The call of the road : factors predicting students' car travelling intentions and behaviour

The most common daily trip for employed persons and students is the commute to and from work and/or place of study. Though there are clear environmental, health and safety benefits from using public transport instead of private vehicles for these trips, a high proportion of commuters still choose private vehicles to get to work or study. This study reports an investigation of psychological factors influencing students’ travel choices from the perspective of the Theory of Planned Behaviour (TPB). Students from 3 different university campuses (n= 186) completed a cross-sectional survey on their car commuting behaviour. Particular focus was given to whether car commuting habits could add to understanding of commuting behaviour over and above behavioural intentions. Results indicated that, as expected, behavioural intention to travel by car was the strongest TPB predictor of car commuting behaviour. Further, general car commuting habits explained additional variance over and above TPB constructs, though the contribution was modest. No relationship between habit and intentions was found. Overall results suggest that, although student car commuting behaviour is habitual in nature, it is predominantly guided by reasoned action. Implications of these findings are that in order to alter the use of private vehicles, the factors influencing commuters’ intentions to travel by car must be addressed. Specifically, interventions should target the perceived high levels of both the acceptability of commuting by car and the perceived control over the choice to commute by car.

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.

Extending life-cycle costing (LCC) analysis for sustainability considerations in road infrastructure projects

Sustainable development is about making societal investments. These investments should be in synchronization with the natural environment, trends of social development, as well as organisational and local economies over a long time span. Traditionally in the eyes of clients, project development will need to produce the required profit margins, with some degrees of consideration for other impacts. This is being changed as all citizens of our society are becoming more aware of concepts and challenges such as the climate change, greenhouse footprints, and social dimensions of sustainability, and will in turn demand answers to these issues in built facilities. A large number of R&D projects have focused on the technical advancement and environmental assessment of products and built facilities. It is equally important address the cost/benefit issue, as developers in the world would not want to loose money by investing in built assets. For infrastructure projects, due to its significant cost of development and lengthy delivery time, presenting the full money story of going green is of vital importance. Traditional views of life-cycle costing tend to focus on the pure economics of a construction project. Sustainability concepts are not broadly integrated with the current LCCA in the construction sector. To rectify this problem, this paper reports on the progress to date of developing and extending contemporary LCCA models in the evaluation of road infrastructure sustainability. The suggested new model development is based on sustainability indicators identified through previous research, and incorporating industry verified cost elements of sustainability measures. The on-going project aims to design and a working model for sustainability life-cycle costing analysis for this type of infrastructure projects.

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.

Dynamic load sharing for heavy vehicles : a new metric

Dynamic load sharing can be defined as a measure of the ability of a heavy vehicle multi-axle group to equalise load across its wheels under typical travel conditions; i.e. in the dynamic sense at typical travel speeds and operating conditions of that vehicle. Various attempts have been made to quantify the ability of heavy vehicles to equalise the load across their wheels during travel. One of these was the concept of the load sharing coefficient (LSC). Other metrics such as the dynamic load coefficient (DLC) have been used to compare one heavy vehicle suspension with another for potential road damage. This paper compares these metrics and determines a relationship between DLC and LSC with sensitivity analysis of this relationship. The shortcomings of these presently-available metrics are discussed with a new metric proposed - the dynamic load equalisation (DLE) measure.

Framework and processes for enhancing sustainability deliverables in Australian road infrastructure projects

Road and highway infrastructure provides the backbone for a nation’s economic growth. The versatile dispersion of population in Australia and its resource boom, coupled with improved living standards and growing societal expectations, calls for continuing development and improvement of road infrastructure under the current local, state and federal governments’ policies and strategic plans. As road infrastructure projects involve huge resources and mechanisms, achieving sustainability not only on economic scales but also through environmental and social responsibility becomes a crucial issue. While sustainability is a logical link to infrastructure development, literature study and consultation with the industry found that there is a lack of common understanding on what constitutes sustainability in the infrastructure context. Its priorities are often interpreted differently among multiple stakeholders. For road infrastructure projects which typically span over long periods of time, achieving tangible sustainability outcomes during the lifecycle of development remains a formidable task. Sustainable development initiatives often remain ideological as in macro-level policies and broad-based concepts. There were little elaboration and exemplar cases on how these policies and concepts can be translated into practical decision-making during project implementation. In contrast, there seemed to be over commitment on research and development of sustainability assessment methods and tools. Between the two positions, there is a perception-reality gap and mismatch, specifically on how to enhance sustainability deliverables during infrastructure project delivery. Review on past research in this industry sector also found that little has been done to promote sustainable road infrastructure development; this has wide and varied potential impacts. This research identified the common perceptions and expectations by different stakeholders towards achieving sustainability in road and highway infrastructure projects. Face to face interviews on selected representatives of these stakeholders were carried out in order to select and categorize, confirm and prioritize a list of sustainability performance targets identified through literature and past research. A Delphi study was conducted with the assistance of a panel of senior industry professionals and academic experts, which further considered the interrelationship and influence of the sustainability indicators, and identified critical sustainability indicators under ten critical sustainability criteria (e.g. Environmental, Health & Safety, Resource Utilization & Management, Social & Cultural, Economic, Public Governance & Community Engagement, Relations Management, Engineering, Institutional and Project Management). This presented critical sustainability issues that needed to be addressed at the project level. Accordingly, exemplar highway development projects were used as case studies to elicit solutions for the critical issues. Through the identification and integration of different perceptions and priority needs of the stakeholders, as well as key sustainability indicators and solutions for critical issues, a set of decision-making guidelines was developed to promote and drive consistent sustainability deliverables in road infrastructure projects.

