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This paper presents an analysis of how the particular categories of children and youth are used within the instructional work of learning to drive. Using Membership Categorisation Analysis (MCA) and multimodal Conversation Analysis (CA) of a collection of cases drawn from 85 video-recorded driving lessons, we demonstrate how the participants treat children and youth as a category of traffic users whose main category predicate appears to be their expected unpredictability and carelessness, placing particularly high demands on drivers' awareness and caution. This is evident in in-event and post-event interactions about traffic encounters with children and youth, as well as in traffic contexts where they have not (yet) been spotted but their sudden appearance is anticipated. The results suggest that the institutional constructions of children and youth as a potential source of trouble prepare trainee drivers for unforeseen events and contingencies and shape their social stock of knowledge as future motorists. [ABSTRACT FROM AUTHOR]

The growth of smart cities is fueled by the vast rise in wireless smart gadgets and uninterrupted connectivity. WiFi is the dominant wireless technology, enabling Internet-of-Things (IoT) connectivity in smart cities due to its ubiquitous access points and low deployment cost. However, smart city applications offer a wide range of services with different quality-of-service (QoS) demands. This paper addresses packet delivery latency as one of the QoS metrics affecting many time-sensitive smart city services. Thus, the paper proposes employing software-defined networking (SDN) to control the traffic load of WiFi access points (APs), preserving its symmetry in a city-wide coverage of WiFi-connected IoT gateways or fog nodes. These gateways receive data packets from smart city/IoT devices via wireless links and forward them over a city-deployed WiFi network to their management entities or servers. Three SDN-based algorithms are devised to reduce the gateways' packet-forwarding delay and keep a symmetric traffic load at the WiFi network APs. The algorithms are developed and tested using a real hardware setup constituting WiFi devices without additional requirements on the IoT gateways (WiFi clients) or the APs, such as support for a specific roaming protocol or bandwidth-consuming signaling such as sending probe packets. Extensive hardware experimentation shows that the SDN controller, via the proposed algorithms, can effectively reduce the packet forwarding latency of IoT gateways by carefully selecting the IoT gateway with the highest packet latency and seamlessly handing it over to the least-loaded covering AP. [ABSTRACT FROM AUTHOR]

This paper develops boundary control for freeway traffic with a downstream bottleneck. Traffic on a freeway segment with capacity drop at outlet of the segment is a common phenomenon that leads to traffic bottleneck problem. The capacity drop can be caused by lane-drop, hills, tunnel, bridge, or curvature on the road. If incoming traffic flow remains unchanged, traffic congestion forms upstream of the bottleneck since the upstream traffic demand exceeds its capacity. Therefore, it is important to regulate the incoming traffic flow of the segment to avoid overloading the bottleneck area. Traffic densities on the freeway segment are described with the Lighthill-Whitham-Richards (LWR) macroscopic partial differential equation (PDE) model. The incoming flow at the inlet of the freeway segment is controlled so that the optimal density that maximizes the outgoing flow is reached and the traffic congestion upstream of the bottleneck is mitigated. The density and traffic flow relation at the bottleneck area, usually described with fundamental diagram, is considered to be unknown. We tackle this problem using extremum seeking (ES) control with delay compensation for the LWR PDE. ES control, a nonmodel-based approach for real-time optimization, is adopted to find the optimal density for the unknown fundamental diagram. A predictor feedback control design is proposed to compensate the delay effect of traffic dynamics in the freeway segment. In the end, simulation results are obtained to validate a desired performance of the controller on the nonlinear LWR model with an unknown fundamental diagram. [ABSTRACT FROM AUTHOR]

Over the last few years, energy optimization in wireless sensor networks (WSNs) has drawn the attention of both the research community and actual users. Sensor nodes are powered by attached batteries that are considered as a critical aspect of sensor nodes design. Besides, the constraint of the limited battery capacity is associated with the concern on how to reduce the energy consumption of nodes to extend the network lifetime. In this context, the purpose of this study is to implement an adaptive medium access control (MAC) for energy saving and traffic control enhancement. This program was designed to arrange nodes into two priority groups according to their traffic rate and data transmission packet delay. This fuzzy algorithm depends on their queue length where it is implemented into the carrier sense multiple access with collision avoidance (CSMA/CA) algorithm. However, other types of nodes should send their data during the contention-free period with a GTS reallocation scheme. Those nodes are classified as low priority access to the medium, and their data transmission is scheduled using time division multiple access methods. Moreover, this proposed scheme dynamically adjusts the contention access period length to ensure that nodes can complete their data transmission during the same super-frame. Simulation results are done using the network simulator tool (NS-2), and it has improved efficiency regarding the IEEE-802.15.4 standard. [ABSTRACT FROM AUTHOR]

Introduction: Noise pollution unlike any other form of pollution, which is often visible to us, is invisible and hence less noticeable. Still, the harmful effects are very real, including ear impairment. While sound occurs due to changes in air pressure that causes our inner ears to vibrate and produces the auditory sensations we interpret as sound, we call sounds that are bothersome or undesired as “noise.” When there is a lot of consistent noise that causes negative emotional and physical effects in humans and animals, it is referred to as noise pollution. Some common examples of noise pollution are construction sites, traffic, industrial work, big events, festivals, railway, and airport traffic. Noise pollution has shown to cause stress, cardiovascular disease, sleep disturbance, and cognitive impairment, making it unpleasant and dangerous. Recent research shows that noise pollution disrupts and damages the ecosystem and the plants and animals that live in it, which, in turn, affects our health drastically. Materials and Methods: Questionnaire was prepared and survey was conducted among college students about noise pollution and data were collected. The survey was prepared on Survey Planet and administered to 60 participants about the risk factors of noise pollution. Results: Students have answered that vehicles are the most common cause of noise pollution, that is, traffic. This causes distraction and headache. It was observed that many students suffer from insomnia due to the noise pollution outdoors, and an increase in the traffic flow has also been observed in their area. The effects of noise pollution directly affect the environment and the beings, making it unpleasant ambience to live under and also cause several health issues. Conclusion: Awareness was created among the college students about the effects and risks of noise pollution. Most of the students are well aware of the traffic rules and regulation and the causes of noise pollution too. They intend to spread the awareness by doing their part to reduce it, starting from their households. [ABSTRACT FROM AUTHOR]

