Editorial: Selected Papers from the 1st European Conference on Human Centred Design for Intelligent Transport Systems

The widespread distribution of in-vehicle driver information systems on the market, and the emergence of advanced driver assistance systems are profoundly changing road transport and more specifically the driver environment and driving activity. Through Intelligent Transport Systems, a range of services are indeed offered to the driver with the objective of facilitating the driving task and improving travel safety. Despite the potential benefits to road safety, these developments raise numerous questions about their relevance, usability and acceptability for drivers and their impact on drivers? behaviour and attitudes. All this contributes to the necessity of encouraging a Human Centred Design approach, in which ITS are designed according to driver needs.     

In-vehicle distraction and fatal accidents in England and Wales.

The paper describes the coding and analysis of a database of police fatal accident reports to investigate the extent to which in-vehicle distraction is a contributory factor in vehicle crashes. A particular focus has been the involvement of mobile telephones and entertainment systems. Analysis of accidents occurring over the period 1985-1995 shows that in-vehicle distraction is reported as a contributory factor in about 2% of fatal accidents (although this figure may be a conservative estimate). Specific examples of distraction attributed to entertainment systems and telephones have been identified. Electronic driver information systems are also of particular interest, but have not featured in the available data. Work is progressing, on an annual cycle, to obtain, code and analyse further data and this is expected to provide an invaluable source of information for accident researchers.     

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.     

Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model

Multi-vehicle rear-end accidents constitute a substantial portion of the accidents occurring at signalized intersections. To examine the accident characteristics, this study utilized the 2001 Florida traffic accident data to investigate the accident propensity for different vehicle roles (striking or struck) that are involved in the accidents and identify the significant risk factors related to the traffic environment, the driver characteristics, and the vehicle types. The Quasi-induced exposure concept and the multiple logistic regression technique are used to perform this analysis. The results showed that seven road environment factors (number of lanes, divided/undivided highway, accident time, road surface condition, highway character, urban/rural, and speed limit), five factors related to striking role (vehicle type, driver age, alcohol/drug use, driver residence, and gender), and four factors related to struck role (vehicle type, driver age, driver residence, and gender) are significantly associated with the risk of rear-end accidents. Furthermore, the logistic regression technique confirmed several significant interaction effects between those risk factors.     

Fatal traffic accidents among trailer truck drivers and accident causes as viewed by other truck drivers

Causality factors, the responsibility of the driver and driver fatigue-related factors were studied in fatal two-vehicle accidents where a trailer truck driver was involved during the period of 1991-1997 (n = 337). In addition, 251 long-haul truck drivers were surveyed in order to study their views regarding contributing factors in accidents involving trucks and the development of possible countermeasure against driver fatigue. Trailer truck drivers were principally responsible for 16% of all the accidents. Younger driver age and driving during evening hours were significant predictors of being principally responsible. In addition, the probability of being principally responsible for the accident increased by a factor of over three if the driver had a chronic illness. Prolonged driving preceding the accident, accident history or traffic offence history did not have a significant effect. Only 2% of the drivers were estimated to have fallen asleep while driving just prior to the accident, and altogether 4% of the drivers had been tired prior to the accident. Of the drivers 13% had however, been driving over 10 h preceding the accident (which has been criminally punishably in Finland since 1995 under the EC regulation) but no individual factors had a significant effect in predicting prolonged driving. The surveyed views regarding causes of truck accidents correspond well with the accident analysis. Accidents were viewed as being most often caused by other road users and driver fatigue was viewed to be no more than the fifth (out of eight) common cause of accidents. The probability of viewing fatigue as a more common cause increased significantly if the driver had experienced fatigue-related problems while driving. However, nearly half of the surveyed truck drivers expressed a negative view towards developing a technological countermeasure against driver fatigue. The negative view was not related to personal experiences of fatigue-related problems while driving.     

