Emerging research methods and their application to road safety

The study of road safety has seen great strides over the past few decades with advances in analytical methods and research tools that allow researchers to provide insights into the complex interactions of the driver, vehicle, and roadway. Data collection methods range from traditional traffic and roadway sensors to instrumented vehicles and driving simulators, capable of providing detailed data on both the normal driving conditions and the circumstances surrounding a safety critical event. In September 2011, the Third International Conference on Road Safety and Simulation was held in Indianapolis, Indiana, USA, which was hosted by the Purdue University Center for Road Safety and sponsored by the Transportation Research Board and its three committees: ANB20 Safety Data, Analysis and Evaluation, AND30 Simulation and Measurement of Vehicle and Operator Performance, and ABJ95 Visualization in Transportation. The conference brought together two hundred researchers from all over the world demonstrating some of the latest research methods to quantify crash causality and associations, and model road safety. This special issue is a collection of 14 papers that were presented at the conference and then peer-reviewed through this journal. These papers showcase the types of analytical tools needed to examine various crash types, the use of naturalistic and on-road data to validate the use of surrogate measures of safety, and the value of driving simulators to examine high-risk situations.     

The driver,the road,the rules … and the rest? A systems-based approach to young driver road safety

The persistent overrepresentation of young drivers in road crashes is universally recognised. A multitude of factors influencing their behaviour and safety have been identified through methods including crash analyses, simulated and naturalistic driving studies, and self-report measures. Across the globe numerous, diverse, countermeasures have been implemented; the design of the vast majority of these has been informed by a driver-centric approach. An alternative approach gaining popularity in transport safety is the systems approach which considers not only the characteristics of the individual, but also the decisions and actions of other actors within the road transport system, along with the interactions amongst them. This paper argues that for substantial improvements to be made in young driver road safety, what has been learnt from driver-centric research needs to be integrated into a systems approach, thus providing a holistic appraisal of the young driver road safety problem. Only then will more effective opportunities and avenues for intervention be realised.     

The development of a naturalistic data collection system to perform critical incident analysis: an investigation of safety and fatigue issues in long-haul trucking

Traditionally, both epidemiological and empirical methods have been used to assess driving safety. This paper describes an alternative, hybrid, naturalistic approach to data collection that shares advantages with each traditional approach. Though this naturalistic approach draws on elements of several safety techniques that have been developed in the past, including the Hazard Analysis Technique, instrumented vehicle studies, and fleet studies of driving safety interventions, it has a number of unique elements. Sophisticated instrumented vehicles collected over 400,000 km of commercial vehicle data to address the long-haul trucking application described in this paper. The development of this data collection and analysis method and data collection instrumentation has resulted in a set of valuable tools to advance the current state-of-the-practice in driving safety assessment. An application of this unique approach to a study of long-haul truck driver performance, behavior, and fatigue is described herein.     

Is naturalistic driving research possible with highly instrumented cars? Lessons learnt in three research centres

This paper provides an overview of the experiences using Highly Instrumented Cars (HICs) in three research Centres across Europe; Spain, the UK and Greece. The data collection capability of each car is described and an overview presented relating to the relationship between the level of instrumentation and the research possible. A discussion then follows which considers the advantages and disadvantages of using HICs for ND research. This includes the obtrusive nature of the data collection equipment, the cost of equipping the vehicles with sophisticated Data Acquisition Systems (DAS) and the challenges for data storage and analysis particularly with respect to video data. It is concluded that the use of HICs substantially increases the depth of knowledge relating to the driver's behaviour and their interaction with the vehicle and surroundings. With careful study design and integration into larger studies with Low(ly) instrumented Cars (LICs), HICs can contribute significantly and in a relatively naturalistic manner to the driver behaviour research.     

