May 2009. Results: A total of 195 (3.4%) of the 5813 drivers observed were using handheld phones and 81 (1.4%) were using hands-free phones. This represents a significant increase in handheld phone usage rates compared to those found in an earlier study conducted in Melbourne in 2006. Cell phone use was associated with a range of driver, vehicle, site, and time characteristics. Handheld phone users were predominately young or middle-aged drivers who drove cars or 4-wheel-drive vehicles (4WDs), and this activity was more likely to occur in the late afternoon. Use of hands-free phones did not differ significantly across gender, age group, vehicle type, observation site, or time of day; however, use of hands-free phones was higher on weekdays compared to weekends. Conclusions: Despite legislation being in place, drivers’ handheld cell phone use is still a major road safety concern, particularly for young and middle-aged drivers. The effectiveness of other strategies for decreasing handheld usage rates, including increased surveillance and tougher penalties, need to be ascertained.

Detection of emergency vehicles: driver responses to advance warning in a driving simulator.

Objective: This research evaluated the effects of an advance warning device (AWD) on the safety of driver interactions with emergency vehicles (EVs). The AWD was intended to provide drivers with advance warning of an approaching on-call EV via visual and auditory warnings when the EV was within a 300- to 400-m radius. Background: Research suggests that drivers can experience difficulty accurately detecting the distance and direction of approaching on-call EV. In-vehicle technology has not previously been explored as a means of overcoming the limitations of existing EV lights and sirens and improving driver detection of EV. Method: An experimental study using an advanced driving simulator examined the effects of the AWD on driving performance in a range of circumstances in which real-world EV crashes and near-misses commonly occur. Each event contained a combination of scenario type (adjacent lane, turning across, car following) and warning condition (control, standard, advance). Results: Data from 22 participants were collected, including measures of speed, braking, and visual scanning. For adjacent-lane and turning-across events, the AWD was associated primarily with reductions in mean speed. The AWD resulted in an earlier lane change to clear a path for the EV in the car-following event. Conclusion: The reduction in speed observed was a positive finding, given the relationship between impact speed and injury severity. Response priming emerged as the mechanism underpinning these effects. Application: Response priming may result in safety benefits in other settings when an advisory warning is presented before the threat can be perceived.

Simulation of safety: A review of the state of the art in road safety simulation modelling

Recent decades have seen considerable growth in computer capabilities, data collection technology and communication mediums. This growth has had considerable impact on our ability to replicate driver behaviour and understand the processes involved in failures in the traffic system. From time to time it is necessary to assess the level of development as a basis of determining how far we have come. This paper sets out to assess the state of the art in the use of computer models to simulate and assess the level of safety in existing and future traffic systems. It reviews developments in the area of road safety simulation models. In particular, it reviews computer models of driver and vehicle behaviour within a road context. It focuses on stochastic numerical models of traffic behaviour and how reliable these are in estimating levels of safety on the traffic network. Models of this type are commonly used in the assessment of traffic systems for capacity, delay and general performance. Adding safety to this assessment regime may allow more comprehensive assessment of future traffic systems. To date the models have focused primarily on vehicular traffic that is, cars and heavy vehicles. It has been shown that these models have potential in measuring the level of conflict on parts of the network and the measure of conflict correlated well with crash statistics. Interest in the prediction of crashes and crash severity is growing and new models are focusing on the continuum of general traffic conditions, conflict, severe conflict, crash and severe crashes. The paper also explores the general data types used to develop, calibrate and validate these models. Recent technological development in in-vehicle data collection, driver simulators and machine learning offers considerable potential for improving the behavioural base, rigour and application of road safety simulation models. The paper closes with some indication of areas of future development.