Looked-but-failed-to-see-errors in traffic

Danish studies of traffic accidents at priority intersections have shown a particular type of accidents. In these accidents a car driver supposed to give way has collided with a bicycle rider on the priority road. Often the involved car drivers have maintained that they did not see the bicycle until immediately before the collision even though the bicycle must have been clearly visible.

Similar types of accidents have been the subject of studies elsewhere. In literature they are labelled “looked-but-failed-to-see”, because it seems clear that in many cases the car drivers have actually been looking in the direction where the other parties were but have not seen (i.e. perceived the presence of) the other road user. This paper describes two studies approaching this problem.

One study is based on 10 self-reported near accidents. It does show that “looked-but-failed-to-see” events do occur, especially for well experienced drivers. The other study based on Gap Acceptance shows that the car driver acceptance of gaps towards cyclists depends on whether or not another car is present. Hypotheses for driver perception and for accident countermeasures are discussed.     

Effects of electronic stability control (ESC) on accidents: a review of empirical evidence

This study summarizes evidence from empirical studies on the effects of electronic stability control (ESC) on accidents in a meta-analysis. Large reductions of single vehicle accidents have been found (-49%; 95% confidence interval: [-55%; -42%]), and smaller but still significant reductions of head-on collisions (-13%; 95% confidence interval: [-17%; -8%]). Multi-vehicle fatal accidents are also significantly reduced (-32%; 95% confidence interval: [-43%; -20%]). The effects can be explained with the potential of ESC to improve driving dynamics and to reduce the probability of loss of control. However, there are significant amounts of heterogeneity in the results, especially for single vehicle accidents, and a sensitivity analysis shows that the results for single vehicle accidents are likely to be affected by publication bias. The results for single vehicle accidents are in excess of what might be expected based on studies that have estimated the total amount of accidents that may be affected by ESC. Consequently, the proportions of accidents that can be avoided by ESC is assumed to be somewhat smaller than suggested by most empirical studies. Properties of the vehicles, time trends, and driver behaviour may have contributed to the large empirical effects.     

A crash-prediction model for road tunnels

Considerable research has been carried out into open roads to establish relationships between crashes and traffic flow, geometry of infrastructure and environmental factors, whereas crash-prediction models for road tunnels, have rarely been investigated. In addition different results have been sometimes obtained regarding the effects of traffic and geometry on crashes in road tunnels. However, most research has focused on tunnels where traffic and geometric conditions, as well as driving behaviour, differ from those in Italy. Thus, in this paper crash prediction-models that had not yet been proposed for Italian road tunnels have been developed. For the purpose, a 4-year monitoring period extending from 2006 to 2009 was considered. The tunnels investigated are single-tube ones with unidirectional traffic. The Bivariate Negative Binomial regression model, jointly applied to non-severe crashes (accidents involving material-damage only) and severe crashes (fatal and injury accidents only), was used to model the frequency of accident occurrence. The year effect on severe crashes was also analyzed by the Random Effects Binomial regression model and the Negative Multinomial regression model. Regression parameters were estimated by the Maximum Likelihood Method. The Cumulative Residual Method was used to test the adequacy of the regression model through the range of annual average daily traffic per lane. The candidate set of variables was: tunnel length (L), annual average daily traffic per lane (AADT_L), percentage of trucks (%Tr), number of lanes (N_L), and the presence of a sidewalk. Both for non-severe crashes and severe crashes, prediction-models showed that significant variables are: L, AADT_L, %Tr, and N_L. A significant year effect consisting in a systematic reduction of severe crashes over time was also detected. The analysis developed in this paper appears to be useful for many applications such as the estimation of accident reductions due to improvement in existing tunnels and/or to modifications of traffic control systems, as well as for the prediction of accidents when different tunnel design options are compared.     