Abstract There is evidence that local traffic density and living near major roads can adversely affect health outcomes. We aimed to assess the relationship between local road length, proximity to primary highways, and cause-specific mortality in the 1991 Canadian Census Health and Environment Cohort (CanCHEC). In this long-term study of 2.6 million people, based on completion of the long-form census in 1991 and followed until 2011, we used annual residential addresses to determine the total length of local roads within 200 m of postal code representative points and the postal code's distance to primary highways. The association between exposure to traffic and cause-specific non-accidental mortality was estimated using Cox proportional hazards models, adjusting for individual covariates and contextual factors, including census division-level proportion in high school, the percentage of recent immigrants, and neighborhood income. We performed sensitivity analyses, including adjustment for exposure to PM 2.5 , NO 2 , or O 3 , restricting to subjects in core urban areas, and spatial variation by climatic zone. The hazard ratio (HR) for all non-accidental mortality associated with an interquartile increase in length of local roads was 1.05 (95% CI 1.04, 1.05), while for an interquartile range increase in proximity to primary highways, the HR was 1.03 (95% CI 1.02, 1.04). HRs by traffic quartile increased with increasing lengths of local roads, as well as with closer proximity to primary highways, for all mortality causes. The associations were stronger within subjects' resident in urban core areas, attenuated by adjustment for PM 2.5 , and HRs showed limited spatial variation by climatic zone. In the CanCHEC cohort, exposure to higher road density and proximity to major traffic roads was associated with increased mortality risk from cerebrovascular and cardiovascular disease, ischemic heart disease, COPD, respiratory disease, and lung cancer, with unclear results for diabetes. Highlights • The association between exposure to traffic and mortality was estimated using Cox proportional hazards models. • Hazard ratios (HRs) for mortality related to length of local roads and proximity to primary highways were calculated. • HRs by traffic quartile increased with greater lengths of local roads, and with closer proximity to main highways. • The associations were stronger within subjects' resident in urban core areas, attenuated by adjustment for PM 2.5. • HRs showed limited spatial variation by climatic zone. [ABSTRACT FROM AUTHOR]

Highlights • We calculated the elasticity and causality of road fatalities with its determinants. • We used panel data of 27 upper middle income countries from Asia, Europe and America. • We employed 4 panel unit root tests, Kao co-integration test, VECM and GMM. • Long-run causality exists for road fatalities, rainfall, and population density. • Road fatalities decreases due to rise in health expenditure and population density. Abstract This study aims to compare the causality and elasticity of road traffic fatalities (RTF) with their determinants for upper middle income countries from three continents by using annual data from 1994 to 2016. Vector Error Correction Model revealed the long run causality of RTF (Asia, Europe, America), GDP (Asia), rainfall (Europe), and population density (Europe, America). Two-way short-run causality was established in three panels of UMICs between RTF and rainfall (Asia), RTF and GDP (Europe, America), and RTF and population density (America). Short-run uni-directional causal association was also observed from RTF to GDP (Asia), RTF to rainfall (Europe, America), RTF to population density (Asia, Europe), and health expenditures to RTF (Europe). A significant fall in RTF was observed due to 1% rise in the share of health expenditures in GDP in UMICs from Asia (0.267%), Europe (0.064%), and America (0.549%). The significant rise in RTF was0.180%, 0.241%, and 0.702%due to 1%increase in per capita GDP in Asia, Europe, and America. The road safety is reduced due to rainfall because the rise in RTF was 0.082%and 0.260%for 1% rise in the rainfall in Asia and America, respectively. The impact of population density was beneficial for the road safety because the decrease in RTF was 0.246%, 0.234%, and 0.977% for 1% rise in the population density in Asia, Europe, and America. The governments should make strict policies for traffic laws implementation. The government should allocate more budget for health sector expenditures. The governments should include traffic education as part of syllabus from primary to higher studies. Government should create awareness about the loss due to road crashes. [ABSTRACT FROM AUTHOR]

BACKGROUND: There is no consensus among medical experts as to whether patients with epilepsy (PWEs) should be permitted to drive. PWEs who have had uncontrolled seizures in the past year are at an increased risk of road traffic accidents, often leading to the destruction of property, injury, or death. Currently, there is no clear policy on whether PWEs can drive in Saudi Arabia. Existing policies attempt to balance the potentially harmful and beneficial aspects of the issue. The purpose of this study was to measure the prevalence of PWEs who are unfit to drive. MATERIALS AND METHODS: Data were collected by interviews, a structured validated questionnaire, and a review of the medical records of 140 PWEs, with a response rate of 84%. RESULTS: Fifty four percent of PWEs were found unfit to drive. Of the 118 participants, 17.7% did not drive and 97 (82.3%) drove. Of the 21 patients who did not drive, 14 (11.8% of the total sample) never drove and 7 (5.9% of the total sample) stopped driving because of epilepsy. Of the 104 patients who drove, 45 (43.2% of the total sample) had a history of seizures while they drove. These incidents had resulted in the involvement of 28 patients (26.9% of the total sample) in motor vehicle accidents and 17 (16.3% of the total sample) patients being admitted to the emergency room. CONCLUSION: Structured regulation and licensing procedures are necessary for PWEs to drive safely. Regulations in other countries demand that seizures be controlled for 1 year before epileptic patients are allowed unrestricted driving. Such regulations would improve road safety in Saudi Arabia. [ABSTRACT FROM AUTHOR]

Percolation transition is widely observed in networks ranging from biology to engineering. While much attention has been paid to network topologies, studies rarely focus on critical percolation phenomena driven by network dynamics. Using extensive real data, we study the critical percolation properties in city traffic dynamics. Our results suggest that two modes of different critical percolation behaviors are switching in the same network topology under different traffic dynamics. One mode of city traffic (during nonrush hours or days off) has similar critical percolation characteristics as small world networks, while the other mode (during rush hours on working days) tends to behave as a 2D lattice. This switching behavior can be understood by the fact that the high-speed urban roads during nonrush hours or days off (that are congested during rush hours) represent effective long-range connections, like in small world networks. Our results might be useful for understanding and improving traffic resilience. [ABSTRACT FROM AUTHOR]

Among traffic flow analysis, there are many methods presented for microscopic and mesoscopic traffic flow in past decades. However, the methods for macroscopic traffic flow analysis are relatively few. That is because the macroscopic traffic flow analysis needs more data and computational resources. In this paper, we focus on macroscopic traffic flow analysis using massive traffic data. A new method, traffic speed cloud maps, is proposed. It can present the traffic states in a large scale, accurately. Also, it can describe the variations of the congestion area. More importantly, with traffic speed cloud maps, people can capture the forming and degrading processes of the congestion and investigate the operation rules of macroscopic traffic flow. In order to evaluate the effectiveness of traffic speed cloud maps, 14 786 073 traffic samples are taken to perform experiments. Experimental results show that traffic speed cloud maps can present the traffic state of large areas accurately, and help us to investigate the variation of macroscopic traffic flow states intuitively and efficiently. [ABSTRACT FROM AUTHOR]

