Derivation of motor vehicle tailpipe particle emission factors suitable for modelling urban fleet emissions and air quality assessments

Background, aim, and scope Urban motor vehicle fleets are a major source of particulate matter pollution, especially of ultrafine particles (diameters < 0.1 µm), and exposure to particulate matter has known serious health effects. A considerable body of literature is available on vehicle particle emission factors derived using a wide range of different measurement methods for different particle sizes, conducted in different parts of the world. Therefore the choice as to which are the most suitable particle emission factors to use in transport modelling and health impact assessments presented as a very difficult task. The aim of this study was to derive a comprehensive set of tailpipe particle emission factors for different vehicle and road type combinations, covering the full size range of particles emitted, which are suitable for modelling urban fleet emissions. Materials and methods A large body of data available in the international literature on particle emission factors for motor vehicles derived from measurement studies was compiled and subjected to advanced statistical analysis, to determine the most suitable emission factors to use in modelling urban fleet emissions. Results This analysis resulted in the development of five statistical models which explained 86%, 93%, 87%, 65% and 47% of the variation in published emission factors for particle number, particle volume, PM1, PM2.5 and PM10 respectively. A sixth model for total particle mass was proposed but no significant explanatory variables were identified in the analysis. From the outputs of these statistical models, the most suitable particle emission factors were selected. This selection was based on examination of the statistical robustness of the statistical model outputs, including consideration of conservative average particle emission factors with the lowest standard errors, narrowest 95% confidence intervals and largest sample sizes, and the explanatory model variables, which were Vehicle Type (all particle metrics), Instrumentation (particle number and PM2.5), Road Type (PM10) and Size Range Measured and Speed Limit on the Road (particle volume). Discussion A multiplicity of factors need to be considered in determining emission factors that are suitable for modelling motor vehicle emissions, and this study derived a set of average emission factors suitable for quantifying motor vehicle tailpipe particle emissions in developed countries. Conclusions The comprehensive set of tailpipe particle emission factors presented in this study for different vehicle and road type combinations enable the full size range of particles generated by fleets to be quantified, including ultrafine particles (measured in terms of particle number). These emission factors have particular application for regions which may have a lack of funding to undertake measurements, or insufficient measurement data upon which to derive emission factors for their region. Recommendations and perspectives In urban areas motor vehicles continue to be a major source of particulate matter pollution and of ultrafine particles. It is critical that in order to manage this major pollution source methods are available to quantify the full size range of particles emitted for traffic modelling and health impact assessments.

Freeway traffic estimation in Beijing based on particle filter

Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.

‘You’re a bad driver but I just made a mistake’ : attribution differences between the ‘victims’ and ‘perpetrators’ of scenario-based aggressive driving incidents

Driver aggression is an increasing concern for motorists, with some research suggesting that drivers who behave aggressively perceive their actions as justified by the poor driving of others. Thus attributions may play an important role in understanding driver aggression. A convenience sample of 193 drivers (aged 17-36) randomly assigned to two separate roles (‘perpetrators’ and ‘victims’) responded to eight scenarios of driver aggression. Drivers also completed the Aggression Questionnaire and Driving Anger Scale. Consistent with the actor-observer bias, ‘victims’ (or recipients) in this study were significantly more likely than ‘perpetrators’ (or instigators) to endorse inadequacies in the instigator’s driving skills as the cause of driver aggression. Instigators were significantly more likely attribute the depicted behaviours to external but temporary causes (lapses in judgement or errors) rather than stable causes. This suggests that instigators recognised drivers as responsible for driving aggressively but downplayed this somewhat in comparison to ‘victims’/recipients. Recipients and instigators agreed that the behaviours were examples of aggressive driving but instigators appeared to focus on the degree of intentionality of the driver in making their assessments while recipients appeared to focus on the safety implications. Contrary to expectations, instigators gave mean ratings of the emotional impact of driving aggression on recipients that were higher in all cases than the mean ratings given by the recipients. Drivers appear to perceive aggressive behaviours as modifiable, with the implication that interventions could appeal to drivers’ sense of self-efficacy to suggest strategies for overcoming plausible and modifiable attributions (e.g. lapses in judgement; errors) underpinning behaviours perceived as aggressive.

