Exploring association between perceived importance of travel/traffic information and travel behaviour in natural disasters : a case study of the 2011 Brisbane floods

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.

Influence of traffic characteristics on polycyclic aromatic hydrocarbon build-up on urban road surfaces

Traffic is one of the prominent sources of polycyclic aromatic hydrocarbons (PAHs) and road surfaces are the most critical platform for stormwater pollution. Build-up of pollutants on road surfaces was the focus of this research study. The study found that PAHs build-up on road surfaces primarily originate from traffic activities, specifically gasoline powered vehicles. Other sources such as diesel vehicles, industrial oil combustion and incineration were also found to contribute to the PAH build-up. Additionally, the study explored the linkages between concentrations of PAHs and traffic characteristics such as traffic volume, vehicle mix and traffic flow. While traffic congestion was found to be positively correlated with 6- ring and 5- ring PAHs in road build-up, it was negatively correlated with 3-ring and 4 ring PAHs. The absence of positive correlation between 3-ring and 4-ring PAHs and traffic parameters is attributed to the propensity of these relatively volatile PAHs to undergo re-suspension and evaporation. The outcomes of this study are expected to contribute effective transport and land use planning for the prevention of PAH pollution in the urban environment.

Are we there yet? Australian road safety targets and road traffic crash fatalities

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.

Are road traffic crash fatality rates converging among OECD countries?

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.

Ultrafine Particles from Traffic Emissions and Children’s Health (UPTECH) in Brisbane, Queensland (Australia): Study design and implementation

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.

Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts

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.