Background The prevalence of diabetes is on rise worldwide and environmental factors are being increasingly recognized to be involved in this rise. An emerging body of evidence has evaluated the impact of long-term exposure to noise on diabetes mellitus, highlighting the need to synthesize this evidence. Objectives To systematically review and conduct meta-analysis of the available evidence on the association between long-term exposure to transport and occupational noise exposure and diabetes mellitus. Methods Selected databases were searched for available evidence published till September 13th, 2017 following MOOSE guidelines. The quality of articles was assessed using the Newcastle–Ottawa Scale. Random effects meta-analysis was applied to abstract combined estimates for diabetes mellitus per 5 dB increase in noise exposure. We evaluated the heterogeneity applying Cochran's Q test and quantified it using I 2 statistic. Meta-regressions were conducted to identify sources of heterogeneity. Publication bias was evaluated using funnel plot and Egger's test. Results Fifteen studies met our inclusion criteria of which nine including five prospective cohorts, two cross-sectional and two case-control studies with a total number of 444460 adult participants and 17430 diabetes mellitus cases included in meta-analyses. We observed a 6% (95% confidence interval (CI): 3%, 9%) increase in the risk of diabetes mellitus per 5 dB increase in noise exposure regardless of its source. Source-specific analyses were suggestive for stronger associations for air traffic noise (combined odds ratio: 1.17; 95% CI: 1.06, 1.29 per 5 dB increase in exposure) flowed by road traffic noise (combined odds ratio: 1.07; 95% CI: 1.02, 1.12). We observed some indications of publication bias; however the findings were robust after trim and fill test. Meta-regression analyses showed that the adjustment in general, and not specifically related to air pollution, could predict the between-study heterogeneity in reported associations. Conclusions The results indicate an increased risk of diabetes mellitus associated with noise exposure, mainly related to air and road traffic. [ABSTRACT FROM AUTHOR]

This work deals with the need and possibility of building car parks in Bucharest above Dâmboviţa river. They included analyses referring to the evolution of the number of existing vehicles in Bucharest, an analysis of the number of vehicles in Bucharest, as compared to other European capitals, and also certain elements leading to the possibility and profitability of building a car park above Dâmboviţa River. [ABSTRACT FROM AUTHOR]

Predicting the risk of traffic demands and delays exceeding critical limits at road junctions, airports, hospitals, etc., requires knowing how both mean and variance of queue size vary over time. Microscopic simulation can explore variability but is computationally demanding and gives only sample results. A computationally efficient approximation to the mean is used in many modelling tools, but only empirical extensions for variance in particular situations have been available. The paper derives theoretical formulae for time-dependent and equilibrium variance, believed to be novel and to apply generally to queues covered by the Pollaczek–Khinchin mean formula, and offering possible structural insights. These are applied in an extended approximation giving mutually consistent mean and variance estimates with improved accuracy. Tests on oversaturated peak demand cases are compared with Markov probabilistic simulation, demonstrating accuracy (R2 > 0.99) for typical random, priority-like (M/M/1) and traffic-signal-like (M/D/1) queues. Implications for risk analysis, planning and policy are considered. [ABSTRACT FROM AUTHOR]

A probabilistic methodology is developed for the evaluation of characteristic maximum traffic load on long-span bridges for which congestion is the governing condition. It considers all the congestion types that can occur such as stop-and-go waves and oscillating congested traffic. The approach uses site-specific traffic data, such as flow and incident data. Statistics on driver behaviour and traffic incident frequency are assembled from the literature. As an example application of the method, a calibrated traffic microsimulation model is used to obtain the input data for the proposed methodology. The results counter many of the prevailing assumptions for long-span bridge loading. [ABSTRACT FROM AUTHOR]

A Workplace Parking Levy (WPL) scheme raises a levy on private non-domestic off street parking provided by employers. In April 2012 Nottingham became the first UK City to implement such a scheme with the revenue generated hypothecated for funding transport improvements. The lag between the introduction of the WPL and the opening of related public transport improvements represents an opportunity to study the impact of a WPL on congestion as a standalone measure. In order to achieve this it is necessary to consider changes to variables external to the WPL, which also impact on congestion, which may obscure any beneficial impact of the scheme. An autoregressive time series model which accounts for the impact of these exogenous variables is used to evaluate the impact of the introduction of the WPL on congestion. Delay per Vehicle Mile is used as the dependent variable to represent congestion while the number of Liable Workplace Parking Places (LWPP) is used as a continuous intervention variable representing the introduction of the WPL. The model also contains a number of economic, transportation and climatic control variables. The results indicate that the introduction of the WPL as measured by the number of LWPP has a statistically significant impact on traffic congestion in Nottingham. Additionally, external explanatory variables are also shown to impact on congestion, suggesting that these may be masking the true impact of the scheme. This research represents the first statistical analysis of the link between the introduction of a WPL and a reduction in congestion. [ABSTRACT FROM AUTHOR]

Experimental and numerical studies are performed to analyze a concrete bridge under moving vehicular loads considering the effects of the damage cracks, stochastic traffic flows, and bridge surface roughness. Specifically, (1) the crack zone in the concrete bridge is modeled by a damage function with three parameters, i.e. the length of damaged zone, the magnitude of the damage, and the variation of Young's modulus of the material; (2) a cellular automation (CA) based traffic flow model is adopted, which can capture the basic features of the probabilistic traffic flows using realistic traffic rules; (3) a three-dimensional (3D) vehicle model and a single vehicle model are each used to simulate the vehicles in the traffic flow for computational efficiency; and (4) the bridge and vehicle coupled equations are established by combining those for the bridge and vehicles using the displacement and interaction force relationship at the contact patches. The experimental and numerical investigations are conducted to validate the proposed modeling methodology. As an illustration, a prototype concrete bridge structure with partial damage is studied. Finally, parametric studies are conducted to study the effects of damage cracks, stochastic traffic flows, and surface roughness on the dynamic displacement, impact factor, impact force, and dynamic load coefficient of the bridge. [ABSTRACT FROM AUTHOR]

During many manmade and natural crises such as terrorist threats, floods, hazardous chemical and gas leaks, emergency personnel need to estimate the time in which people can evacuate from the affected urban area. Knowing an estimated evacuation time for a given crisis, emergency personnel can plan and prepare accordingly with the understanding that the actual evacuation time will take longer. Given the urban area to be evacuated, street widths exiting the area's perimeter, the area's population density, average vehicle occupancy, transport mode share and crawl speed, an estimation of traffic evacuation time can be derived. Peak-hour traffic data collected at three, midblock, Mumbai sites of varying geometric features and traffic composition were used in calibrating a model that estimates peak-hour traffic flow rates. Model validation revealed a correlation coefficient of +0.98 between observed and predicted peak-hour flow rates. A methodology is developed that estimates traffic evacuation time using the model. [ABSTRACT FROM AUTHOR]