Driver celeration behaviour and accidents – an analysis

A theory of changes in speed of a vehicle (termed ‘celerations’) as an overall measure of driver behaviour regarding the control of the vehicle, and as a predictor of traffic accidents, is described. The driver behaviours that result in speed changes of vehicles are speed, close following, braking and steering control actions. Assuming that all speed change indicates risk, several testable predictions follow. The most important of these is that there is a positive association between drivers’ celeration sum and their accidents. Formulas for the measurement of celeration and the association with crashes are presented, as well as methodological principles for this. Relevant literature is reviewed, as well as the tests of various hypotheses undertaken so far. The suggested way of measuring driver behaviour and predicting accident involvement would be useful in many kinds of studies of driver behaviour, and also for testing and screening purposes and especially for large-scale monitoring of professional drivers.     

Voluntary risk taking and skill deficits in young driver accidents in the UK

In absolute terms, young drivers have three to four times as many accidents per year as older drivers; and even allowing for their relative numbers in the population, their accident involvement is about 2.5 times higher than older drivers. A sample of 3437 accident reports was considered, including 1296 in detail, from midland police forces in the UK, involving drivers aged 17-25, and covering the years 1994-1996 inclusive. Four types of accident were identified as being of particular concern due to their high frequency: 'cross-flow'-turns; rear-end shunts; loss of control on bends; and accidents in darkness. (The term 'cross-flow' is used in relation to turns to denote an intersection accident where a driver is turning across the path of oncoming traffic, i.e., left turns in the US and continental Europe, but right turns in the UK and other countries where driving on the left side of the road is the norm.) An examination of driver risk taking behaviours as revealed in police interviews gave an insight into some of the motivational factors underlying young driver behaviour. Young driver accidents of all types are found to be frequently the result of 'risk taking' factors as opposed to 'skill deficit' factors. It had previously been thought that one of the main problems that young drivers have is in the area of specific skills needed in the driving task. However, it appears that a large percentage of their accidents are purely the result of two or three failures resulting from voluntary risk taking behaviour, rather than skill deficits per se. It is shown that specific groups of young drivers can even be considered as above average in driving skills, but simultaneously have a higher accident involvement due to their voluntary decisions to take risks.     

The contribution of on-road studies of road user behaviour to improving road safety

For over 40 years transport safety researchers have been using methods of vehicle instrumentation to gain greater insights into the factors that contribute to road user crash risk and the associated crash factors. In the previous decade in particular the widespread availability of lower cost and more advanced methods of vehicle instrumentation and recording technologies are supporting the increasing number of on-road research studies worldwide. The design of these studies ranges from multi-method studies using instrumented test vehicles and defined driving routes, to field operational tests, through to much larger and more naturalistic studies. It is timely to assess the utility of these methods for studying the influences of driver characteristics and states, the design and operation of the road system, and the influences of in-vehicle technologies on behaviour and safety for various road user groups. This special issue considers the extent to which on-road studies using vehicle instrumentation have been used to advance knowledge across these areas of road safety research. The papers included in this issue illustrate how research using instrumented test vehicles continues to generate new knowledge, and how the larger scale United States and European naturalistic and field operational test studies are providing a wealth of data about road user behaviour in real traffic. This is balanced with a number of studies that present methodological developments in data collection and analysis methods that, while promising, need further validation. The use of on-road methods to accurately describe the behaviours occurring in everyday real-world conditions, to quantify risks for safety critical events, and an improved understanding of the factors that contribute to risk, clearly has huge potential to promote further road trauma reductions.     

Factors contributing to driver choice after hitting a pedestrian in Japan

In Japan, where pedestrian deaths account for a third of road traffic fatalities, 7.4% of victims die from hit-and-run accidents. To identify determinants for drivers considering leaving an accident scene after hitting a pedestrian, environment-related, driver-related, and pedestrian-related factors were examined using Japanese national police data. Results generally confirmed the conceptual framework of previous studies, which examined hit-and-run behavior based on a classic economic cost–benefit approach. However, results suggest that effects of road-related factors and harsher legal punishments have limited influence for reducing hit-and-run likelihood after a driver hits a pedestrian. Measures to prevent hit-and-run accidents are presented herein.     

