Understanding neighbourhood liveability for older urban Australians

As with other major developed cities, the sub-tropical and fastest growing Australian capital city of Brisbane has adopted policies designed to increase residential densities and meet the liveability and sustainability goal of decreasing car dependence and greenhouse gas emissions. This goal hinges on a pedestrian friendly environment and walkable proximity to satisfy everyday needs. While older people are particularly attracted to sub-tropical urban environments, there has been little empirical evidence linking liveability satisfaction and perceived and actual use of older people’s urban neighbourhood. Using qualitative (diaries and in-depth interviews) and quantitative (Global Positioning Systems and Geographical Information Systems mapping) liveability research data this paper explores whether high density supports liveability and is sustainable for older people living in a sub-tropical urban environment. This paper links satisfaction and perceived use of the sub-tropical urban Brisbane environment with actual mapped characteristics and use. Linking the two methods (both quantitative and qualitative) is important in obtaining a greater understanding of human behaviour and the lived world of older urban Australians and in providing a wider picture of sub-tropical urban neighbourhoods for a significant population group within those neighbourhoods. What emerges from the research is an uneven standard of design, provision of amenities and maintenance of the public realm which negatively impacts on local neighbourhood participation by older urban Australians. By highlighting these issues this research furthers the understanding of design factors which make the sub-tropical urban neighbourhood more liveable and sustainable for older people and will inform actionable and implementable policies, programs and designs.

Experiences of neighbourhood walkability among older Australians living in high density inner-city areas

Walking as an out-of-home mobility activity is recognised for its contribution to healthy and active ageing. The environment can have a powerful effect on the amount of walking activity undertaken by older people, thereby influencing their capacity to maintain their wellbeing and independence. This paper reports the findings from research examining the experiences of neighbourhood walking for 12 older people from six different inner-city high density suburbs, through analysis of data derived from travel diaries, individual time/space activity maps (created via GPS tracking over a seven-day period and GIS technology), and in-depth interviews. Reliance on motor vehicles, the competing interests of pedestrians and cyclists on shared pathways and problems associated with transit systems, public transport, and pedestrian infrastructure emerged as key barriers to older people venturing out of home on foot. GPS and GIS technology provide new opportunities for furthering understanding of the out-of-home mobility of older populations.

Using advanced traits of passengers to facilitate route-choice decision-making

Research interest in pedestrian behaviour spans the retail industry, emergency services, urban planners and other agencies. Most models to simulate and model pedestrian movement can be distinguished on the basis of geographical scale, from the micro-scale movement of obstacle avoidance, through the meso-scale of individuals planning multi-stop shopping trips, up to the macro-scale of overall flow of masses of people between places. In this paper, route-choice decision-making model is devised for modelling passengers flow in airport terminal. A set of devised advanced traits of passengers is firstly proposed. Advanced traits take into account a passenger’s cognitive preferences and demonstrate underlying motivations of route-choice decisions. Although the activities of passengers are normally regarded as stochastic and sometimes unpredictable, real scenarios of passenger flows are basically feasible to be compared with virtual simulations in terms of tactical route-choice decision-making. Passengers in the model are as intelligent agents who possess a bunch of initial basic traits and are categorized into five distinguish groups in terms of routing preferences. Route choices are consecutively determined by inferring current advanced traits according to the utility matrix.

Reducing road related injuries for young adolescents : an investigation of truancy as a risk factor

Truancy is recognised as an indicator of engagement in high-risk behaviours for adolescents. Injuries from road related risk behaviours continue to be a leading cause of death and disability for early adolescents (13-14 years). The aim of this research is to determine the extent to which truancy relates to increased risk of road related injuries for early adolescents. Four hundred and twenty-seven Year 9 students (13-14 years) from five high schools in Queensland, Australia, completed a questionnaire about their perceptions of risk and recent injury experience. Self-reported injuries were assessed by the Extended Adolescent Injury Checklist (E-AIC). Injuries resulting from motorcycle use, bicycle use, vehicle use (as passenger or driver), and as a pedestrian were measured for the preceding three months. Students were also asked to indicate whether they sought medical attention for their injuries. Truancy rates were assessed from self-reported skipping class or wagging school over the same three month period. The findings explore the relationship between early adolescent truancy and road related injuries. The relationship between road related injuries and truancy was analysed separately for males and females. Results of this study revealed that road related injuries and reports of associated medical treatment are higher for young people who engage in truancy when compared with non-truant adolescents. The results of this study contribute knowledge about truancy as a risk factor for engagement in road related risks. The findings have the potential to enhance school policies and injury prevention programs if emphasis is placed on increasing school attendance as a safety measure to decrease road related injuries for young adolescents.