The increasing requirement of transmission network sizes would result in huge energy consumption with communication traffic. Green communication technologies are expected to help in reducing energy consumption impact to environment. Therefore, it is important to design energy-efficient strategy that can decrease energy consumption. This paper proposes to use the acquaintance and improved targeted immunization strategies from complex systems to resolve energy consumption issues and uses traffic as measure standard to obtain a stable threshold. The simulation results show that the improved control strategy is better and more effective to save as much energy as possible. [ABSTRACT FROM AUTHOR]

The ‘mobilities turn’ has reinvigorated the social critique on the automobility system. Theorizing its profound reconfigurations of social life, relationist commitments invite a certain silence regarding the associated social pathologies, however. This article explores a critical-theoretical interpretation of the mobilities paradigm. It proposes the ‘interactive metal fatigue’ (IMF) concept, which theorizes the emergence of ‘interpassive’ social relations as socio-technical dialectics. Taking into account the contradictions that surround the critical-theoretical project, IMF paves the way for balanced critiques of mobilities. This will be shown through the case of Shared Space, an attempt to free public space from traffic management colonization. [ABSTRACT FROM PUBLISHER]

Multipath routing is a burning issue in mobile ad hoc network due to its various advantages over single path routing. Some of these advantages are load balancing, bandwidth aggregation, and fault tolerance. Multipath routing means multiple paths exist between source and destination pair. Many works discussed in section 2 addressed queuing delays, but none of them suggested queuing delay for multiple path deliveries of data in mobile ad hoc network context. In this paper, we have designed a mathematical model to compute delay and throughput for multipath. Our model follow the network of M/M/1 queues, and we have applied Burke's theorem to calculate the queuing delay of the packet in mobile network scenario. This model can be used to estimate delay and throughput of an individual path. Further, through the analysis the best path for data delivery out of available multiple paths as well as the multipath path can be used simultaneously for data delivery to the destination. Simulation result shows that splitted traffic multiple paths outperform splitted traffic. Therefore, our model is useful for design and analysis of ad hoc network. The simulation work has been carried out in Qualnet simulator. [ABSTRACT FROM AUTHOR]

In common with the rest of the developed world, road traffic noise has been a public policy issue in Australia for many years. From attitudinal studies relating to noise in the environment, it is consistently shown that the higher annoyance scores for noise heard within the home result from road traffic noise. Governments in Australia, at all levels, have responded with a range of traffic noise management measures. At the federal government level these have primarily related to reducing noise at the source, namely the vehicle. State governments have developed traffic noise policies to guide the design for major roads and to control the planning of new noise-sensitive areas adjacent to major road corridors. Local governments have also considered traffic noise and introduced local traffic management measures on roads they control. This paper reviews and discusses the approaches in the different policies in current use in Australian states and territories for the management of road traffic noise. [ABSTRACT FROM AUTHOR]

The present literature review study investigated the relationship between impulsivity and driver behaviors, offences and road traffic accidents through the lenses of characterological perspective. The studies published from 1970 to 2014 that examined and reported a relationship between impulsivity and at least one driving related outcome (e.g., a self-report measure of driver behavior) were included. The relevant 38 out of 288 studies are presented in four sections based on the driving related outcomes as; (i) aberrant driver behaviors and driving anger/aggression, (ii) driving under the influence, (iii) traffic offences and accidents, (iv) other. The vast majority of the studies reported significant relationships between impulsivity and the driving outcomes. The general findings of the studies in the literature, suggestions including a new definition of impulsivity in driving context, and future directions are discussed in the scope of a proposed integrative conceptual framework. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing (fracking) has been used extensively in the US and Canada since the 1950s and offers the potential for significant new sources of oil and gas supply. Numerous other countries around the world (including the UK, Germany, China, South Africa, Australia and Argentina) are now giving serious consideration to sanctioning the technique to provide additional security over the future supply of domestic energy. However, relatively high population densities in many countries and the potential negative environmental impacts that may be associated with fracking operations has stimulated controversy and significant public debate regarding if and where fracking should be permitted. Road traffic generated by fracking operations is one possible source of environmental impact whose significance has, until now, been largely neglected in the available literature. This paper therefore presents a scoping-level environmental assessment for individual and groups of fracking sites using a newly-created Traffic Impacts Model (TIM). The model produces estimates of the traffic-related impacts of fracking on greenhouse gas emissions, local air quality emissions, noise and road pavement wear, using a range of hypothetical fracking scenarios to quantify changes in impacts against baseline levels. Results suggest that the local impacts of a single well pad may be short duration but large magnitude. That is, whilst single digit percentile increases in emissions of CO 2 , NO x and PM are estimated for the period from start of construction to pad completion (potentially several months or years), excess emissions of NO x on individual days of peak activity can reach 30% over baseline. Likewise, excess noise emissions appear negligible (< 1 dBA) when normalised over the completion period, but may be considerable (+ 3.4 dBA) in particular hours, especially in night-time periods. Larger, regional scale modelling of pad development scenarios over a multi-decade time horizon give modest CO 2 emissions that vary between 2.5 and 160.4 kT, dependent on the number of wells, and individual well fracking water and flowback waste requirements. The TIM model is designed to be adaptable to any geographic area where the required input data are available (such as fleet characteristics, road type and quality), and we suggest could be deployed as a tool to help reach more informed decisions regarding where and how fracking might take place taking into account the likely scale of traffic-related environmental impacts. [ABSTRACT FROM AUTHOR]

This paper studies the synergic relationship between traffic and tourism in Croatia’s Dubrovnik-Neretva County by the 2020., based on the idicators detected in 2014. It elects the variables that characterise the synergy of traffic and tourism i, speaking from the standpoint of traffic and geography, in the most problematic county in the Republic of Croatia. The basic hypothesis has been confirmed through scientifically obtained research results, through the quantification of the model's variables and the direct growth rates of the designed model. On the basis of scientific insights into the sustainable development of traffic and tourism in Dubrovnik-Neretva County, it is possible to propose a new information model for traffic at the service of the sustainable development of tourism in the County for period 2014.-2020. [ABSTRACT FROM AUTHOR]

Air quality remains as one of the pressing problems of urban areas. While air pollution modelling is a well-established field of research in environmental engineering, the challenge is to integrate Geographic Information System - GIS as a scientific tool for analysis within the environmental policy-making and management process. This work aims to visualize modelled results from atmospheric dispersion of pollutants caused bytraffic, using capabilities of open source GIS tool, e.g. QGIS. Supporting air dispersion modelling, QGIS provides release of information in a convenient and easily understandable way, which can be quickly distributed to necessary sides for further management and decision making. [ABSTRACT FROM AUTHOR]