The view from the road: The contribution of on-road glance-monitoring technologies to understanding driver behavior

Using glance-monitoring technologies for on-road studies is an excellent way to investigate driver behaviors in an ecologically valid setting. Recent advances in glance-monitoring technologies have made it possible to conduct on-road studies of drivers’ glance behavior that heretofore were simply not possible. Yet it is not always easy to determine which glance-monitoring technology to use for a particular application. Here, we first identify the generic capabilities of the various glance-monitoring technologies. We then describe how particular glance-monitoring technologies have been used in the field to (a) identify the skill deficiencies of novice and older drivers, (b) evaluate the effectiveness of training programs that are designed to reduce deficits in these skills, and (c) address interface issues both inside (e.g., collision warning systems) and outside (e.g., yield markings) the vehicle. The limitations and advantages of on-road eye-tracking and the associated glance-monitoring technologies are identified throughout. A comparison, where possible, is made between the results of on-road eye-tracking studies of drivers’ behaviors and the results of those studies conducted in the laboratory. Overall, the use of appropriate on-road glance-monitoring technologies has greatly enhanced our theoretical understanding of why drivers behave the way they do, and this knowledge has paved the way for significant improvements in road user safety.     

A conceptual framework for road safety and mobility applied to cycling safety

Scientific literature lacks a model which combines exposure to risk, risk, and the relationship between them. This paper presents a conceptual road safety framework comprising mutually interacting factors for exposure to risk resulting from travel behaviour (volumes, modal split, and distribution of traffic over time and space) and for risk (crash and injury risk). The framework's three determinants for travel behaviour are locations of activities; resistances (generalized transport costs); needs, opportunities, and abilities. Crash and injury risks are modelled by the three ‘safety pillars’: infrastructure, road users and the vehicles they use. Creating a link in the framework between risk and exposure is important because of the ‘non-linear relationship’ between them, i.e. risk tends to decrease as exposure increases. Furthermore, ‘perceived’ risk (a type of travel resistance) plays a role in mode choice, i.e. the perception that a certain type of vehicle is unsafe can be a deterrent to its use. This paper uses theories to explain how the elements in the model interact. Cycling is an area where governments typically have goals for both mobility and safety. To exemplify application of the model, the paper uses the framework to link research on cycling (safety) to land use and infrastructure. The model's value lies in its ability to identify potential consequences of measures and policies for both exposure and risk. This is important from a scientific perspective and for policy makers who often have objectives for both mobility and safety.     

Driving speed and the risk of road crashes: a review

Driving speed is an important factor in road safety. Speed not only affects the severity of a crash, but is also related to the risk of being involved in a crash. This paper discusses the most important empirical studies into speed and crash rate with an emphasis on the more recent studies. The majority of these studies looked at absolute speed, either at individual vehicle level or at road section level. Respectively, they found evidence for an exponential function and a power function between speed and crash rate. Both types of studies found evidence that crash rate increases faster with an increase in speed on minor roads than on major roads. At a more detailed level, lane width, junction density, and traffic flow were found to interact with the speed-crash rate relation. Other studies looked at speed dispersion and found evidence that this is also an important factor in determining crash rate. Larger differences in speed between vehicles are related to a higher crash rate. Without exception, a vehicle that moved (much) faster than other traffic around it, had a higher crash rate. With regard to the rate of a (much) slower moving vehicle, the evidence is inconclusive.     

Use of crash surrogates and exceedance statistics to estimate road safety

The limited ability of existing safety models to properly reflect crash causality has its source in cross-sectional analysis applied to the estimation of the intrinsically complex safety factors with highly aggregated and frequently poor quality of data. The adequacy of the data may be improved thanks to the unprecedented progress in sensing technologies and the invention of the naturalistic driving method of data collection. Proposed in this paper is a new modeling paradigm that integrates several types of safety models. The primary improvement results from a more adequate representation of the crash occurrence process by incorporating crash precursor events into the modeling framework. A Pareto-based estimating method for the likelihood of a collision occurrence, given a precursor event, is explained and illustrated with the simple example of road departures.     

Are SUVs dangerous vehicles?