V1-inspired features induce a weighted margin in SVMs

Image representations derived from simplified models of the primary visual cortex (V1), such as HOG and SIFT, elicit good performance in a myriad of visual classification tasks including object recognition/detection, pedestrian detection and facial expression classification. A central question in the vision, learning and neuroscience communities regards why these architectures perform so well. In this paper, we offer a unique perspective to this question by subsuming the role of V1-inspired features directly within a linear support vector machine (SVM). We demonstrate that a specific class of such features in conjunction with a linear SVM can be reinterpreted as inducing a weighted margin on the Kronecker basis expansion of an image. This new viewpoint on the role of V1-inspired features allows us to answer fundamental questions on the uniqueness and redundancies of these features, and offer substantial improvements in terms of computational and storage efficiency.

Trends in cycling patterns and interactions with pedestrians in the city centre

All levels of government continue to advocate increasing the number of people cycling for recreation and transport. However, governments and the general public still have concerns about the implications for the safety of cyclists and other road users. While there is concern about injury for bicycle-pedestrian collisions, for 2008-09 in Australia only 40 pedestrians were hospitalised as a result of a collision with a cyclist (and 33 cyclists from collisions with pedestrians). There is little research that observes changes over time in actual cyclist behaviours and interactions with other road users. This paper presents the results of an observational study of cycling in the Brisbane Central Business District based on data collected using the same methodology in October 2010 and 2012.

Crisis response planning in tunnel and road networks

Critical road infrastructure (such as tunnels and overpasses) is of major significance to society and constitutes major components of interdependent, ‘systems and networks’. Failure in critical components of these wide area infrastructure systems can often result in cascading disturbances with secondary and tertiary impacts - some of which may become initiating sources of failure in their own right, triggering further systems failures across wider networks. Perrow1) considered the impact of our increasing use of technology in high-risk fields, analysing the implications on everyday life and argued that designers of these types of infrastructure systems cannot predict every possible failure scenario nor create perfect contingency plans for operators. Challenges exist for transport system operators in the conceptualisation and implementation of response and subsequent recovery planning for significant events. Disturbances can vary from reduced traffic flow causing traffic congestion throughout the local road network(s) and subsequent possible loss of income to businesses and industry to a major incident causing loss of life or complete loss of an asset. Many organisations and institutions, despite increasing recognition of the effects of crisis events, are not adequately prepared to manage crises2). It is argued that operators of land transport infrastructure are in a similar category of readiness given the recent instances of failures in road tunnels. These unexpected infrastructure failures, and their ultimately identified causes, suggest there is significant room for improvement. As a result, risk profiles for road transport systems are often complex due to the human behaviours and the inter-mix of technical and organisational components and the managerial coverage needed for the socio-technical components and the physical infrastructure. In this sense, the span of managerial oversight may require new approaches to asset management that combines the notion of risk and continuity management. This paper examines challenges in the planning of response and recovery practices of owner/operators of transport systems (above and below ground) in Australia covering: • Ageing or established infrastructure; and • New-build infrastructure. With reference to relevant international contexts this paper seeks to suggest options for enhancing the planning and practice for crisis response in these transport networks and as a result support the resilience of Critical Infrastructure.

