Urban traffic state estimation: Fusing point and zone based data

Loop detectors are the oldest and widely used traffic data source. On urban arterials, they are mainly installed for signal control. Recently state of the art Bluetooth MAC Scanners (BMS) has significantly captured the interest of stakeholders for exploiting it for area wide traffic monitoring. Loop detectors provide flow- a fundamental traffic parameter; whereas BMS provides individual vehicle travel time between BMS stations. Hence, these two data sources complement each other, and if integrated should increase the accuracy and reliability of the traffic state estimation. This paper proposed a model that integrates loops and BMS data for seamless travel time and density estimation for urban signalised network. The proposed model is validated using both real and simulated data and the results indicate that the accuracy of the proposed model is over 90%.

Optimising offsets and bandwidths in vehicle traffic networks

Bandwidths and offsets are important components in vehicle traffic control strategies. This article proposes new methods for quantifying and selecting them. Bandwidth is the amount of green time available for vehicles to travel through adjacent intersections without the requirement to stop at the second traffic light. The offset is the difference between the starting-time of ``green'' periods at two adjacent intersections, along a given route. The core ideas in this article were developed during the 2013 Maths and Industry Study Group in Brisbane, Australia. Analytical expressions for computing bandwidth, as a function of offset, are developed. An optimisation model, for selecting offsets across an arterial, is proposed. Arterial roads were focussed upon, as bandwidth and offset have a greater impact on these types of road as opposed to a full traffic network. A generic optimisation-simulation approach is also proposed to refine an initial starting solution, according to a specified metric. A metric that reflects the number of stops, and the distance between stops, is proposed to explicitly reduce the dissatisfaction of road users, and to implicitly reduce fuel consumption and emissions. Conceptually the optimisation-simulation approach is superior as it handles real-life complexities and is a global optimisation approach. The models and equations in this article can be used in road planning and traffic control.

Residential balconies with road traffic noise : a combined source image and radiosity model

Several significant studies have been made in recent decades toward understanding road traffic noise and its effects on residential balconies. These previous studies have used a variety of techniques such as theoretical models, scale models and measurements on real balconies. The studies have considered either road traffic noise levels within the balcony space or inside an adjacent habitable room or both. Previous theoretical models have used, for example, simplified specular reflection calculations, boundary element methods (BEM), adaptations of CoRTN or the use of Sabine Theory. This paper presents an alternative theoretical model to predict the effects of road traffic noise spatially within the balcony space. The model includes a specular reflection component by calculating up to 10 orders of source images. To account for diffusion effects, a two compartment radiosity component is utilised. The first radiosity compartment is the urban street, represented as a street with building facades on either side. The second radiosity compartment is the balcony space. The model is designed to calculate the predicted road traffic noise levels within the balcony space and is capable of establishing the effect of changing street and balcony geometries. Screening attenuation algorithms are included to determine the effects of solid balcony parapets and balcony ceiling shields.

Bisphenol A degradation enhanced by air bubbles via advanced oxidation using in situ generated ferrous ions from nano zero-valent iron/palygorskite composite materials

Novel nano zero-valent iron/palygorskite composite materials prepared by evaporative and centrifuge methods are tested for the degradation of bisphenol A in an aqueous medium. A systematic study is presented which showed that nano zero-valent iron material has little effect on bisphenol A degradation. When hydrogen peroxide was added to initiate the reaction, some percentage of bisphenol A removal (∼20%) was achieved; however, with the aid of air bubbles, the percentage removal can be significantly increased to ∼99%. Compared with pristine nano zero-valent iron and commercial iron powder, nano zero-valent iron/palygorskite composite materials have much higher reactivity towards bisphenol A and these materials are superior as they have little impact on the solution pH. However, for pristine nano zero-valent iron, it is difficult to maintain the reaction system at a favourable low pH which is a key factor in maintaining high bisphenol A removal. All materials were characterized by X-ray diffraction, scanning electron microscopy, elemental analysis, transmission electron microscopy and X-ray photoelectron spectroscopy. The optimum conditions were obtained based on a series of batch experiments. This study has extended the application of nano zero-valent iron/palygorskite composites as effective materials for the removal of phenolic compounds from the environment.

Elemental composition and potential toxicity of airborne particles at some urban schools

Although both the size and chemical composition of ambient particles are important parameters in determining their toxicities, their relative contributions are unclear (Heal et al., 2012). Children are particularly at risk to the detrimental health effects that have been linked to long term exposure to airborne particles (See e.g. Ruckerl et al., 2011). However, there is currently limited understanding of the health effects in children due to long term exposure to airborne particles. Schools are locations within an urban environment where children experience significant exposure to vehicle emissions, and to date there is limited information assessing children’s exposure at school. This study is a part of a large project aimed at gaining a holistic picture of the exposure of children to traffic related pollutants. In the current paper, results from the investigation of the elemental composition of airborne particle at urban schools are presented.