Objectives Road traffic injuries ( RTI) have become a leading cause for admissions at Luang Namtha Provincial Hospital (LNPH) in rapidly developing northern Laos. Objectives were to investigate trends, risk factors and better estimates of RTI. Methods Repeated annual surveys were conducted with structured questionnaires among all RTI patients at LNPH from 2007 to 2011. Hospital and police data were combined by capture-recapture method. Results The majority of 1074 patients were young [median 22 years (1-88)], male (68%), motorcyclists (76%), drove without licence (85%) and without insurance (95%). Most accidents occurred during evenings and Lao New Year. Serious motorbike injuries were associated with young age (1-15 years), male sex ( OR 2.2, 95% CI 1.1-4.6) and drivers ( OR 2.1, 95% CI 1.1-4.3); more serious head injuries with alcohol consumption ( OR 2.5, 95% CI 1.7-3.7), male sex ( OR 2.3, 95% CI 1.4-3.7) and no helmet use ( OR 2.0, 95% CI 1.2-3.4). No helmet use was associated with young age, time period, pillion passengers ( OR 2.7, 95% CI 1.6-4.7), alcohol ( OR 1.9, 95% CI 1.2-2.8) and no driver license ( OR 2.0; 95% CI 1.1-3.4). Main reasons not to wear helmets were not possessing one, and being pillion passenger. Capture-recapture analysis showed four times higher RTI estimates than officially reported. Mortality rate was 11.6/100.000 population (95% CI 5.1-18.1/100.000). Conclusions RTI were substantially underestimated. Combining hospital with police data can provide better estimates in resource-limited settings. Preventive programmes and law enforcement have to target male drivers, alcohol, licensing and helmet use, especially among children and pillion passengers. Increased efforts are needed during evening time and special festivals. [ABSTRACT FROM AUTHOR]

Background: Most countries have detailed lists of traffic rules and elaborate legal regimes for penalizing drivers who break them. Previous research has suggested that drivers tend to drive more safely after receiving penalties for traffic infringements.Methods: We linked driver-level data on infringements and crashes in Queensland, Australia (1995-2010) with information on the licence histories of all drivers in the state. We used a case-crossover design to examine drivers' risk of crashing in the month following an infringement penalty. We also examined whether changes in crash risk following infringement penalties varied according to driver age and gender, type of infringement and whether the offender was at fault in a subsequent crash.Results: Drivers had higher risks of crashes following infringement penalties [odds ratio (OR) 1.32; 95% confidence interval (CI) 1.29-1.36], especially crashes in which the offender was at fault (1.41; 1.36-1.46). Crash risk relative to a comparable period was particularly high for teenage drivers (1.55; 1.34-1.78) and among drivers penalized for dangerous driving (3.19; 2.52-4.03) or driving under the influence of alcohol (1.99; 1.67-2.37). The risk remained relatively high for more than 6 months after the penalty, but declined steadily over this period.Conclusions: Crash risk among drivers in Queensland was higher, not lower, following receipt of penalties for traffic infringements. Penalties themselves are unlikely to increase crash risk. A more likely explanation is that penalties (or the corresponding infringements) mark episodes of risky driving. Our findings suggest that such episodes trounce any deterrent effect penalties may produce. [ABSTRACT FROM AUTHOR]

Probabilistic analysis of traffic loading on a bridge traditionally involves an extrapolation from measured or simulated load effects to a characteristic maximum value. In recent years, long run simulations, whereby thousands of years of traffic are simulated, have allowed researchers to gain new insights into the nature of the traffic scenarios that govern at the limit state. For example, mobile cranes and low-loaders, sometimes accompanied by a common articulated truck, have been shown to govern in most cases. In this paper, the extreme loading scenarios identified in the long-run simulation are applied to a non-linear, two-dimensional (2D) plate finite element model. For the first time, the loading scenarios that govern in 2D nonlinear analyses are found and compared to those that govern for 2D linear and one-dimensional (1D) linear and nonlinear analyses. Results show that, for an isotropic slab, the governing loading scenarios are similar to those that govern in simple 1D (beam) models. Furthermore, there are only slight differences in the critical positions of the vehicles. It is also evident that the load effects causing failure in the 2D linear elastic plate models are significantly lower, i.e., 2D linear elastic analysis is more conservative than both 2D nonlinear and 1D linear and nonlinear analyses. [ABSTRACT FROM AUTHOR]

In this paper, we consider repeated routing games with piecewise-constant congestion taxing in which a central planner sets and announces the congestion taxes for fixed windows of time in advance. Specifically, congestion taxes are calculated using marginal congestion pricing based on the flow of the vehicles on each road prior to the beginning of the taxing window (and, hence, there is a time-varying delay in setting the congestion taxes). We motivate the piecewise-constant taxing policy by that users or drivers may dislike fast-changing prices and that they also prefer prior knowledge of the prices. We prove for this model that the multiplicative update rule and the discretized replicator dynamics converge to a socially optimal flow when using vanishing step sizes. Considering that the algorithm cannot adapt itself to a changing environment when using vanishing step sizes, we propose adopting constant step sizes in this case. Then, however, we can only prove the convergence of the dynamics to a neighborhood of the socially optimal flow (with the size of the neighbourhood being of the order of the selected step size). The results are illustrated on a nonlinear version of Pigou’s famous routing game. [ABSTRACT FROM AUTHOR]

Transportation (on road, water and through air) is the most powerful potential source of acoustic pollution these days, so its framing in general ecological cycle is not suitable. Man must better understand the unity of the nature with all intimate connections between all its factors and to insert them in these complex structures and objective phenomena. [ABSTRACT FROM AUTHOR]

This study focuses on correlations between total number concentrations, road traffic emissions and noise levels in an urban area in the southwest of Spain during the winter and summer of 2009. The high temporal correlation between sound pressure levels, traffic intensity, particle number concentrations related to traffic, black carbon and NO x concentrations suggests that noise is linked to traffic emissions as a main source of pollution in urban areas. First, the association of these different variables was studied using PreFuRGe, a computational tool based on data mining and fuzzy logic. The results showed a clear association between noise levels and road-traffic intensity for non-extremely high wind speed levels. This behaviour points, therefore, to vehicular emissions being the main source of urban noise. An analysis for estimating the total number concentration from noise levels is also proposed in the study. The high linearity observed between particle number concentrations linked to traffic and noise levels with road traffic intensity can be used to calculate traffic related particle number concentrations experimentally. At low wind speeds, there are increases in noise levels of 1 dB for every 100 vehicles in circulation. This is equivalent to 2000 cm − 3 per vehicle in winter and 500 cm − 3 in summer. At high wind speeds, wind speed could be taken into account. This methodology allows low cost sensors to be used as a proxy for total number concentration monitoring in urban air quality networks. [ABSTRACT FROM AUTHOR]