Towards the retrieval of accurate OD matrices from Bluetooth data : lessons learned from 2 years of data

The Bluetooth technology is being increasingly used to track vehicles throughout their trips, within urban networks and across freeway stretches. One important opportunity offered by this type of data is the measurement of Origin-Destination patterns, emerging from the aggregation and clustering of individual trips. In order to obtain accurate estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. These issues mainly stem from the use of the Bluetooth technology amongst drivers, and the physical properties of the Bluetooth sensors themselves. First, not all cars are equipped with discoverable Bluetooth devices and the Bluetooth-enabled vehicles may belong to some small socio-economic groups of users. Second, the Bluetooth datasets include data from various transport modes; such as pedestrian, bicycles, cars, taxi driver, buses and trains. Third, the Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be extracted from the data. Finally, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

Detecting anomalous events at railway level crossings

Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

Agent-based model of passenger flows in airport terminals

Passenger flow studies in airport terminals have shown consistent statistical relationships between airport spatial layout and pedestrian movement, facilitating prediction of movement from terminal designs. However, these studies are done at an aggregate level and do not incorporate how individual passengers make decisions at a microscopic level. Therefore, they do not explain the formation of complex movement flows. In addition, existing models mostly focus on standard airport processing procedures such as immigration and security, but seldom consider discretionary activities of passengers, and thus are not able to truly describe the full range of passenger flows within airport terminals. As the route-choice decision-making of passengers involves many uncertain factors within the airport terminals, the mechanisms to fulfill the capacity of managing the route-choice have proven difficult to acquire and quantify. Could the study of cognitive factors of passengers (i.e. human mental preferences of deciding which on-airport facility to use) be useful to tackle these issues? Assuming the movement in virtual simulated environments can be analogous to movement in real environments, passenger behaviour dynamics can be similar to those generated in virtual experiments. Three levels of dynamics have been devised for motion control: the localised field, tactical level, and strategic level. A localised field refers to basic motion capabilities, such as walking speed, direction and avoidance of obstacles. The other two fields represent cognitive route-choice decision-making. This research views passenger flow problems via a "bottom-up approach", regarding individual passengers as independent intelligent agents who can behave autonomously and are able to interact with others and the ambient environment. In this regard, passenger flow formation becomes an emergent phenomenon of large numbers of passengers interacting with others. In the thesis, first, the passenger flow in airport terminals was investigated. Discretionary activities of passengers were integrated with standard processing procedures in the research. The localised field for passenger motion dynamics was constructed by a devised force-based model. Next, advanced traits of passengers (such as their desire to shop, their comfort with technology and their willingness to ask for assistance) were formulated to facilitate tactical route-choice decision-making. The traits consist of quantified measures of mental preferences of passengers when they travel through airport terminals. Each category of the traits indicates a decision which passengers may take. They were inferred through a Bayesian network model by analysing the probabilities based on currently available data. Route-choice decision-making was finalised by calculating corresponding utility results based on those probabilities observed. Three sorts of simulation outcomes were generated: namely, queuing length before checkpoints, average dwell time of passengers at service facilities, and instantaneous space utilisation. Queuing length reflects the number of passengers who are in a queue. Long queues no doubt cause significant delay in processing procedures. The dwell time of each passenger agent at the service facilities were recorded. The overall dwell time of passenger agents at typical facility areas were analysed so as to demonstrate portions of utilisation in the temporal aspect. For the spatial aspect, the number of passenger agents who were dwelling within specific terminal areas can be used to estimate service rates. All outcomes demonstrated specific results by typical simulated passenger flows. They directly reflect terminal capacity. The simulation results strongly suggest that integrating discretionary activities of passengers makes the passenger flows more intuitive, observing probabilities of mental preferences by inferring advanced traits make up an approach capable of carrying out tactical route-choice decision-making. On the whole, the research studied passenger flows in airport terminals by an agent-based model, which investigated individual characteristics of passengers and their impact on psychological route-choice decisions of passengers. Finally, intuitive passenger flows in airport terminals were able to be realised in simulation.

Impairment of simulated motorcycle riding performance under low dose alcohol

Crash statistics that include the blood alcohol concentration (BAC) of vehicle operators reveal that crash involved motorcyclists are over represented at low BACs (e.g., ≤0.05%). This riding simulator study compared riding performance and hazard response under three low dose alcohol conditions (sober, 0.02% BAC, 0.05% BAC). Forty participants (20 novice, 20 experienced) completed simulated rides in urban and rural scenarios while responding to a safety-critical peripheral detection task (PDT). Results showed a significant increase in the standard deviation of lateral position in the urban scenario and PDT reaction time in the rural scenario under 0.05% BAC compared with zero alcohol. Participants were most likely to collide with an unexpected pedestrian in the urban scenario at 0.02% BAC, with novice participants at a greater relative risk than experienced riders. Novices chose to ride faster than experienced participants in the rural scenario regardless of BAC. Not all results were significant, emphasising the complex situation of the effects of low dose BAC on riding performance, which needs further research. The results of this simulator study provide some support for a legal BAC for motorcyclists below 0.05%.

