Mobile phone use while driving : an investigation of the beliefs influencing drivers’ hands-free and hand-held mobile phone use.

This study explored the psychological influences of hands-free and hand-held mobile phone use while driving. Participants were 796 Australian drivers aged 17 to 76 years who owned mobile phones. A cross-sectional survey assessed frequency of calling and text messaging while driving (overall, hands-free, hand-held) as well as drivers’ behavioural, normative, and control beliefs relating to mobile phone use while driving. Irrespective of handset type, 43% of drivers reported answering calls while driving on a daily basis, followed by making calls (36%), reading text messages (27%), and sending text messages (18%). In total, 63.9% of drivers did not own hands-free kits and, of the drivers that owned hand-free kits, 32% did not use it most or all of the time. Significant differences were found in the behavioural, normative, and control beliefs of frequent and infrequent users of both types of handset while driving. As expected, frequent users reported more advantages of, more approval from others for, and fewer barriers that would prevent them from, using either a hands-free or a hand-held mobile phone while driving than infrequent users. Campaigns to reduce mobile phone use while driving should attempt to minimise the perceived benefits of the behaviour and highlight the risks of this unsafe driving practice.

A decision support system for sustainable urban development : the integrated land use and transportation indexing model

The broad definition of sustainable development at the early stage of its introduction has caused confusion and hesitation among local authorities and planning professionals. The main difficulties are experience in employing loosely-defined principles of sustainable development in setting policies and goals. The question of how this theory/rhetoric-practice gap could be filled will be the theme of this study. One of the widely employed sustainability accounting approaches by governmental organisations, triple bottom line, and applicability of this approach to sustainable urban development policies will be examined. When incorporating triple bottom line considerations with the environmental impact assessment techniques, the framework of GIS-based decision support system that helps decision-makers in selecting policy option according to the economic, environmental and social impacts will be introduced. In order to embrace sustainable urban development policy considerations, the relationship between urban form, travel pattern and socio-economic attributes should be clarified. This clarification associated with other input decision support systems will picture the holistic state of the urban settings in terms of sustainability. In this study, grid-based indexing methodology will be employed to visualise the degree of compatibility of selected scenarios with the designated sustainable urban future. In addition, this tool will provide valuable knowledge about the spatial dimension of the sustainable development. It will also give fine details about the possible impacts of urban development proposals by employing disaggregated spatial data analysis (e.g. land-use, transportation, urban services, population density, pollution, etc.). The visualisation capacity of this tool will help decision makers and other stakeholders compare and select alternative of future urban developments.

Drivers' and cyclists' experiences of sharing the road : incidents, attitudes and perceptions of visibility

This study explored the beliefs and attitudes of cyclists and drivers regarding cyclist visibility, use of visibility aids and crashes involving cyclists and motorists. Data are presented for 1460 participants (622 drivers and 838 cyclists) and demonstrate that there are high rates of cyclist–vehicle crashes, many of which were reported to be due to the driver not seeing the cyclist in time to avoid a collision. A divergence in attitudes was also apparent in terms of attribution of responsibility in cyclist–vehicle conflicts on the road. While the use of visibility aids was advocated by cyclists, this was not reflected in self-reported wearing patterns, and cyclists reported that the distance at which they would be first recognised by a driver was twice that estimated by the drivers. Collectively, these results suggest that interventions should target cyclists’ use of visibility aids, which is less than optimal in this population, as well as re-educating both groups regarding visibility issues.

The on-road difficulties of older drivers and their relationship with self-reported motor vehicle crashes

OBJECTIVES: To quantify the driving difficulties of older adults using a detailed assessment of driving performance and to link this with self-reported retrospective and prospective crashes. DESIGN: Prospective cohort study. SETTING: On-road driving assessment. PARTICIPANTS: Two hundred sixty-seven community-living adults aged 70 to 88 randomly recruited through the electoral roll. MEASUREMENTS: Performance on a standardized measure of driving performance. RESULTS: Lane positioning, approach, and blind spot monitoring were the most common error types, and errors occurred most frequently in situations involving merging and maneuvering. Drivers reporting more retrospective or prospective crashes made significantly more driving errors. Driver instructor interventions during self-navigation (where the instructor had to brake or take control of the steering to avoid an accident) were significantly associated with higher retrospective and prospective crashes; every instructor intervention almost doubled prospective crash risk. CONCLUSION: These findings suggest that on-road driving assessment provides useful information on older driver difficulties, with the self-directed component providing the most valuable information.