This article draws attention to the emergent modes of urban sociality and circumscribed mobility that define the lives of traffic-stricken residents in the megacity of Jakarta, Indonesia. I argue that Jakarta traffic has exceeded the scale and discourse of a technopolitical problem of failed infrastructure; rather, the systemic and rhizomic nature of traffic provides the temporal infrastructure that governs the flow of living and leisure, and the patterning of individual desires and struggles in urban Indonesia. I use the term 'absolute traffic' to convey the limit horizon of gridlock as a set of exhausting physical and psychic states that urban residents survive daily. Despite such overwhelming challenges to mobility, particularly for the city's underprivileged populations, I argue for an agentive perspective of absolute traffic in which forms of play, negotiation and disruption form important moments for the public display of infrastructural aptitude. Strategies for surviving and engaging with absolute traffic emerge in ephemeral sites of finely attuned traffic subjectivity --in the sociality of strangers, the political demonstrations of activists, the growing citizen journalism for traffic reports on radio shows and social media sites, and finally, in the artistic sensibility of artists captivated by the vernacular forms of urban chaos. [ABSTRACT FROM AUTHOR]

This brief note is an introduction to the special issue devoted to modeling, qualitative analysis and simulations of vehicular traffic, crowds and swarms, viewed as living, hence complex, systems. The first part focuses on the conceptual difficulties to be tackled when dealing with the most challenging topics of this subject, mainly on interactions and complexity features. The second part provides a brief overview and critical analysis of the contents. Finally, some perspective ideas on conceivable future research objectives are brought to the reader's attention. [ABSTRACT FROM AUTHOR]

This paper focused on modelling Black Carbon (BC) concentrations in two busy street canyons, the Crown and Belliard Street in Brussels. The used original Operational Street Pollution Model was adapted to BC by eliminating the chemical module and is noted here as CANS BC . Model validations were performed using temporal BC data from the fixed measurement network in Brussels. Subsequently, BC emissions were adjusted so that simulated BC concentrations equalled the observed ones, averaged over the whole period of simulation. Direct validations were performed for the Crown Street, while BC model calculations for the Belliard Street were validated indirectly using the linear relationship between BC and NO x . Concerning the Crown Street, simulated and observed half-hourly BC concentrations correlated well ( r = 0.74) for the period from July 1st, 2011 till June 30th, 2013. In particular, CANS BC performed very well to simulate the monthly and diurnal evolutions of averaged BC concentrations, as well as the difference between weekdays and weekends. This means that the model correctly handled the meteorological conditions as well as the variation in traffic emissions. Considering dispersion, it should however be noted that BC concentrations are better simulated under stable than under unstable conditions. Even if the correlation on half-hourly NO x concentrations was slightly lower ( r = 0.60) than the one of BC, indirect validations of CANS BC for the Belliard Street yielded comparable results and conclusions as described above for the Crown Street. Based on our results, it can be stated that CANS BC is suitable to accurately simulate BC concentrations in the street canyons of Brussels, under the following conditions: (i) accurate vehicle counting data is available to correctly estimate traffic emissions, and (ii) vehicle speeds are measured in order to improve emission estimates and to take into account the impact of the turbulence generated by moving vehicles on the local dispersion of BC. [ABSTRACT FROM AUTHOR]

Objective. To identify and summarize the findings of studies describing interventions aimed at reducing road traffic injuries. Methods. An integrative systematic review without meta-analysis was performed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were used to synthesize the findings of the articles reviewed. The keywords "traffic accidents", "review" and "public policy" were used in isolation or combined with boolean operator "And" to search PubMed, Web of Science, SciELO, and LILACS for the period between 2006 and 2011. Results. Twenty-two studies were included in the systematic review. Of these, two described engineering strategies, two described other road safety policies, three described education strategies, and 15 described law enforcement policies. Law enforcement had the most effective immediate results. Engineering strategies proved important to promote a safe environment. Finally, education strategies had an informative role and served to support other strategies, but did not seem sufficient to promote cultural changes regarding road safety. Conclusions. Law enforcement seems to be the most effective strategy to change the behavior of drivers, especially regarding speed limits and drinking and driving. [ABSTRACT FROM AUTHOR]

We conducted a multi-country study to estimate the perceived economic values of traffic-related air pollution and noise health risks within the framework of a large European project. We used contingent valuation as a method to assess the willingness-to-pay (WTP) for both types of pollutants simultaneously. We asked respondents how much they would be willing to pay annually to avoid certain health risks from specific pollutants. Three sets of vignettes with different levels of information were provided prior to the WTP questions. These vignettes described qualitative general health risks, a quantitative single health risk related to a pollutant, and a quantitative scenario of combined health risks related to a pollutant. The mean WTP estimates to avoid road-traffic air pollution effects for the three vignettes were: €130 per person per year (pp/y) for general health risks, €80 pp/y for a half year shorter in life expectancy, and €330 pp/y to a 50% decrease in road-traffic air pollution. Their medians were €40 pp/y, €10 pp/y and €50 pp/y, respectively. The mean WTP estimates to avoid road-traffic noise effects for the three vignettes were: €90 pp/y for general health risks, €100 pp/y for a 13% increase in severe annoyance, and €320 pp/y for a combined-risk scenario related to an increase of a noise level from 50 dB to 65 dB. Their medians were €20 pp/y, €20 pp/y and €50 pp/y, respectively. Risk perceptions and attitudes as well as environmental and pollutant concerns significantly affected WTP estimates. The observed differences in crude WTP estimates between countries changed considerably when perception-related variables were included in the WTP regression models. For this reason, great care should be taken when performing benefit transfer from studies in one country to another. [ABSTRACT FROM AUTHOR]

The object of this paper is to analyze and to suggest improvements on intersection management systems using existing equipment currently available in street intersections. In order to do this, we designed an intersection management system capable of detecting traffic violations as well as vehicle collisions using high-speed cameras. We propose to implement the above mentioned system through design and simulation in the LabVIEW programming environment. LabVIEW offers all the instrumentation necessary to accurately simulate the phenomena that occur in modern-day intersections, making it possible to further develop the existing intersection technology. It also makes it possible to determine the requirements and limitations of the existing equipment and to find the best solutions for every scenario. [ABSTRACT FROM AUTHOR]