The prevalence and characteristics of self-reported dangerous driving behaviours among a young cohort

Background: Young motorists engaging in anti-social and often dangerous driving manoeuvres (which is often referred to as “hooning” within Australia) is an increasing road safety problem. While anecdotal evidence suggests that such behaviour is positively linked with crash involvement, researchers have yet to examine whether younger drivers who deliberately break road rules and drive in an erratic manner (usually with peers) are in fact over represented in crash statistics. This paper outlines research that aimed to identify the characteristics of individuals most likely to engaging in hooning behaviours, as well as examine the frequency of such driving behaviours and if such activity is linked with self-reported crash involvement.---------- Methods: A total of 717 young drivers in Queensland voluntarily completed a questionnaire to investigate their driving behaviour and crash history.---------- Results: Quantitative analysis of the data revealed that almost half the sample reported engaging in some form of “hooning” behaviour at least once in their lifetime, although only 4% indicated heavy participation in the behaviour e.g., >50 times. Street racing was the most common activity reported by participants followed by “drifting” and then “burnouts”. Logistic regression analysis indicated that being younger and a male was predictive of reporting such anti-social driving behaviours, and importantly, a trend was identified between such behaviour and self-reported crash involvement.---------- Conclusions: This research provides preliminary evidence that younger male drivers are more likely to engage in dangerous driving behaviours, which ultimately may prove to increase their overall risk of becoming involved in a crash. This paper will further outline the study findings in regards to current enforcement efforts to deter such driving activity as well as provide direction for future research efforts in this area.---------- Research highlights: ► The self-reported driving behaviours of 717 younger Queensland drivers were examined to investigate the relationship between deliberately breaking road rules and self-reported crash involvement. ► Younger male drivers were most likely to engage in such aberrant driving behaviours and a trend was identified between such behaviour and self-reported crash involvement.

Numerical evaluation of pollutant dispersion at a toll plaza based on system dynamics and Computational Fluid Dynamics models

The health of tollbooth workers is seriously threatened by long-term exposure to polluted air from vehicle exhausts. Using traffic data collected at a toll plaza, vehicle movements were simulated by a system dynamics model with different traffic volumes and toll collection procedures. This allowed the average travel time of vehicles to be calculated. A three-dimension Computational Fluid Dynamics (CFD) model was used with a k–ε turbulence model to simulate pollutant dispersion at the toll plaza for different traffic volumes and toll collection procedures. It was shown that pollutant concentration around tollbooths increases as traffic volume increases. Whether traffic volume is low or high (1500 vehicles/h or 2500 vehicles/h), pollutant concentration decreases if electronic toll collection (ETC) is adopted. In addition, pollutant concentration around tollbooths decreases as the proportion of ETC-equipped vehicles increases. However, if the proportion of ETC-equipped vehicles is very low and the traffic volume is not heavy, then pollutant concentration increases as the number of ETC lanes increases.

Queensland Government’s people’s question time : the challenges and opportunities of population growth in Queensland

As AITPM National President, I was invited by Queensland’s Premier, Hon. Anna Bligh MP, as an audience guest to People’s Question Time on Wednesday 24 March 2010, which focused on ‘The Challenges and Opportunities of Population Growth in Queensland’. On the panel were: Premier and Minister for the Arts, Anna Bligh; Minister for Climate Change and Sustainability, Kate Jones; Minister for Infrastructure and Planning, Stirling Hinchliffe; Michael Rayner – Growth Management Summit Advisory Panel, Principal Director, Cox Rayner Architects; and Greg Hallam – Executive Director, Local Government Association of Queensland. The moderator for this session was Law Academic Erin O’Brien, of Queensland University of Technology.