Analysis of traffic accident injury severity on Spanish rural highways using Bayesian networks

Several different factors contribute to injury severity in traffic accidents, such as driver characteristics, highway characteristics, vehicle characteristics, accidents characteristics, and atmospheric factors. This paper shows the possibility of using Bayesian Networks (BNs) to classify traffic accidents according to their injury severity. BNs are capable of making predictions without the need for pre assumptions and are used to make graphic representations of complex systems with interrelated components. This paper presents an analysis of 1536 accidents on rural highways in Spain, where 18 variables representing the aforementioned contributing factors were used to build 3 different BNs that classified the severity of accidents into slightly injured and killed or severely injured. The variables that best identify the factors that are associated with a killed or seriously injured accident (accident type, driver age, lighting and number of injuries) were identified by inference.     

Risk factors associated with traffic violations and accident severity in China

With the recent economic boom in China, vehicle volume and the number of traffic accident fatalities have become the highest in the world. Meanwhile, traffic accidents have become the leading cause of death in China. Systematically analyzing road safety data from different perspectives and applying empirical methods/implementing proper measures to reduce the fatality rate will be an urgent and challenging task for China in the coming years. In this study, we analyze the traffic accident data for the period 2006–2010 in Guangdong Province, China. These data, extracted from the Traffic Management Sector-Specific Incident Case Data Report, are the only officially available and reliable source of traffic accident data (with a sample size >7000 per year). In particular, we focus on two outcome measures: traffic violations and accident severity. Human, vehicle, road and environmental risk factors are considered. First, the results establish the role of traffic violations as one of the major risks threatening road safety. An immediate implication is: if the traffic violation rate could be reduced or controlled successfully, then the rate of serious injuries and fatalities would be reduced accordingly. Second, specific risk factors associated with traffic violations and accident severity are determined. Accordingly, to reduce traffic accident incidence and fatality rates, measures such as traffic regulations and legislation—targeting different vehicle types/driver groups with respect to the various human, vehicle and environment risk factors—are needed. Such measures could include road safety programs for targeted driver groups, focused enforcement of traffic regulations and road/transport facility improvements. Data analysis results arising from this study will shed lights on the development of similar (adjusted) measures to reduce traffic violations and/or accident fatalities and injuries, and to promote road safety in other regions.     

Cannabis use and traffic accidents in a birth cohort of young adults

Objective: to examine linkages between cannabis use and traffic accident risks in a birth cohort of 907 young New Zealanders studied from 18 to 21 years. Methods: during the course of a 21-year longitudinal study of a birth cohort of 907 New Zealand born children information was gathered on (a) annual frequency of cannabis use over the period from 18 to 21 years; (b) annual rates of traffic accidents during the period 18–21 years; (c) measures of driver behaviours and characteristics. The association between cannabis use and traffic accident risk was examined among the 907 sample members who reported driving a motor vehicle between the ages of 18 and 21 years. Results: there were statistically significant relationships between reported annual cannabis use and annual accident rates. This association was present only for ‘active’ accidents in which driver behaviours contributed to the accident; those using cannabis more than 50 times per year had estimated rates of active accidents that were 1.6 (95% CI 1.2–2.0) times higher than the rate for non-users. However, statistical control for driver behaviours and characteristics related to cannabis use (drink driving behaviour; risky/illegal driving behaviours; driver attitudes; gender) eliminated the association between cannabis use and traffic accident risks. Conclusions: although cannabis use was associated with increased risks of traffic accidents among members of this birth cohort, these increased risks appear to reflect the characteristics of the young people who used cannabis rather than the effects of cannabis use on driver performance.     