Correlated traffic data refers to a collection of time series recorded simultaneously in different regions throughout the same transportation network route. Due to the presence of both temporal and spatial correlation properties between multiple time series data, accurate time series prediction becomes challenging. The accuracy of the traffic data prediction helps mitigating traffic congestion and establish a robust traffic management system. When a prediction algorithm fails to consider the correlations present in the dataset, the accuracy of the prediction results reduces. To overcome the prediction shortcomings, this study proposes a Long Short-Term Memory (LSTM)-based correlated traffic data prediction (LSTM-CTP) framework. The proposed LSTM-CTP framework was employed for two different real-time traffic datasets. These datasets were initially preprocessed to capture both temporal and spatial trends and the correlations between the collected data series. By employing LSTM, temporal and spatial trends were predicted. Further, the Kalman-filter approach was employed to obtain the final prediction by aggregating the temporal and spatial trend predictions. The performance of the proposed LSTM-CTP was evaluated using different performance metrics and compared with different time-series prediction algorithms. The proposed framework showed substantial improvements in prediction results compared to the other algorithms. Overall, the proposed LSTM-CTP framework can help control traffic congestion and ensure a more robust traffic management system in the future. [ABSTRACT FROM AUTHOR]

In this paper, we propose a pair-dependent rejection rate of packet information between routers in the framework of the minimal traffic model applied to scale-free networks. We have shown that the behavior of the transition point from the phase where the system balances the inflow of new information packets with successful delivery of the old ones to the congested phase depends on the underlying mechanism of packet rejection. It is possible to achieve larger values for the critical load by varying the rejection of the packets issued from a given node by its neighbors. We have proposed an asymmetric protocol, where we found the existence of a whole interval where the packet rejection is strongly beneficial to the overall performance of the system. We have also shown that for the dynamic protocol, the transition point is shifted toward higher values permitting the network to handle more traffic load, despite the fact that the critical load decreases when increasing the rejection parameter. [ABSTRACT FROM AUTHOR]

Background: Traffic-related air pollution (TRAP) is a major source of air pollution but the impact on health in Nigeria is not well described. Patients and Methods: A descriptive cross-sectional study of road traffic workers and university students in Lagos. Eligible, accessible and willing participants were included in the sample. Respiratory symptoms and anthropometry were obtained from all the participants using an adapted Medical Research Council (MRC) questionnaire and they all did a spirometry test and exhaled carbon monoxide (CO) test. Results: Fifty-nine individuals participated with complete data, including 47 traffic policemen and 12 students who acted as controls. The mean age (SD) was 35.1 (8.0) and 35.4 years (6.3) for the traffic workers and students, respectively. All the respondents were men. The mean (SD) duration of occupation as a traffic policeman was 4.4 (4.4) and a median of 4 years (range 1-25). There was no significant difference in the presentation of respiratory and non-respiratory symptoms between the two groups. Compared with the students, the traffic workers had higher age, height and sex adjusted forced expiratory volume in one second and forced vital capacity. Traffic policemen had significantly higher levels of exhaled CO than the students (1.18 vs 0.73 ppm, P < 0.006). Conclusion: There is a high prevalence of respiratory symptoms in both traffic policemen and non-traffic residents of Lagos metropolis, indicating widespread pollution. [ABSTRACT FROM AUTHOR]

Abstract: Background: Increasing evidence suggests that ultrafine particles (UFPs) may contribute to cardiorespiratory morbidity. We examined the relationship between near road UFPs and several traffic and built environment factors to identify predictors that may be used to estimate exposures in population-based studies. Black carbon (BC) was also examined. Methods: Data were collected on up to 6 occasions at 73 sites in Montreal, Canada over 6-week period during summer, 2012. After excluding highly correlated variables, road width, truck ratio (trucks/total traffic), building height, land zoning parameters, and meteorological factors were evaluated. Random-effect models were used to estimate percent changes in UFP and BC concentrations with interquartile changes in each candidate predictor adjusted for meteorological factors. Results: Mean pollutant concentrations varied substantially across sites (UFP range: 1977–94, 798particles/cm3; BC range: 29–9460ng/m3). After adjusting for meteorology, interquartile increases in road width (14%, 95% CI: 0, 30), building height (13%, 95% CI: 5, 22), and truck ratio (13%, 95% CI: 3, 23) were the most important predictors of mean UFP concentrations. Road width (28%, 95% CI: 9, 51) and industrial zoning (18%, 95% CI: 2, 37) were the strongest predictors of maximum UFP concentrations. Industrial zoning (35%, 95% CI: 9, 67) was the strongest predictor of BC. Conclusions: A number of traffic and built environmental factors were identified as important predictors of near road UFP and BC concentrations. Exposure models incorporating these factors may be useful in evaluating the health effects of traffic related air pollution. [Copyright &y& Elsevier]

In a traffic-aware route search (TARS), the user provides start and target locations and sets of search terms. The goal is to find the fastest route from the start location to the target via geographic entities (points of interest) that correspond to the search terms, while taking into account variations in the travel speed due to changes in traffic conditions, and the possibility that some visited entities will not satisfy the search requirements. A TARS query may include temporal constraints and order constraints that restrict the order by which entities are visited. Since TARS generalizes the Traveling-Salesperson Problem, it is an NP-hard problem. Thus, it is unlikely to find a polynomial-time algorithm for evaluating TARS queries. Hence, we present in this paper three heuristics to answer TARS queries-a local greedy approach, a global greedy approach and an algorithm that computes a linear approximation to the travel speeds, formulates the problem as a Mixed Integer Linear Programming (MILP) problem and uses a solver to find a solution. We provide an experimental evaluation based on actual traffic data and show that using a MILP solver to find a solution is effective and can be done within a limited running time in many real-life scenarios. The local-greedy approach is the least effective in finding a fast route, however, it has the best running time and it is the most scalable. [ABSTRACT FROM AUTHOR]

Mechanistic-empirical pavement design guide (MEPDG) uses axle load spectra and the number of axle applications to characterise traffic loads for pavement design. Alberta Transportation installed weigh-in-motion (WIM) systems at six highway locations to characterise traffic loads in Alberta for MEPDG design. Seasonal and regional trends in traffic characteristics of the six WIM sites were investigated and compared with the default values in the MEPDG for the years 2009 and 2010. Truck traffic classification (TTC) and axle load distribution factor (ALDF) for the WIM sites showed deviations from the MEPDG defaults. Seasonal variations were also evident in the distribution of different classes of truck throughout the year. Differences are attributed to cold climate conditions and special truck traffic in Alberta because of local industries. Influence of the differences between site-specific traffic characteristics and the MEPDG defaults on the performance of both flexible and rigid pavements for Alberta conditions was investigated through a sensitivity analysis. It was found that the flexible pavement performance is sensitive to TTC and ALDF, and the rigid pavement performance is most sensitive to ALDF. [ABSTRACT FROM AUTHOR]