Calibration and operational analysis of variable speed limits for high flow condition

Variable Speed Limits (VSL) is a control tool of Intelligent Transportation Systems (ITS) which can enhance traffic safety and which has the potential to contribute to traffic efficiency. This study presents the results of a calibration and operational analysis of a candidate VSL algorithm for high flow conditions on an urban motorway of Queensland, Australia. The analysis was done using a framework consisting of a microscopic simulation model combined with runtime API and a proposed efficiency index. The operational analysis includes impacts on speed-flow curve, travel time, speed deviation, fuel consumption and emission.

Age and gender comparisons of driving while sleepy : behaviours and risk perceptions

To assist road safety professionals in developing effective strategies to combat the risk associated with driving while fatigued, a survey was administered to 1000 Australian drivers. Participants reported their past behaviours in regards to driving while sleepy and their perceptions of risk associated with driving fatigued as compared to speeding and driving under the influence of alcohol. Although participants appeared to be aware of the substantial risk associated with driving while sleepy, many drivers reported that they frequently drive when sleepy. Age and gender comparisons, revealed that risk taking behaviour in regards to driving while sleepy is occurring across all age groups and in both male and female drivers. Overall young to middle age drivers and male drivers reported the highest frequency of driving while sleepy and reported the lowest perceived personal risk in regards to driving while sleepy.

Year 7 students’ approaches to understanding and solving NAPLAN numeracy problems

This study investigated how the interpretation of mathematical problems by Year 7 students impacted on their ability to demonstrate what they can do in NAPLAN numeracy testing. In the study, mathematics is viewed as a culturally and socially determined system of signs and signifiers that establish the meaning, origins and importance of mathematics. The study hypothesises that students are unable to succeed in NAPLAN numeracy tests because they cannot interpret the questions, even though they may be able to perform the necessary calculations. To investigate this, the study applied contemporary theories of literacy to the context of mathematical problem solving. A case study design with multiple methods was used. The study used a correlation design to explore the connections between NAPLAN literacy and numeracy outcomes of 198 Year 7 students in a Queensland school. Additionally, qualitative methods provided a rich description of the effect of the various forms of NAPLAN numeracy questions on the success of ten Year 7 students in the same school. The study argues that there is a quantitative link between reading and numeracy. It illustrates that interpretation (literacy) errors are the most common error type in the selected NAPLAN questions, made by students of all abilities. In contrast, conceptual (mathematical) errors are less frequent amongst more capable students. This has important implications in preparing students for NAPLAN numeracy tests. The study concluded by recommending that increased focus on the literacies of mathematics would be effective in improving NAPLAN results.

Peer passenger identity and passenger pressure on young drivers' speeding intentions

Young drivers, aged 17 to 24 years, have the highest fatality rate in Australia. It is believed that part of this risk is due to pressure from peer passengers to engage in speeding; which may be active (i.e., verbal encouragement) or passive (i.e., perceived pressure on the part of the driver). The Theory of Planned Behaviour (TPB) was used to investigate this impact of peer passengers on young drivers, particularly the influence of the type of peer pressure and a driver’s level of identification with their passengers. A scenario-based questionnaire was constructed, informed by focus groups and pilot studies, and distributed to university students (N = 398). The questionnaire measured participants’ intentions and the TPB constructs, including two components of perceived behaviour control, within a baseline scenario as well as an experimental scenario in which the variables of type of pressure and identification were manipulated. Consistent with the hypotheses, the study found that attitudes and self-efficacy significantly predicted intentions over and above the variance explained by the sociodemographic variables of age, gender, self-esteem, sensation seeking, as well as past behaviour and exposure. Across the scenarios, attitudes explained between 4.3% and 14.5%, while self-efficacy to refrain from speeding explained between 4.9% and 17.1%, of the unique variance in intentions to speed. However, contrary to expectations, intentions to speed were found to be higher in the “no passenger” than “passenger present” conditions, although this finding is not completely inconsistent with recent literature. A high level of identification with passengers led to higher intentions to speed than low identification as expected, but, inconsistent with expectations, different types of pressure (i.e., active versus passive) did not influence intentions to speed.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Considering weather in simulation traffic

