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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]

The analysis of travel behavior is the basis for urban road traffic planning, management, and policy formulation. This paper studies the morning peak travel behavior of urban residents when autonomous vehicles and conventional vehicles coexist, based on the behavioral differences between the two in driving and parking. The paper addresses the following three scenarios: (1) Autonomous vehicles only improve road capacity; (2) Autonomous vehicles only reduce travel time; (3) They affect both road capacity and travel time. For each scenario, all possible equilibrium travel modes were considered to derive the system costs under different proportions of intelligent and non-intelligent vehicle users. Under the assumptions of the proposed model, the choice of travel behavior in different travel modes is deduced, as well as the departure rate, critical time point, and travel cost of travelers. It can be seen that increasing the capacity of intelligent vehicles relative to conventional vehicles, reducing the coefficient of travel cost reduction, and increasing the proportion of autonomous vehicles all reduce the total system cost. This research helps to deepen the understanding of morning peak travel modes in a mixed vehicle environment and provides theoretical guidance for transportation management departments to formulate multi-modal travel plans. [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]

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]

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]

[Display omitted] Carbon footprint analysis measures the greenhouse gas emissions from the mobilization of members of an institution. Commonly, the product between the distance and economy fuel rate is used to estimate fuel consumption and, thus, carbon dioxide emission (CO 2). However, the distance is a constant variable in a specific route, generating constant values of fuel consumption. We analyzed the influence at the local level of the time variable in the fuel consumption by each leg of an entire route and the type of vehicle used. The results showed that in intense traffic conditions, the consumed fuel was 1.1–1.5 times more than normal. The proposed approach presented similar results to previous studies with real-world carbon dioxide emissions. In addition, using a multivariate regression model, the relationship between CO 2 emitted with time disaggregated by the leg and by the type of vehicle was found to be linear, significant, and highly correlated. [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]

Estimates of road speeds have become commonplace and central to route planning, but few systems in production provide information about the reliability of the prediction. Probabilistic forecasts of travel time capture reliability and can be used for risk-averse routing, for reporting travel time reliability to a user, or as a component of fleet vehicle decision-support systems. Many of these uses (such as those for mapping services like Bing or Google Maps) require predictions for routes in the road network, at arbitrary times; the highest-volume source of data for this purpose is GPS data from mobile phones. We introduce a method (TRIP) to predict the probability distribution of travel time on an arbitrary route in a road network at an arbitrary time, using GPS data from mobile phones or other probe vehicles. TRIP captures weekly cycles in congestion levels, gives informed predictions for parts of the road network with little data, and is computationally efficient, even for very large road networks and datasets. We apply TRIP to predict travel time on the road network of the Seattle metropolitan region, based on large volumes of GPS data from Windows phones. TRIP provides improved interval predictions (forecast ranges for travel time) relative to Microsoft’s engine for travel time prediction as used in Bing Maps. It also provides deterministic predictions that are as accurate as Bing Maps predictions, despite using fewer explanatory variables, and differing from the observed travel times by only 10.1% on average over 35,190 test trips. To our knowledge TRIP is the first method to provide accurate predictions of travel time reliability for complete, large-scale road networks. [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]

Public health concerns regarding adverse health effects for populations spending significant amounts of time near high traffic roadways has increased substantially in recent years. Roadside features, including solid noise barriers, have been investigated as potential methods that can be implemented in a relatively short time period to reduce air pollution exposures from nearby traffic. A field study was conducted to determine the influence of noise barriers on both on-road and downwind pollutant concentrations near a large highway in Phoenix, Arizona, USA. Concentrations of nitrogen dioxide, carbon monoxide, ultrafine particles, and black carbon were measured using a mobile platform and fixed sites along two limited-access stretches of highway that contained a section of noise barrier and a section with no noise barrier at-grade with the surrounding terrain. Results of the study showed that pollutant concentrations behind the roadside barriers were significantly lower relative to those measured in the absence of barriers. The reductions ranged from 50% within 50 m from the barrier to about 30% as far as 300 m from the barrier. Reductions in pollutant concentrations generally began within the first 50 m of the barrier edge; however, concentrations were highly variable due to vehicle activity behind the barrier and along nearby urban arterial roadways. The concentrations on the highway, upwind of the barrier, varied depending on wind direction. Overall, the on-road concentrations in front of the noise barrier were similar to those measured in the absence of the barrier, contradicting previous modeling results that suggested roadside barriers increase pollutant levels on the road. Thus, this study suggests that noise barriers do reduce potential pollutant exposures for populations downwind of the road, and do not likely increase exposures to traffic-related pollutants for vehicle passengers on the highway. [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]

