276 resultados para Traffic congestion
Resumo:
A sound understanding of travellers’ behavioural changes and adaptation when facing a natural disaster is a key factor in efficiently and effectively managing transport networks at such times. This study specifically investigates the importance of travel/traffic information and its impact on travel behaviour during natural disasters. Using the 2011 Brisbane flood as a case study, survey respondents’ perceptions of the importance of travel/traffic information before, during, and after the flood were modelled using random-effects ordered logit. A hysteresis phenomenon was observed: respondents’ perceptions of the importance of travel/traffic information increased during the flood, and although its perceived importance decreased after the flood, it did not return to the pre-flood level. Results also reveal that socio-demographic features (such as gender and age) have a significant impact on respondents’ perceptions of the importance of travel/traffic information. The roles of travel time and safety in a respondent’s trip planning are also significantly correlated to their perception of the importance of this information. The analysis further shows that during the flood, respondents generally thought that travel/traffic information was important, and adjusted their travel plans according to information received. When controlling for other factors, the estimated odds of changing routes and cancelling trips for a respondent who thought that travel/traffic information was important, are respectively about three times and seven times the estimated odds for a respondent who thought that travel/traffic information was not important. In contrast, after the flood, the influence of travel/traffic information on respondents’ travel behaviour diminishes. Finally, the analysis shows no evidence of the influence of travel/traffic information’s on respondents’ travel mode; this indicates that inducing travel mode change is a challenging task.
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Background Road safety targets are widely used and provide a basis for evaluating progress in road safety outcomes against a quantified goal. In Australia, a reduction in fatalities from road traffic crashes (RTCs) is a public policy objective: a national target of no more than 5.6 fatalities per 100,000 population by 2010 was set in 2001. The purpose of this paper is to examine the progress Australia and its states and territories have made in reducing RTC fatalities, and to estimate when the 2010 target may be reached by the jurisdictions. Methods Following a descriptive analysis, univariate time-series models estimate past trends in fatality rates over recent decades. Data for differing time periods are analysed and different trend specifications estimated. Preferred models were selected on the basis of statistical criteria and the period covered by the data. The results of preferred regressions are used to determine out-of-sample forecasts of when the national target may be attained by the jurisdictions. Though there are limitations with the time series approach used, inadequate data precluded the estimation of a full causal/structural model. Results Statistically significant reductions in fatality rates since 1971 were found for all jurisdictions with the national rate decreasing on average, 3% per year since 1992. However the gains have varied across time and space, with percent changes in fatality rates ranging from an 8% increase in New South Wales 1972-1981 to a 46% decrease in Queensland 1982-1991. Based on an estimate of past trends, it is possible that the target set for 2010 may not be reached nationally, until 2016. Unsurprisingly, the analysis indicated a range of outcomes for the respective state/territory jurisdictions though these results should be interpreted with caution due to different assumptions and length of data. Conclusions Results indicate that while Australia has been successful over recent decades in reducing RTC mortality, an important gap between aspirations and achievements remains. Moreover, unless there are fairly radical ("trend-breaking") changes in the factors that affect the incidence of RTC fatalities, deaths from RTCs are likely to remain above the national target in some areas of Australia, for years to come.
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This article examines the trends of road traffic crash (RTC) fatality rates in OECD countries over the past four decades. Based on recent developments in the economic growth literature we propose and test the hypothesis that RTC fatality rates initially increase with economic development, peak, and then gradually decrease. The theory predicts that, as a result, the RTC fatality rates of different countries will tend to converge over time. Our results for the period 1961–2007 reveal no evidence of the convergence of RTC fatality rates across the OECD as a whole for that time period. Nevertheless, there is evidence of convergence among sub-groups of countries. This evidence may assist policymakers as an additional way of benchmarking their country's performance against that of its peers and to identify the next-closest peer in country sub-groups with superior road safety performance.