The impact of weather on traffic and its behavior is not well studied in literature primarily due to lack of integrated traffic and weather data. Weather can significant effect the traffic and traffic management measures developed for fine weather might not be optimal for adverse weather. Simulation is an efficient tool for analyzing traffic management measures even before their actual implementation. Therefore, in order to develop and test traffic management measures for adverse weather condition we need to first analyze the effect of weather on fundamental traffic parameters and thereafter, calibrate the simulation model parameters in order to simulate the traffic under adverse weather conditions. In this paper we first, analyses the impact of weather on motorway traffic flow and drivers’ behaviour with traffic data from Swiss motorways and weather data from MeteoSuisse. Thereafter, we develop methodology to calibrate a microscopic simulation model with the aim to utilize the simulation model for simulating traffic under adverse weather conditions. Here, study is performed using AIMSUN, a microscopic traffic simulator.

Study on road traffic noise prediction model taking into account the citywide network

For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

An estimation of crash risks using a log-linear model and the induced exposure technique

Prevention and safety promotion programmes. Traditionally, in-depth investigations of crash risks are conducted using exposure controlled study or case-control methodology. However, these studies need either observational data for control cases or exogenous exposure data like vehicle-kilometres travel, entry flow or product of conflicting flow for a particular traffic location, or a traffic site. These data are not readily available and often require extensive data collection effort on a system-wide basis. Aim: The objective of this research is to propose an alternative methodology to investigate crash risks of a road user group in different circumstances using readily available traffic police crash data. Methods: This study employs a combination of a log-linear model and the quasi-induced exposure technique to estimate crash risks of a road user group. While the log-linear model reveals the significant interactions and thus the prevalence of crashes of a road user group under various sets of traffic, environmental and roadway factors, the quasi-induced exposure technique estimates relative exposure of that road user in the same set of explanatory variables. Therefore, the combination of these two techniques provides relative measures of crash risks under various influences of roadway, environmental and traffic conditions. The proposed methodology has been illustrated using Brisbane motorcycle crash data of five years. Results: Interpretations of results on different combination of interactive factors show that the poor conspicuity of motorcycles is a predominant cause of motorcycle crashes. Inability of other drivers to correctly judge the speed and distance of an oncoming motorcyclist is also evident in right-of-way violation motorcycle crashes at intersections. Discussion and Conclusions: The combination of a log-linear model and the induced exposure technique is a promising methodology and can be applied to better estimate crash risks of other road users. This study also highlights the importance of considering interaction effects to better understand hazardous situations. A further study on the comparison between the proposed methodology and case-control method would be useful.

Fatigue crack growth and fatigue life evaluation for welded steel bridge members with initial crack

Initial crack widely exists in the welded members of steel bridge induced by the welding procedure or by the fatigue damage crack initiation. The behavior of crack growth with a view to fatigue damage accumulation on the tip of cracks is discussed. Fatigue life of welded components with initial crack in bridges under traffic loading is investigated. Based on existing fatigue experiment results of welded members with initial crack and the fatigue experiment results of welded bridge members under constant stress cycles, the crack would keep semi-elliptical shape with variable ratio of a/c during the crack propagation. Based on the concept of continuum damage accumulated on the tip of fatigue cracks,the fatigue damage law suitable for steel bridge members under traffic loading is modified to consider the crack growth.The virtual crack growth method and the semi-elliptical crack shape assumption are proposed in this paper to deduce a new model of fatigue crack growth rate for welded bridge members under traffic loading. And the calculated method of the stress intensity factor necessary for evaluation of the fatigue life of welded bridge members with cracks is discussed.The proposed fatigue crack growth model is then applied to calculate the crack growth and the fatigue life of existing welded members with fatigue experimental results. The fatigue crack propagation computation results show that the ratio of crack depth to the half crack surface length a/c is variable during crack propagation process and the stress cycle increases with the increase of a0/c0 with certain a0/t0 .The calculated and measured fatigue lives are generally in good agreement,at some initial conditions of cracking, for welded members widely used in steel bridges.