Investigation of air quality at Lithgow Correctional Centre

This project was conducted at Lithgow Correctional Centre (LCC), NSW, Australia. Air quality field measurements were conducted on two occasions (23-27 May 2012, and 3-8 December 2012), just before and six months after the introduction of smoke free buildings policies (28 May 2012) at the LCC, respectively. The main aims of this project were to: (1) investigate the indoor air quality; (2) quantify the level of exposure to environmental tobacco smoke (ETS); (3) identify the main indoor particle sources; (4) distinguish between PM2.5 / particle number from ETS, as opposed to other sources; and (5) provide recommendations for improving indoor air quality and/or minimising exposure at the LCC. The measurements were conducted in Unit 5.2A, Unit 5.2B, Unit 1.1 and Unit 3.1, together with personal exposure measurements, based on the following parameters: -Indoor and outdoor particle number (PN) concentration in the size range 0.005-3 µm -Indoor and outdoor PM2.5 particle mass concentration -Indoor and outdoor VOC concentrations -Personal particle number exposure levels (in the size range 0.01-0.3 µm) -Indoor and outdoor CO and CO2 concentrations, temperature and relative humidity In order to enhance the outcomes of this project, the indoor and outdoor particle number (PN) concentrations were measured by two additional instruments (CPC 3787) which were not listed in the original proposal.

The effect of very small air gaps on small field dosimetry

The purpose of this study was to investigate the effect of very small air gaps (less than 1 mm) on the dosimetry of small photon fields used for stereotactic treatments. Measurements were performed with optically stimulated luminescent dosimeters (OSLDs) for 6 MV photons on a Varian 21iX linear accelerator with a Brainlab lMLC attachment for square field sizes down to 6 mm 9 6 mm. Monte Carlo simulations were performed using EGSnrc C++ user code cavity. It was found that the Monte Carlo model used in this study accurately simulated the OSLD measurements on the linear accelerator. For the 6 mm field size, the 0.5 mm air gap upstream to the active area of the OSLD caused a 5.3 % dose reduction relative to a Monte Carlo simulation with no air gap...

Traffic incident clearance time and arrival time prediction based on hazard models

Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

Partitioning of dioxins (PCDDs/Fs) in ambient air at urban residential locations

In this work, 17-polychlorinated dibenzo-pdioxin/furan (PCDD/Fs) isomers were measured in ambient air at four urban sites in Seoul, Korea (from February to June 2009). The concentrations of their summed values RPCDD/Fs) across all four sites ranged from 1,947 (271 WHO05 TEQ) (Jong Ro) to 2,600 (349 WHO05 TEQ) fg/m3 (Yang Jae) with a mean of 2,125 ± 317) fg/m3 (292 WHO05 TEQ fg/m3). The sum values for the two isomer groups of RPCDD and RPCDF were 527 (30 WHO05 TEQ) and 1,598 (263 WHO05 TEQ) fg/m3, respectively. The concentration profile of individual species was dominated by the 2,3,4,7,8-PeCDF isomer, which contributed approximately 36 % of the RPCDD/Fs value. The observed temporal trends in PCDD/F concentrations were characterized by relative enhancement in the winter and spring. The relative contribution of different sources, when assessed by principal component analysis, is explained by the dominance of vehicular emissions along with coal (or gas) burning as the key source of ambient PCDD/Fs in the residential areas studied.

Enabling safe autonomous driving in real-world city traffic using multiple criteria decision making

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

Agent-based modelling simulation case study : assessment of airport check-in and evacuation process by considering group travel behaviour of air passengers

Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

Noisy Bluetooth traffic data?

Traffic state estimation in an urban road network remains a challenge for traffic models and the question of how such a network performs remains a difficult one to answer for traffic operators. Lack of detailed traffic information has long restricted research in this area. The introduction of Bluetooth into the automotive world presented an alternative that has now developed to a stage where large-scale test-beds are becoming available, for traffic monitoring and model validation purposes. But how much confidence should we have in such data? This paper aims to give an overview of the usage of Bluetooth, primarily for the city-scale management of urban transport networks, and to encourage researchers and practitioners to take a more cautious look at what is currently understood as a mature technology for monitoring travellers in urban environments. We argue that the full value of this technology is yet to be realised, for the analytical accuracies peculiar to the data have still to be adequately resolved.

Ultrafine particles in cities

Ultrafine particles (UFP; diameter less than 100 nm) are ubiquitous in urban air, and an acknowledged risk to human health. Globally, the major source for urban outdoor UFP concentrations is motor traffic. Ongoing trends towards urbanisation and expansion of road traffic are anticipated to further increase population exposure to UFPs. Numerous experimental studies have characterised UFPs in individual cities, but an integrated evaluation of emissions and population exposure is still lacking. Our analysis suggest that average exposure to outdoor UFPs in Asian cities is about four-times larger than those in European cities but impacts on human health are largely unknown. This article reviews some fundamental drivers of UFP emissions and dispersion, and highlights unresolved challenges, as well as recommendations to ensure sustainable urban development whilst minimising any possible adverse health impacts.