Resumo:
Ultrafine particles are particles that are less than 0.1 micrometres (µm) in diameter. Due to their very small size they can penetrate deep into the lungs, and potentially cause more damage than larger particles. The Ultrafine Particles from Traffic Emissions and Children’s Health (UPTECH) study is the first Australian epidemiological study to assess the health effects of ultrafine particles on children’s health in general and peripheral airways in particular. The study is being conducted in Brisbane, Australia. Continuous indoor and outdoor air pollution monitoring was conducted within each of the twenty five participating school campuses to measure particulate matter, including in the ultrafine size range, and gases. Respiratory health effects were evaluated by conducting the following tests on participating children at each school: spirometry, forced oscillation technique (FOT) and multiple breath nitrogen washout test (MBNW) (to assess airway function), fraction of exhaled nitric oxide (FeNO, to assess airway inflammation), blood cotinine levels (to assess exposure to second-hand tobacco smoke), and serum C-reactive protein (CRP) levels (to measure systemic inflammation). A pilot study was conducted prior to commencing the main study to assess the feasibility and reliably of measurement of some of the clinical tests that have been proposed for the main study. Air pollutant exposure measurements were not included in the pilot study.
Resumo:
In transport networks, Origin-Destination matrices (ODM) are classically estimated from road traffic counts whereas recent technologies grant also access to sample car trajectories. One example is the deployment in cities of Bluetooth scanners that measure the trajectories of Bluetooth equipped cars. Exploiting such sample trajectory information, the classical ODM estimation problem is here extended into a link-dependent ODM (LODM) one. This much larger size estimation problem is formulated here in a variational form as an inverse problem. We develop a convex optimization resolution algorithm that incorporates network constraints. We study the result of the proposed algorithm on simulated network traffic.
Resumo:
The development of methods for real-time crash prediction as a function of current or recent traffic and roadway conditions is gaining increasing attention in the literature. Numerous studies have modeled the relationships between traffic characteristics and crash occurrence, and significant progress has been made. Given the accumulated evidence on this topic and the lack of an articulate summary of research status, challenges, and opportunities, there is an urgent need to scientifically review these studies and to synthesize the existing state-of-the-art knowledge. This paper addresses this need by undertaking a systematic literature review to identify current knowledge, challenges, and opportunities, and then conducts a meta-analysis of existing studies to provide a summary impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to assess quality, publication bias, and outlier bias of the various studies; and the time intervals used to measure traffic characteristics were also considered. As a result of this comprehensive and systematic review, issues in study designs, traffic and crash data, and model development and validation are discussed. Outcomes of this study are intended to provide researchers focused on real-time crash prediction with greater insight into the modeling of this important but extremely challenging safety issue.
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In response to the Travelsafe Committee Report No. 51 – report on the inquiry into Automatic Plate Recognition Technology – it was recommended that the Queensland Police Service continue to trial the deployment of ANPR technology for traffic enforcement work and to evaluate the road safety impacts and operational effectiveness of the technology. As such, the purpose of this report is to provide an independent evaluation of a trial of ANPR that was conducted by a project team within the State Traffic Support Branch of the Queensland Police Service (QPS) and provide recommendations as to the applicability and usability of the technology for use throughout Queensland...
Resumo:
This study examines the impact of incentives on commuters' travel behavior based upon a questionnaire survey conducted with respect to the Beijing Subway System. Overall, we find that offering incentives to commuters, particularly fast food restaurant-related services and reduced ticket fares, has a positive influence on avoiding the morning rush hour. Furthermore, by using an interaction analysis, we discover that a flexible work schedule has an impact on commuters' behavior and the efficiency of the subway system. Finally, we recommend two possible policies to maximize the utility of the subway system and to reduce congestion at the peak of morning service: (1) a set of incentives that includes free wireless internet service with a coupon for breakfast and a discount on ticket fares before the morning peak, and; (2) the introduction of a flexible work schedule.