Towards an automatic road lane marks extraction based on ISODATA segmentation and shadow detection from large-scale aerial images

The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

Mobility and safety are conflicting goals for transport policy makers when making decisions about graduated driver licensing

Policy decisions are frequently influenced by more than research results alone. This review examines one road safety countermeasure, graduated driver licensing, in three jurisdictions and identifies how the conflict between mobility and safety goals can influence policy decisions relating to this countermeasure. Evaluations from around the world of graduated driver licensing have demonstrated clear reductions in crashes for young drivers. However, the introduction of this countermeasure may be affected, both positively and negatively, by the conflict some policy makers experience between ensuring individuals remain both mobile and safe as drivers. This review highlights how this conflict in policy decision making can serve to either facilitate or hinder the introduction of graduated driver licensing systems. However, policy makers whose focus on mobility is too strong when compared with safety may be mistaken, with evidence suggesting that after a graduated driver licensing system is introduced young drivers adapt their behaviour to the new system and remain mobile. As a result, policy makers should consciously acknowledge the conflict between mobility and safety and consider an appropriate balance in order to introduce these systems. Improvements to the licensing system can then be made in an incremental manner as the balance between these two priorities change. Policy makers can achieve an appropriate balance by using empirical evidence as a basis for their decisions.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

Road network extraction with new vectorization and pruning from high-resolution RS images

With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.

Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

The application of the Park & Ride and TOD concepts to develop a new framework that can maximise public transport patronage

With growing concern over the use of the car in our urbanized society, there have emerged a number of lobby groups and professional bodies promoting a return to public transport, walking and cycling, with the urban village as the key driving land use, as a means of making our cities’ transportation systems more sustainable. This research has aimed at developing a framework applicable to the Australian setting that can facilitate increased passenger patronage of rail based urban transport systems from adjacent or associated land uses. The framework specifically tested the application of the Park & Ride and Transit Oriented Development (TOD) concepts and their applicability within the cultural, institutional, political and transit operational characteristics of Australian society. The researcher found that, although the application of the TOD concept had been limited to small pockets of town houses and mixed use developments around stations, the development industry and emerging groups within the community are posed to embrace the concept and bring with it increased rail patronage. The lack of a clear commitment to infrastructure and supporting land uses is a major barrier to the implementation of TODs. The research findings demonstrated significant scope for the size of a TOD to expand to a much greater radius of activity from the public transport interchange, than the commonly quoted 400 to 600 meters, thus incorporating many more residents and potential patrons. The provision of Park & Rides, and associated support facilities like Kiss & Rides, have followed worldwide trends of high patronage demands from the middle and outer car dependent suburbs of our cities. The data collection and analysis gathered by the researcher demonstrated that in many cases Park & Rides should form part of a TOD to ensure ease of access to rail stations by all modes and patron types. The question, however, remains how best to plan the incorporation of a Park & Ride within a TOD and still maintain those features that attract and promote TODs as a living entity.

Direct and indirect effects on households’ intentions to replace the old car

With the purpose of testing the hypothesis that households’ intentions to replace their old car have a direct negative relationship to its perceived quality (‘current level’) and a direct positive relationship to their aspirations for a new car (‘aspiration level’), a rotating panel of car owners were interviewed every fourth month during 2 years. In this data set the hypothesis received support. In addition the results showed that the age of the car, the total number of miles driven, and the number of anticipated repairs affected the current level, whereas marital status, the number of children, consumer confidence, and environmental concern affected the aspiration level.

The silk road project : dance and embodiment in the age of motion capture

The Silk Road Project was a practice-based research project investigating the potential of motion capture technology to inform perceptions of embodiment in dance performance. The project created a multi-disciplinary collaborative performance event using dance performance and real-time motion capture at Deakin University’s Deakin Motion Lab. Several new technological advances in producing real-time motion capture performance were produced, along with a performance event that examined the aesthetic interplay between a dancer’s movement and the precise mappings of its trajectories created by motion capture and real-time motion graphic visualisations.