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.

Driver behaviour and decision making at railway level crossings : An exploratory on-road case study

Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, 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. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

Developing a life-cycle costing analysis model for sustainability enhancement in road infrastructure project

With increasing pressure to provide environmentally responsible infrastructure products and services, stakeholders are putting significant foci on the early identification of financial viability and outcome of infrastructure projects. Traditionally, there has been an imbalance between sustainable measures and project budget. On one hand, the industry tends to employ the first-cost mentality and approach to developing infrastructure projects. On the other, environmental experts and technology innovators often push for the ultimately green products and systems without much of a concern for cost. This situation is being quickly changed as the industry is under pressure to continue to return profit, while better adapting to current and emerging global issues of sustainability. For the infrastructure sector to contribute to sustainable development, it will need to increase value and efficiency. Thus, there is a great need for tools that will enable decision makers evaluate competing initiatives and identify the most sustainable approaches to procuring infrastructure projects. In order to ensure that these objectives are achieved, the concept of life-cycle costing analysis (LCCA) will play significant roles in the economics of an infrastructure project. Recently, a few research initiatives have applied the LCCA models for road infrastructure that focused on the traditional economics of a project. There is little coverage of life-cycle costing as a method to evaluate the criteria and assess the economic implications of pursuing sustainability in road infrastructure projects. To rectify this problem, this paper reviews the theoretical basis of previous LCCA models before discussing their inability to determinate the sustainability indicators in road infrastructure project. It then introduces an on-going research aimed at developing a new model to integrate the various new cost elements based on the sustainability indicators with the traditional and proven LCCA approach. It is expected that the research will generate a working model for sustainability based life-cycle cost analysis.

Single camera vision-only SLAM on a suburban road network

Simultaneous Localization And Mapping (SLAM) is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision only approaches. This paper presents a method for generating approximate rotational and translation velocity information from a single vehicle-mounted consumer camera, without the computationally expensive process of tracking landmarks. The method is tested by employing it to provide the odometric and visual information for the RatSLAM system while mapping a complex suburban road network. RatSLAM generates a coherent map of the environment during an 18 km long trip through suburban traffic at speeds of up to 60 km/hr. This result demonstrates the potential of ground based vision-only SLAM using low cost sensing and computational hardware.

Contesting ‘sustainability’ in infrastructure planning : The debate of the public interest in Brisbane’s Boggo Road Busway development

Sustainable infrastructure demands that declared principles of sustainability are enacted in the processes of its implementation. However, a problem arises if the concept of sustainability is not thoroughly scrutinised in the planning process. The public interest could be undermined when the rhetoric of sustainability is used to substantiate a proposed plan. This chapter analyses the manifestation of sustainable development in the Boggo Road Busway Plan in Brisbane, Australia against the sustainability agenda set in the South East Queensland Regional and Transport Plans. Although the construction of the Busway was intended to improve public transport access in the region, its implementation drew significant environmental concerns. Local community groups contested the ‘sustainability’ concept deployed in Queensland’s infrastructure planning. Their challenges resulted in important concessions in the delivery of the Busway plan. This case demonstrates that principles of sustainable infrastructure should be measurable and that local communities be better informed in order to fulfil the public interest in regional planning.

Alternate structural system of incorporating flat bed rail wagons as low volume road bridge decks

The stimulus for this project rose from the need to find an alternative solution to aging superstructures of road-bridge in low volume roads (LVR). The solution investigated, designed and consequently plans to construct, involved replacing an aging super-structure of a 10m span bridge with Flat-Bed Rail Wagon (FBRW). The main focus of this paper is to present alternate structural system for the design of the FBRW as road bridge deck conforming to AS5100. The structural adequacy of the primary members of the FBRW was first validated using full scale experimental investigation to AS5100 serviceability and ultimate limit state loading. The bare FBRW was further developed to include a running surface. Two options were evaluated during the design phase, namely timber and reinforced concrete. First option, which is presented here, involved strengthening of the FBRW using numerous steel sections and overlaying the bridge deck with timber planks. The idea of this approach was to use all the primary and secondary members of the FBRW in load sharing and to provide additional members where weaknesses in the original members arose. The second option, which was the preferred option for construction, involved use of primary members only with an overlaying reinforced concrete slab deck. This option minimised the risk associated with any uncertainty of secondary members to its structural adequacy. The paper will report selected results of the experiment as well as the design phases of option one with conclusions highlighting the viability of option 1 and its limitations.