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 article presents the development of a estimation model using an artificial neural network to estimate the traffic factor parameter, which reflects changes in travel time for a single transport connection. The modeling of traffic is highly challenging due to the complex and non-linear nature of road systems, the interactions between diverse road users, and the ripple effects of congestion. The research problem addressed is the need to consider a wide range of factors that contribute to congestion, as identified in the literature. To address this challenge, a universal Feedforward Neural Network (FNN) was designed, specifically the Multilayer Perceptron (MLP) 38–10-1 model. The input layer neurons of the MLP receive a vector of input values representing various factors such as road types, technical properties, time of day, days of the week, incidents, weather conditions, and population density. The model was trained using a dataset consisting of 41,945 records of fully completed input variables, extracted from a larger dataset of 300,000 travel time measurements collected from a real transport network mapped on a macro scale (Mazovia, Poland). During the research, the model achieved a satisfactory level of Mean Absolute Percentage Error (MAPE) for the test set (9.12%) and a Normalized Root Mean Squared Error (NRMSE) below 0.02, indicating good estimation performance. Furthermore, this work proposes specialized models with the structure of MLP 34–10-1 for individual types of roads, which also demonstrated satisfactory estimation abilities. These models have practical applications in traffic management and planning. Overall, this research addresses the research problem of modeling factors for predicting travel time changes using an artificial neural network approach. The developed models provide accurate estimations and offer potential applications in transportation systems. [ABSTRACT FROM AUTHOR]

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]

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 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]

Modelling approaches for simulating air and stormwater pollution due to on-road vehicles are reviewed and discussed. Models for traffic, emissions, atmospheric dispersion, and stormwater contamination are studied with particular emphasis on their couplings to create a modelling chain. The models must be carefully selected according to the requirements and level of detail of the integrated modelling chain. Although a fair amount of research has been conducted to link air pollution and road traffic, many questions related to spatio-temporal scales, domains of validity, consistency among models, uncertainties of model simulation results, and interfaces between models remain open. The aim of this work is to review the current status of the relationships between traffic, emissions, air quality, and water quality models, to recommend modelling approaches and to propose some directions for improving the state of the science. The difficulties and challenges associated with model coupling are illustrated with specific examples. [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 current generation of macroscopic and microscopic simulation packages do not have control algorithms that incorporate many of the advanced features now available in commercial traffic control hardware. Consequently, there is a need to develop cost effective procedures for evaluating state of the practice traffic signal control equipment so that informed deployment and design decisions can be made. These same procedures can also be used by researchers to develop new algorithms for applications such as transit priority or adaptive control. In order to achieve that objective, this paper presents the motivation for using hardware-in-the-loop simulation procedures. Hardware-in-the-loop simulation presents a new set of challenges for traffic engineering model developers as the “correctness” of a real-time model not only depends upon the numerical computation, but the timeliness with which the simulation model interacts with external control equipment. This paper reviews the state of practice, summarizes the fundamental technologies necessary for implementing such a system, and uses a simple statistical test for assessing the real-time errors introduced into a simulation model. [Copyright &y& Elsevier]

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]

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]

The Traffic and Urban Mobility System (Sistema de Información de Tráfico y Movilidad Urbana - SITYMUR) is a tool used to collect positional data from circulating agents on the roads, in order to generate traffic and mobility information in near real time. This issue raises important technological challenges concerning communications, data processing and publication of the results. This article describes these challenges and discusses the effectiveness of solutions proposed by showing a number of traffic and speed results for Bogotá as well as suggesting possible alternatives for improvement. [ABSTRACT FROM AUTHOR]

Traffic flow at a single crossroad consisting of two perpendicular one-lane roads, treated earlier by Ishibashi and Fukui [ J. Phys. Soc. Jpn. 70, 2793 (2001); 70, 3747 (2001)], has been studied on the basis of the local occupation probability method. However, in this work, based on the novel theoretical analysis and computer simulations, we have studied this crossroad traffic model again and presented the same phase diagrams of traffic flow in the case of various maximum vehicle velocities. We have also derived the flow formulas in all regions in the phase diagrams, which are in good agreement with computer simulation results. Compared with the previous local occupation probability method, our analytical way is simpler and may be widely used for other traffic bottlenecks research. [ABSTRACT FROM AUTHOR]

Community severance occurs where road traffic (speed or volume) inhibits access to goods, services, or people. Appleyard and Lintell's seminal study of residents of three urban streets in San Francisco found an inverse relationship between traffic and social contacts. The extent of social networks predicts unhealthy behaviors, poor health, and mortality; high rather than low social integration is associated with reduced mortality, with an effect size of similar magnitude to stopping smoking. Although community severance diminishes social contacts, the implications of community severance for morbidity and mortality have not been empirically established. Based on a systematic literature search, we discuss what is actually known about community severance. There is empirical evidence that traffic speed and volume reduces physical activity, social contacts, children's play, and access to goods and services. However, no studies have investigated mental or physical health outcomes in relation to community severance. While not designed specifically to do so, recent developments in road design may also ameliorate community severance. [ABSTRACT FROM AUTHOR]

