Probability based data analysis for road asset management

Road agencies require comprehensive, relevan and quality data describing their road assets to support their investment decisions. An investment decision support system for raod maintenance and rehabilitation mainly comprise three important supporting elements namely: road asset data, decision support tools and criteria for decision-making. Probability-based methods have played a crucial role in helping decision makers understand the relationship among road related data, asset performance and uncertainties in estimating budgets/costs for road management investment. This paper presents applications of the probability-bsed method for road asset management.

To err (on the road) is human? An on-road study of driver errors

Human error, its causes and consequences, and the ways in which it can be prevented, remain of great interest to road safety practitioners. This paper presents the findings derived from an on-road study of driver errors in which 25 participants drove a pre-determined route using MUARC's On-Road Test Vehicle (ORTeV). In-vehicle observers recorded the different errors made, and a range of other data was collected, including driver verbal protocols, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. The drivers tested made a range of different errors, with speeding violations, both intentional and unintentional, being the most common. Further more detailed analysis of a sub-set of specific error types indicates that driver errors have various causes, including failures in the wider road 'system' such as poor roadway design, infrastructure failures and unclear road rules. In closing, a range of potential error prevention strategies, including intelligent speed adaptation and road infrastructure design, are discussed.

Work-related road safety as a conduit for community road safety

The aim of this paper is to review the potential of work-related road safety as a conduit for community road safety based on research and practical experience. It covers the opportunity to target young people, family and community members through the workplace as part of a holistic approach to occupational road safety informed by the Haddon Matrix. Detailed case studies are presented based on British Telecom and Wolseley, which have both committed to community-based initiatives as part of their long-term, ongoing work-related road safety programs. Although no detailed community-based collision outcomes are available, the paper concludes that work-related road safety can be a conduit for community road safety and can provide an opportunity for researchers, policy makers and practitioners.

Driver knowledge about road fatalities in Australia

The term “road toll” quantifies road deaths and attracts media attention, particularly during Easter/Christmas holiday periods. Since the media focuses considerable attention on this issue, we might expect that this would translate into awareness among drivers the number of people killed, which in turn, would hopefully encourage safer driving. Road safety professionals are cognisant of road toll trends but there is little information available to indicate awareness of road fatalities among the general population. This research investigated awareness of fatalities on Queensland and Australian roads among Queensland drivers.

The influence of fatalistic beliefs on risky road use behavior in developing countries

There is little discussion of fatalism in the road safety literature, and limited research. However, fatalism is a potential barrier to participation in health-promoting behaviours, particularly among the populations of developing countries and to some extent in developed countries. Many people still believe in divine discretion and magical powers as causes of road crashes in different parts of the world. Fatalistic beliefs and beliefs in mystical powers and superstition appear to influence perceptions of crash risk and consequently lead people to take risks and neglect safety measures. Fatalistic beliefs may cause individuals to be resigned to risks because they cannot do anything to reduce these risks.

Road safety messages tailored for young adults : Using the Internet and encouraging protective passenger behaviour

Young drivers are at higher risk of crashes than other drivers when carrying passengers. Graduated Driver Licensing has demonstrated effectiveness in reducing fatalities however there is considerable potential for additional strategies to complement the approach. A survey with 276 young adults (aged 17-25 years, 64% females) was conducted to examine the potential and importance of strategies that are delivered via the Internet and potential strategies for passengers. Strategies delivered via the Internet represent opportunity for widespread dissemination and greater reach to young people at times convenient to them. The current study found some significant differences between males and females with regard to ways the Internet is used to obtain road safety information and the components valued in trusted road safety sites. There were also significant differences between males and females on the kinds of strategies used as passengers to promote driver safety and the context in which it occurred, with females tending to take more proactive strategies than males. In sum, young people see value in Internet delivery for passenger safety information (80% agreed/ strongly agreed) and more than 90% thought it was important to intervene while a passenger of a risky driver. Thus tailoring Internet road safety strategies to young people may differ for males and females however there is considerable potential for a passenger focus in strategies aimed at reducing young driver crashes.

Development and implementation of the areawide Dynamic ROad traffic NoisE (DRONE) simulator

This paper discusses the areawide Dynamic ROad traffic NoisE (DRONE) simulator, and its implementation as a tool for noise abatement policy evaluation. DRONE involves integrating a road traffic noise estimation model with a traffic simulator to estimate road traffic noise in urban networks. An integrated traffic simulation-noise estimation model provides an interface for direct input of traffic flow properties from simulation model to noise estimation model that in turn estimates the noise on a spatial and temporal scale. The output from DRONE is linked with a geographical information system for visual representation of noise levels in the form of noise contour maps.

Integration of a road traffic noise model (ASJ) and traffic simulation (AVENUE) for a built-up area

A road traffic noise prediction model (ASJ MODEL-1998) has been integrated with a road traffic simulator (AVENUE) to produce the Dynamic areawide Road traffic NoisE simulator-DRONE. This traffic-noise-GIS based integrated tool is upgraded to predict noise levels in built-up areas. The integration of traffic simulation with a noise model provides dynamic access to traffic flow characteristics and hence automated and detailed predictions of traffic noise. The prediction is not only on the spatial scale but also on temporal scale. The linkage with GIS gives a visual representation to noise pollution in the form of dynamic areawide traffic noise contour maps. The application of DRONE on a real world built-up area is also presented.