This study was a population cohort study of all licensed passenger vehicles in New Zealand in the years 2005–2006. The objective of the study was to evaluate the effect on road safety of sports utility vehicles (SUVs) compared to other passenger vehicle types. Statistical models were fitted to the population of 2,996,000 vehicles of which 17,245 were involved in an injury crash. Controlling for distance driven, vehicle and owner characteristics, SUVs were found to be relatively safe vehicles in terms of injury crash involvement and in terms of the injury rate of their own occupants or other road users into which they crashed. Current research on SUV safety clearly shows them to be a road safety concern, but only once a collision occurs. The present study shows that SUVs in New Zealand have relatively few collisions compared to other passenger vehicle types, allowing for factors such as distance driven, some allowance for the type of driving exposure (via the owners’ addresses) and for owner age and gender. Overall, the vehicle type implicated most frequently in injury crashes and involving the highest rate of road injuries was sports cars, causing clearly the most harm per licensed vehicle. Instead of concerning themselves primarily with SUVs, the focus of road safety agencies should be on the relatively high crash risk of sports cars, which are clearly a road safety concern. Their high crash involvement rate and injury rate is likely to be largely due to the way they are driven rather than to inherent characteristics of the vehicles themselves.     

Computational and experimental crash analysis of the road safety barrier

The paper describes the computational analysis and experimental crash tests of a new road safety barrier. The purpose of this research was to develop and evaluate a full-scale computational model of the road safety barrier for use in crash simulations and to further compare the computational results with real crash test data. The impact severity and stiffness of the new design have been evaluated with the dynamic nonlinear elasto-plastic analysis of the three-dimensional road safety barrier within the framework of the finite element method with LS-DYNA code. Comparison of computational and experimental results proved the correctness of the computational model. The tests have also shown that the new safety barrier assures controllable crash energy absorption which in turn increases the safety of vehicle occupants.     

Do not blame the driver: A systems analysis of the causes of road freight crashes

Although many have advocated a systems approach in road transportation, this view has not meaningfully penetrated road safety research, practice or policy. In this study, a systems theory-based approach, Rasmussens’s (1997) risk management framework and associated Accimap technique, is applied to the analysis of road freight transportation crashes. Twenty-seven highway crash investigation reports were downloaded from the National Transport Safety Bureau website. Thematic analysis was used to identify the complex system of contributory factors, and relationships, identified within the reports. The Accimap technique was then used to represent the linkages and dependencies within and across system levels in the road freight transportation industry and to identify common factors and interactions across multiple crashes. The results demonstrate how a systems approach can increase knowledge in this safety critical domain, while the findings can be used to guide prevention efforts and the development of system-based investigation processes for the heavy vehicle industry. A research agenda for developing an investigation technique to better support the application of the Accimap technique by practitioners in road freight transportation industry is proposed.     

Prevalence and factors associated with road traffic crash among taxi drivers in Hanoi,Vietnam

Injury due to road traffic crash is a major cause of ill health and premature deaths in developing countries. Taxis provide a main mode of public transport in Vietnam but there has been little research on the risk of crash for taxi drivers. This retrospective study collected information on taxi crashes for the period 2006–2009 by interviewing drivers from five taxi companies in Hanoi, Vietnam, using a structured questionnaire. Of the total 1214 participants recruited, 276 drivers reported at least one crash, giving an overall crash prevalence of 22.7%. Among the crashed group, 50 drivers (18.1%) were involved in two to four crashes. Logistic regression analysis further identified age of driver, type of driving licence, employment status, perceived sufficiency of income, seat-belt usage, and traffic infringement history to be significantly associated with the crash risk. Further prospective and qualitative studies are recommended to provide detailed crash characteristics as well as behaviour and perception of taxi drivers, so that an effective intervention can be developed to improve road safety and to prevent injury of these commercial drivers.     