Highlights: [•] This study explores firm-level relocation decisions in response to traffic congestion in Philadelphia. [•] This research evaluates firm decisions to flee regionally and locally-scaled congestion between 2003 and 2007. [•] This study estimates models of firm relocation and location choices as consequences of multiple explanatory variables. [•] Results suggest that high regional congestion and low local congestion are predictors of relocation. [•] On aggregate, results suggest that regional congestion is a diseconomy and local congestion appears to be an amenity. [Copyright &y& Elsevier]

An effective calibration method of the cellular automaton based traffic microsimulation model is proposed in this paper. It is shown that by utilizing a genetic algorithm it is possible to calibrate different parameters of the model much better than a traffic expert. Moreover, using this process it is also possible to find several model parameters that arc extremely difficult to calibrate as relevant data can not be measured using standard monitoring technologies or complete data sets arc often not available. The quality of the new calibrated models is discussed in the task of vehicle travel time estimation. The precision of simulations is increased over three times compared to a manually tuned model. The average error rate is 10.75 % in comparison with several field travel time data. [ABSTRACT FROM AUTHOR]

The article explores the relationship between regulating traffic and structuring congestion in mid-nineteenth-century London. It examines plans for the opening of new streets and for the erection of dedicated structures such as subways and pedestrian bridges, as well as the debates around legislation regulating everyday practices, which included the introduction of time intervals and designating pedestrian street crossings. The need for people and vehicles to circulate was central to all of these as were the reactions against congestion. The article interrogates the extent to which the study of what might be termed circulation's inextricable other, namely congestion, sheds a new light on our understanding of the experience of modernity at a particular time in London's history. [ABSTRACT FROM AUTHOR]

The negative impacts of urban traffic growth are well known, e.g., congestion, increased air pollution, and more traffic noise. Humans can readily see traffic congestion, and can hear traffic noise, but inevitably they are much less aware of odorless, invisible, silent air pollution. Therefore, quite naturally people, whether the general public or transport professionals, struggle to visualize air pollution from traffic, and will find it particularly difficult to visualize changes in air pollution levels resulting from changes in traffic conditions because of the implementation of various urban transport schemes. Hence, there is always a risk of the air quality impacts of potential urban transport schemes being underappreciated. Therefore, this paper contributes to the knowledge by devising a new three-dimensional (3D) visualization approach for modeled air quality before and after the implementation of potential urban transport schemes. Using the Dunkirk area of the City of Nottingham in the United Kingdom as a case study, research has been undertaken to integrate an air pollution dispersion model for the pollutant with a 3D digital city model. The modeled concentrations, before and after the implementation of an urban transport scheme, were represented in the 3D city model at various heights above the ground: first, as 3D point shapes; second, as 3D planar surfaces; and finally, as 3D volumetric clouds. The 3D volumetric clouds approach used the analogy of people's perceptions of gray clouds in the sky as representing undesirable weather, and hence provided an intuitive 3D visualization of all the modeled concentrations, at and above the ground surface, in a single 3D virtual scene. Benefits have been identified in enhancing the level of understanding of the pollution dispersion using this new approach to visualization. This has allowed the visualization process to be used in the development of future traffic scenarios that could be used to alter the design of a proposed transport scheme to increase its air quality benefits. This 3D visualization approach was found to be applicable to other transport schemes in different parts of the City of Nottingham. [ABSTRACT FROM AUTHOR]

Abstract: An integrated modelling approach is adopted to estimate microscale urban traffic emissions. The modelling framework consists of a traffic microsimulation model developed in PARAMICS, a microscopic emissions model (Comprehensive Modal Emissions Model), and two dispersion models, AERMOD and the Quick Urban and Industrial Complex (QUIC). This framework is applied to a traffic network in downtown Toronto, Canada to evaluate summer time morning peak traffic emissions of carbon monoxide (CO) and nitrogen oxides (NO x ) during five weekdays at a traffic intersection. The model predicted results are validated against sensor observations with 100% of the AERMOD modelled CO concentrations and 97.5% of the QUIC modelled NO x concentrations within a factor of two of the corresponding observed concentrations. Availability of local estimates of ambient concentration is useful for accurate comparisons of predicted concentrations with observed concentrations. Predicted and sensor measured concentrations are significantly lower than the hourly threshold Maximum Acceptable Levels for CO (31 ppm, ∼90 times lower) and NO2 (0.4 mg/m3, ∼12 times lower), within the National Ambient Air Quality Objectives established by Environment Canada. [Copyright &y& Elsevier]

The development of real time traffic flow models for urban road networks is of paramount importance for the purposes of optimizing and control of traffic flow. Motivated by the modeling of road networks in last decade, this paper proposes a different and simplified approach, known as section approach to model road networks in the framework of macroscopic traffic flow models. For evaluation of the traffic states on a single road, an anisotropic continuum GK-model developed by [Gupta and Katiyar, J. Phys. A 38, 4069 (2005)] is used as a single-section model. This model is applied to a two-section single lane road with points of entry and exits. In place of modeling the effect of off- and on-ramps in the continuity equation, a set of special boundary condition is taken into account to treat the points of entry and exit. A four-section road network comprised of two one-lane roads is also modeled using this methodology. The performances of the section approaches are investigated and obtained results are demonstrated over simulated data for different boundary conditions. [ABSTRACT FROM AUTHOR]

Abstract: Many studies nowadays make the effort of determining personal exposure rather than estimating exposure at the residential address only. While intra-urban air pollution can be modeled quite easily using interpolation methods, estimating exposure in transport is more challenging. The aim of this study is to investigate which factors determine black carbon (BC) concentrations in transport microenvironments. Therefore personal exposure measurements are carried out using portable aethalometers, trip diaries and GPS devices. More than 1500 trips, both by active modes and by motorized transport, are evaluated in Flanders, Belgium. GPS coordinates are assigned to road segments to allow BC concentrations to be linked with trip and road characteristics (trip duration, degree of urbanization, road type, traffic intensity, travel speed and road speed). Average BC concentrations on highways (10.7μg/m3) are comparable to concentrations on urban roads (9.6μg/m3), but levels are significantly higher than concentrations on rural roads (6.1μg/m3). Highways yield higher BC exposures for motorists compared to exposure on major roads and local roads. Overall BC concentrations are elevated at lower speeds (<30km/h) and at speeds above 80km/h, in accordance to vehicle emission functions. Driving on roads with low traffic intensities resulted in lower exposures than driving on roads with higher traffic intensities (from 5.6μg/m3 for roads with less than 500veh/h, up to 12μg/m3 for roads with over 2500veh/h). Traffic intensity proved to be the major explanatory variable for in-vehicle BC exposure, together with timing of the trip and urbanization. For cyclists and pedestrians the range in BC exposure is smaller and models are less predictive; for active modes exposure seems to be influenced by timing and degree of urbanization only. [Copyright &y& Elsevier]