Resumo:
Injury as a result of road traffic crashes is one of the most significant public health problems in developing countries. It intersects with disability as a development issue because a substantial proportion of people injured in road traffic crashes experience disability, both short term and long term. While there have been significant steps towards better management of road safety globally, especially in developing countries, the implications for road safety policy and practice of disability due road traffic crashes is not fully appreciated. In particular, qualitative information on the lived experience people with a long term disability as a result of a road traffic crash can inform better road safety policy and practice, as demonstrated in a case study from Thailand. The benefits of better policies and practices are likely to accrue to a wide range of road users, and to contribute to the achievement of sustainable development.
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This study examines the context of coordinated responses, triggers for coordinated responses, and preference for or choice of coordinating strategies in road traffic injury prevention at a local level in some OECD countries. This aim is achieved through a mixed-methodology. In this respect, 22 semi-structured interviews were conducted with road traffic injury prevention experts from five OECD countries. In addition, 31 professional road traffic injury prevention stakeholders from seven OECD nations completed a self-administered, online survey. It found that there was resource limitation and inter-dependence across actors within the context of road traffic injury prevention at a local level. Furthermore, this study unveiled the realization of resource-dependency as a trigger for coordinated responses at a local level. Moreover, the present examination has revealed two coordinating strategies favored by experts in road traffic injury prevention – i.e. self-organizing community groups, which are deemed to have a platform to deliver programs within communities, and the funding of community groups to forge partnerships. However, the present study did not appear to endorse other strategies such as the formalization of coordinated responses or a legal mandate to coordinate responses. In essence, this study appears to suggest a need to manage coordinated responses from an adaptive perspective with interactions across road traffic injury prevention programs being forged on a mutual understanding of inter-dependency arising out of resource scarcity. In fact, the role of legislation and top-down national models in local level management of coordinated responses is likely to be one of identifying opportunities to interact with self-organized community groups and fund partnership-based road traffic injury prevention events.
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Despite the extent of works done on modelling port water collisions, not much research effort has been devoted to modelling collisions at port anchorages. This paper aims to fill this important gap in literature by applying the Navigation Traffic Conflict Technique (NTCT) for measuring the collision potentials in anchorages and for examining the factors contributing to collisions. Grounding on the principles of the NTCT, a collision potential measurement model and a collision potential prediction model were developed. These models were illustrated by using vessel movement data of the anchorages in Singapore port waters. Results showed that the measured collision potentials are in close agreement with those perceived by harbour pilots. Higher collision potentials were found in anchorages attached to shoreline and international fairways, but not at those attached to confined water. Higher operating speeds, larger numbers of isolated danger marks and day conditions were associated with reduction in the collision potentials.
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In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.
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Origin-Destination matrices (ODM) estimation can benefits of the availability of sample trajectories which can be measured thanks to recent technologies. This paper focus on the case of transport networks where traffic counts are measured by magnetic loops and sample trajectories available. An example of such network is the city of Brisbane, where Bluetooth detectors are now operating. This additional data source is used to extend the classical ODM estimation to a link-specific ODM (LODM) one using a convex optimisation resolution that incorporates networks constraints as well. The proposed algorithm is assessed on a simulated network.
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This paper proposes an analytical Incident Traffic Management framework for freeway incident modeling and traffic re-routing. The proposed framework incorporates an econometric incident duration model and a traffic re-routing optimization module. The incident duration model is used to estimate the expected duration of the incident and thus determine the planning horizon for the re-routing module. The re-routing module is a CTM-based Single Destination System Optimal Dynamic Traffic Assignment model that generates optimal real-time strategies of re-routing freeway traffic to its adjacent arterial network during incidents. The proposed framework has been applied to a case study network including a freeway and its adjacent arterial network in South East Queensland, Australia. The results from different scenarios of freeway demand and incident blockage extent have been analyzed and advantages of the proposed framework are demonstrated.