An empirical analysis of farm vehicle crash injury severities on Iowa's public road system

Farm vehicle crashes are a major safety concern for farmers as well as all other users of the public road system in agricultural states. Using data on farm vehicle crashes that occurred on Iowa's public roads between 2004 and 2006, we estimate a multinomial logit model to identify crash-, farm vehicle-, and driver-specific factors that determine farm vehicle crash injury severity outcomes. Estimation findings indicate that there are crash patterns (rear-end manner of collision; single-vehicle crash; farm vehicle crossed the centerline or median) and conditions (obstructed vision and crash in rural area; dry road, dark lighting, speed limit 55 mph or higher, and harvesting season), as well as farm vehicle and driver-contributing characteristics (old farm vehicle, young farm vehicle driver), where targeted intervention can help reduce the severity of crash outcomes. Determining these contributing factors and their effect is the first step to identifying countermeasures and safety strategies in a bid to improve transportation safety for all users on the public road system in Iowa as well as other agricultural states.     

Estimating the human recovery costs of seriously injured road crash casualties

Road crashes result in substantial trauma and costs to societies around the world. Robust costing methods are an important tool to estimate costs associated with road trauma, and are key inputs into policy development and cost–benefit analysis for road safety programmes and infrastructure projects. With an expanding focus on seriously injured road crash casualties, in addition to the long standing focus on fatalities, methods for costing seriously injured casualties are becoming increasingly important. Some road safety agencies are defining a seriously injured casualty as an individual that was admitted to hospital following a road crash, and as a result, hospital separation data provide substantial potential for estimating the costs associated with seriously injured road crash casualties. The aim of this study is to establish techniques for estimating the human recovery costs of (non-fatal) seriously injured road crash casualties directly from hospital separation data. An individuals’ road crash-related hospitalisation record and their personal injury insurance claim were linked for road crashes that occurred in New South Wales, Australia. These records provided the means for estimating all of the costs to the casualty directly related to their recovery from their injuries. A total of 10,897 seriously injured road crash casualties were identified and four methods for estimating their recovery costs were examined, using either unit record or aggregated hospital separation data. The methods are shown to provide robust techniques for estimating the human recovery costs of seriously injured road crash casualties, that may prove useful for identifying, implementing and evaluating safety programmes intended to reduce the incidence of road crash-related serious injuries.     

Estimation of rear-end vehicle crash frequencies in urban road tunnels

According to The Handbook of Tunnel Fire Safety, over 90% (55 out of 61 cases) of fires in road tunnels are caused by vehicle crashes (especially rear-end crashes). It is thus important to develop a proper methodology that is able to estimate the rear-end vehicle crash frequency in road tunnels. In this paper, we first analyze the time to collision (TTC) data collected from two road tunnels of Singapore and conclude that Inverse Gaussian distribution is the best-fitted distribution to the TTC data. An Inverse Gaussian regression model is hence used to establish the relationship between the TTC and its contributing factors. We then proceed to introduce a new concept of exposure to traffic conflicts as the mean sojourn time in a given time period that vehicles are exposed to dangerous scenarios, namely, the TTC is lower than a predetermined threshold value. We further establish the relationship between the proposed exposure to traffic conflicts and crash count by using negative binomial regression models. Based on the limited data samples used in this study, the negative binomial regression models perform well although a further study using more data is needed.     

Under-reporting of road crash casualties in France

INTRODUCTION: Police crash data, which are the basis for safety research in most countries, are incomplete and biased. We focus here on the extent of under-reporting in France, and how it is related to casualty and crash characteristics. METHODS: Police data are compared with a road trauma registry, on the Rh?ne county, after record-linkage. The study covers the 1997-2001 period, totalling 59,714 casualties. A multivariate analysis is conducted, modelling the probability of being police-reported among casualties in the registry, as a function of crash and casualty characteristics. Results are expressed as relative risks (RR) and adjusted probabilities. RESULTS: Police reporting rate is 37.7%. Under-reporting varies mainly according to injury severity (RR=0.35 for slightly injured versus severely injured), to road user type and third party involvement (yes/no): comparing casualties with no third party versus those with one, RR=0.32 among motorcyclists whereas RR=0.78 among car occupants. Under-reporting also varies with road type, road environment (metropole/rural) and type of police force, all of which are structurally dependent. CONCLUSION: Any study based on police crash data may be quite misleading. We are therefore working on obtaining unbiased estimates of road casualties figures, by extrapolating the Rh?ne road trauma registry to the nation-wide level.     