The determination of characteristic bridge load effect is a complex problem. Usually, statistical extrapolation of simulated static load effects is used to derive a lifetime characteristic static load effect. However, when a vehicle crosses a bridge, dynamic interactions occur which often cause greater total load effect. This total load effect is related to the static load effect through a dynamic amplification factor (DAF). Specifications often recommend a conservative level for DAF, based on bridge length, number of lanes, and type of load effect only. Therefore significant improvements in the accuracy of this calculation are possible if a DAF, specific to the considered bridge, is applied. In this paper, the authors develop a novel method that considers site-specific bridge and traffic load conditions and allows for the reduced probability of both high static loading and high dynamic interaction occurring simultaneously. This approach utilises multivariate extreme value theory, in conjunction with static simulations and finite element vehicle–bridge dynamic interaction models. It is found that the dynamic allowance for the sample bridge and traffic considered is significantly less than recommended by bridge codes. This finding can have significant implications for the assessment of existing bridge stock. [ABSTRACT FROM PUBLISHER]

Abstract: How much can we tell about flows through networks just from their topological properties? Whereas flow distributions of river basins, trees or cardiovascular systems come naturally to mind, more complex topologies are not so immediate, especially if the network is large and heterogeneously directed. Our study is motivated by the question of how the distribution of path-dependent trails in directed networks is correlated to the distribution of network flows. As an example we have studied the path-dependencies in closed trails in four metropolitan areas in England and the USA and computed their global and spatial correlations with measured traffic flows. We have found that the heterogeneous distribution of traffic intensity is mirrored by the distribution of agglomerate path-dependency and that high traffic roads are packed along corridors at short-to-medium trail lengths from the ensemble of nodes. [ABSTRACT FROM AUTHOR]

Abstract: We intend to define a continuous car-following model exclusively based on the time gap. A model of the interaction between a vehicle and its predecessor is produced by adjusting the time gap to a targeted safety time that is a function of speed. The model is defined by a differential system, to which a consistent numerical scheme is associated. The parameters of the model are statistically estimated by maximum likelihood. In order to reproduce a heterogeneous traffic flow, vehicles are differentiated by type, and to recreate asymmetric longitudinal behavior, acceleration phases are distinguished from deceleration phases. Introducing a reaction time, inducing a delay in the perception and processing of information about vehicles in interaction, can alter the stability of the flux through appearance of kinematic waves. By simulation, the types and domains of parameters which are asymptotically unstable are identified. The results reveal that, in the model, the statistically estimated parameters form is strongly factor of instability. [Copyright &y& Elsevier]

Urban streets are hierarchically organized in the sense that a majority of streets are trivial, while a minority of streets is vital. This hierarchy can be simply, but elegantly, characterized by the 80/20 principle, i.e. 80% of streets are less connected (below the average), while 20% of streets are well connected (above the average); out of the 20%, there is 1% of streets that are extremely well connected. This paper, using a European city as an example, examined, at a much more detailed level, such street hierarchies from the perspective of geometric and topological properties. Based on an empirical study, we further proved a previous conjecture that a minority of streets accounts for a majority of traffic flow; more accurately, the 20% of top streets accommodate 80% of traffic flow (20/80), and the 1% of top streets account for more than 20% of traffic flow (1/20). Our study provides new evidence as to how a city is (self-)organized, contributing to the understanding of cities and their evolution using increasingly available mobility geographic information. [ABSTRACT FROM AUTHOR]

Recent studies have made it clear that Iran has too many road traffic injuries (RTI). This paper explains the reasons for high traffic injury rates and points to solutions. It also provides detailed data on the burden of traffic injury in Iran in 2005. Traffic injury rates have rapidly risen out of control because for a variety of possible reasons such as increasing number of non-standard cars and motorcycles, low gas price, decreasing ratio of travels via public transportation than with private vehicles, and problems with safety design. Besides a high need for a system safety approach, Iran needs to deal with the problem of producing a high number of cars and motorcycles. Providing safe mobility for the people of Iran needs to be a top priority of the government. [ABSTRACT FROM AUTHOR]