Awesome foursome? The compatibility of situation awareness across drivers, riders, cyclists, and pedestrians

Collisions between distinct road users (e.g. drivers and motorcyclists) make a substantial contribution to the road trauma burden. Although evidence suggests distinct road users interpret the same road situations differently, it is not clear how road users’ situation awareness differs, nor is it clear which differences might lead to conflicts. This article presents the findings from an on-road study which examined driver, cyclist, motorcyclist and pedestrian situation awareness at intersections. The findings suggest that situation awareness at intersection is markedly different across the four road user groups studied, and that some of these differences may create conflicts between the different road users. The findings also suggest that the causes of the differences identified relate to road design and road user experience. In closing, the key role of road design and training in supporting safe interactions between distinct road users is discussed.

Characteristics of police-reported road traffic crashes in Ethiopia over a six year period

Ethiopia has one of Africa’s fastest growing non-oil producing economies and an increasing level of motorisation (AfDB, OECD, UNDP, & UNECA, 2012). This rapidly increasing mobility has created some unique road safety concerns; however there is scant published information and related commentary (United Nations Economic Commission for Africa, 2009). The objective of this paper is to quantify police-reported traffic crashes in Ethiopia and characterise the existing state of road safety. Six years (July 2005 - June 2011) of police-reported crash data were analysed, consisting of 12,140 fatal and 29,454 injury crashes on the country’s road network. The 12,140 fatal crashes involved 1,070 drivers, 5,702 passengers, and 7,770 pedestrians, totalling 14,542 fatalities, an average of 1.2 road user fatalities per crash. An important and glaring trend that emerges is that more than half of the fatalities in Ethiopia involve pedestrians. The majority of the crashes occur during daytime hours, involve males, and involve persons in the 18-50 age group—Ethiopia’s active workforce. Crashes frequently occur in mid blocks or roadways. The predominant collision between motor vehicles and pedestrians was a rollover on a road tangent section. Failing to observe the priority of pedestrians and speeding were the major causes of crashes attributed by police. Trucks and minibus taxis were involved in the majority of crashes, while automobiles (small vehicles) were less involved in crashes relative to other vehicle types, partially because small vehicles tend to be driven fewer kilometres per annum. These data illustrate and justify a high priority to identify and implement effective programs, policies, and countermeasures focused on reducing pedestrian crashes.

Effects of mobile phone distraction on drivers’ reaction times

Distraction resulting from mobile phone use whilst driving has been shown to increase the reaction times of drivers, thereby increasing the likelihood of a crash. This study compares the effects of mobile phone conversations on reaction times of drivers responding to traffic events that occur at different points in a driver’s field of view. The CARRS-Q Advanced Driving Simulator was used to test a group of young drivers on various simulated driving tasks including a traffic event that occurred within the driver’s central vision—a lead vehicle braking suddenly—and an event that occurred within the driver’s peripheral—a pedestrian entering a zebra crossing from a footpath. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), and while engaged in hands-free and handheld phone conversations. The drivers were aged between 21 to 26 years and split evenly by gender. Differences in reaction times for an event in a driver’s central vision were not statistically significant across phone conditions, probably due to a lower speed selection by the distracted drivers. In contrast, the reaction times to detect an event that originated in a distracted driver’s peripheral vision were more than 50% longer compared to the baseline condition. A further statistical analysis revealed that deterioration of reaction times to an event in the peripheral vision was greatest for distracted drivers holding a provisional licence. Many critical events originate in a driver’s periphery, including vehicles, bicyclists, and pedestrians emerging from side streets. A reduction in the ability to detect these events while distracted presents a significant safety concern that must be addressed.

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations

The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q Advanced Driving Simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver’s peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21 to 26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver’s age, license type (Provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.