Microsimulation modelling of driver behaviour towards alternative warning devices at railway level crossings

Level crossings are amongst the most complex of road safety issues, due to the addition of rail infrastructure, trains and train operations. The differences in the operational characteristics of different warning devices together with varying crossing, traffic or/and train characteristics, cause different driver behaviour at crossings. This paper compares driver behaviour towards two novel warning devices (rumble strips and in-vehicle audio warning) with two conventional warning devices (flashing light and stop sign) at railway level crossings using microsimulation modelling. Two safety performance indicators directly related to collision risks, violation and time-to-collision, were adopted. Results indicated the active systems were more effective at reducing likely collisions compared to passive devices. With the combined application of driving simulation and traffic microsimulation modelling, traffic safety performance indicators for a level crossing can be estimated. From these, relative safety comparisons for the different traffic devices are derived, or even for absolute safety evaluation with proper calibration from field investigations.     

Exploring inattention and distraction in the SafetyNet Accident Causation Database

Distraction and inattention are considered to be very important and prevalent factors in the causation of road accidents. There have been many recent research studies which have attempted to understand the circumstances under which a driver becomes distracted or inattentive and how distraction/inattention can be prevented. Both factors are thought to have become more important in recent times partly due to the evolution of in-vehicle information and communication technology. This study describes a methodology that was developed to understand when factors such as distraction and inattention may have been contributors to crashes and also describes some of the consequences of distraction and inattention in terms of subsequent driver actions.     

Jerky driving--An indicator of accident proneness?

This study uses continuously logged driving data from 166 private cars to derive the level of jerks caused by the drivers during everyday driving. The number of critical jerks found in the data is analysed and compared with the self-reported accident involvement of the drivers. The results show that the expected number of accidents for a driver increases with the number of critical jerks caused by the driver. Jerk analyses make it possible to identify safety critical driving behaviour or “accident prone” drivers. They also facilitate the development of safety measures such as active safety systems or advanced driver assistance systems, ADAS, which could be adapted for specific groups of drivers or specific risky driving behaviour.     

Spatio-temporal analysis of road traffic accidents in Oyo State, Nigeria

Studies on road traffic accidents in developing nations have been very scanty. In Nigeria in particular not much is known about accident phenomena. This paper is an account of a scientific investigation into the spatial and temporal characteristics of road traffic accidents in Oyo State, Nigeria. The study is based, principally, on the Nigerian Police Official documented road traffic accident statistics from January 1980 to December 1984. The study examined general features of road traffic accident occurrence in the state and undertook a critical analysis of both temporal and spatial dimensions of the problem. The study identified six traffic zones that could be designated as accident Black Spots in the state, to which priority attention should be given in any road safety programme. Moreover, the study attempted to explain some of the complex factors that might account for the observed spatial and temporal variation in road accidents frequency and fatality. Significantly, the study observed a consistently high number of road accidents during the months of March, September, and December, while fluctuatingly high and low accident figures are recorded for other months of the year. Some possible reasons for this temporal trend in accident occurrence is discussed.     

Comparison of a vehicle equipped with Electronic Stability Control (ESC) to a vehicle with Four Wheel Steering (4WS)

Electronic Stability Control (ESC) and Four Wheel Steering (4WS) have been used to control the yaw rate and sideslip angle of automobiles, in order to improve stability and prevent accidents. The scope of this paper is to compare the behaviour of a vehicle equipped with no control systems, to a vehicle equipped with ESC, a vehicle equipped with 4WS and a vehicle equipped with a combination of ESC and 4WS in a series of simulated tests, using an adequate vehicle and driver model. The operating parameters of the control systems and the driver model have been optimised by using an evolution strategy. According to the results, the vehicle equipped with 4WS performed better in open-loop tests, while the vehicle equipped with ESC performed better in closed-loop tests where the vehicle is controlled by the driver model. The vehicle equipped with a combination of ESC and 4WS has achieved consistently better results in all our tests and has shown that the use of 4WS systems can augment the operation of ESC system and achieve a better safety level for future vehicles.