Road safety performance indicators for the interurban road network

Various road safety performance indicators (SPIs) have been proposed for different road safety research areas, mainly as regards driver behaviour (e.g. seat belt use, alcohol, drugs, etc.) and vehicles (e.g. passive safety); however, no SPIs for the road network and design have been developed. The objective of this research is the development of an SPI for the road network, to be used as a benchmark for cross-region comparisons. The developed SPI essentially makes a comparison of the existing road network to the theoretically required one, defined as one which meets some minimum requirements with respect to road safety. This paper presents a theoretical concept for the determination of this SPI as well as a translation of this theory into a practical method. Also, the method is applied in a number of pilot countries namely the Netherlands, Portugal, Greece and Israel. The results show that the SPI could be efficiently calculated in all countries, despite some differences in the data sources. In general, the calculated overall SPI scores were realistic and ranged from 81 to 94%, with the exception of Greece where the SPI was relatively lower (67%). However, the SPI should be considered as a first attempt to determine the safety level of the road network. The proposed method has some limitations and could be further improved. The paper presents directions for further research to further develop the SPI.     

Toll road crashes of commercial and passenger motor vehicles

Revenue-collection data from toll roads allow for accurate estimates of miles driven by vehicle type and, when combined with crash data, valid estimates of crash involvements per mile driven. Data on vehicle-miles traveled and collisions were obtained from toll road authorities in Florida. Kansas, and New York. In addition, state crash files and published vehicle-miles of travel were obtained for toll roads in Illinois. Indiana, Ohio, and Pennsylvania. Large commercial motor vehicles were significantly underinvolved in single-vehicle crashes on all state toll roads. In five states, commercial motor vehicles were significantly overinvolved in multiple-vehicle crashes relative to passenger vehicles; the exceptions were Kansas, where they had significantly lower multiple-vehicle involvement rates, and Indiana. where there were no significant differences in multiple-vehicle involvements by vehicle type. The risk of commercial motor vehicle involvement in multiple-vehicle crashes resulting in deaths or serious injuries was double that of passenger vehicles in the two states (Ohio and Pennsylvania) that identified serious injuries. Whether crash rates, on toll roads of commercial motor vehicles are higher or lower than those of passenger vehicles appears to depend on the type of crash, specific toll road. and traffic density.     

Road user behaviour changes following a self-explaining roads intervention

The self-explaining roads (SER) approach uses road designs that evoke correct expectations and driving behaviours from road users to create a safe and user-friendly road network. Following the implementation of an SER process and retrofitting of local and collector roads in a suburb within Auckland City, lower speeds on local roads and less variation in speed on both local and collector roads were achieved, along with a closer match between actual and perceived safe speeds. Preliminary analyses of crash data shows that the project has resulted in a 30% reduction crash numbers and an 86% reduction in crash costs per annum, since the road changes were completed. In order to further understand the outcomes from this project, a study was carried out to measure the effects of the SER intervention on the activity and behaviour of all road users. Video was collected over nine separate days, at nine different locations, both before and after SER construction. Road user behaviour categories were developed for all potential road users at different location types and then used to code the video data. Following SER construction, on local roads there was a relatively higher proportion of pedestrians, less uniformity in vehicle lane keeping and less indicating by motorists along with less through traffic, reflecting a more informal/low speed local road environment. Pedestrians were less constrained on local roads following SER construction, possibly reflecting a perceptually safer and more user-friendly environment. These behaviours were not generally evident on collector roads, a trend also shown by the previous study of speed changes. Given that one of the objectives of SER is to match road user behaviour with functionally different road categories, the road user behaviour differences demonstrated on different road types within the SER trial area provides further reinforcement of a successful SER trial.