BACKGROUND: Traffic-related air pollution has been associated with adverse health outcomes, and the immune system may be a biologic mediator of health effects. OBJECTIVES: We analyzed associations between living near major roads and immune status as measured by five immune assays. We hypothesized that living near a freeway, arterial, or truck route would be associated with increased inflammation and decreased immune function. METHODS: We used a geographic information system (GIS) to determine residential proximity to major roads among 115 postmenopausal, overweight women in the greater Seattle, Washington (USA), area whose immunity was assessed at the baseline visit of an exercise intervention trial. We evaluated three inflammatory markers (C-reactive protein, serum amyloid A, and interleukin-6) and two functional assays of cellular immunity [natural killer (NK) cell cytotoxicity and T-lymphocyte proliferation]. RESULTS: Women living within 150 m of arterial roads had 21% lower NK cytotoxicity compared with women who lived farther from an arterial [mean cytotoxicity, 19.5%; 95% confidence interval (CI), 15.6--23.5%; vs. mean cytotoxicity, 24.8%; 95% CI, 22.0--27.5%], after adjustment for both individual-level and census tract--level demographic characteristics. This association was limited to women who reported exercising near traffic. Fewer women lived near freeways and truck routes. Markers of inflammation and lymphocyte proliferation did not consistently differ according to proximity to major roads. CONCLUSIONS: If the observed association between residential proximity to traffic and decreased NK cytotoxicity is confirmed in other populations, our results may have implications for local land use policy. [ABSTRACT FROM AUTHOR]

Within the framework of Biham–Middleton–Levine traffic model with origin–destination trips, we study the evacuation processes of cars in cities. Cars move from the origin to the destination points. A driver which reaches its destination disappears with rate β. It is found that the evacuation processes are greatly influenced by the origin–destination distance probability distribution. We also find that the evacuation time of drivers diverges in the form of a power law τ ∝ β-ν, with ν = 1. [ABSTRACT FROM AUTHOR]

Growing concern about health and climate impacts and future tightening of air quality standards will make accurate impact assessment of (new) road infrastructure and policy development increasingly important. As a consequence, there is a need for more accurate (complex) emission models at the local scale. In the development of complex emission models it is important, however, to strike a balance between the level of modelling detail and prediction accuracy and to validate emission modelling results. This paper discusses a number of existing and emerging road traffic emission models in Europe. Particular focus is on a new modeling approach employing statistical techniques and based on a large emissions and fuel consumption tests database. It appears valuable and feasible to develop an Australian and New Zealand version of this model. This would add to the diversity of current emission modelling in Australia and New Zealand. As a next step, an optimum and agreed-upon modelling framework should be established, based on additional research, model comparison and validation. [ABSTRACT FROM AUTHOR]

Stability analysis of a single-lane microscopic car-following model is studied analytically from the perspective of delayed reactions of human drivers. In the literature, the delayed reactions of the drivers are modeled with discrete delays, which assume that drivers make their control decisions based on the stimuli they receive from a point of time in the history. We improve this model by introducing a distribution of delays, which assumes that the control actions are based on information distributed over an interval of time in history. Such an assumption is more realistic, as it takes into consideration the memory capabilities of the drivers and the inevitable heterogeneity of their delay times. We calculate exact stability regions in the parameter space of some realistic delay distributions. Case studies are provided demonstrating the application of the results. [ABSTRACT FROM AUTHOR]

In this paper, we propose a simple betweenness-driven model to capture the dynamics of traffic routing choice behaviors. By comparing with two other models (degree-driven and cost-driven), it is shown that the cost-driven routing strategy is more complex and sensitive to traffic congestion. Another result indicates that the load distributions are determined by the connectivity distribution and route choice behaviors of the traffic network. The model thus provides useful insight for the design of traffic networks. [ABSTRACT FROM AUTHOR]

Abstract: A new public conveyance model applicable to buses and trains is proposed in this paper by using stochastic cellular automaton. We have found the optimal density of vehicles, at which the average velocity becomes maximum, significantly depends on the number of stops and passengers behavior of getting on a vehicle at stops. The efficiency of the hail-and-ride system is also discussed by comparing the different behavior of passengers. Moreover, we have found that a big cluster of vehicles is divided into small clusters, by incorporating information of the number of vehicles between successive stops. [Copyright &y& Elsevier]

This article investigates (determinants of) travelers' needs concerning travel information, based on a web survey filled out by 488 individuals. It aims at narrowing down three identified gaps in empirical literature available on this topic. Firstly, instead of focusing on the influence of manifest factors on travelers' need for information, such as trip circumstances, this article addresses the role of behavioral factors, in specific travelers' perception of their own knowledge levels. Secondly, instead of focusing only on currently available types of travel information, such as information on travel time and cost, this article also discusses travelers' need for a number of more advanced types of travel information, such as personalized early warning functions. Thirdly, instead of focusing on travel by car or transit, this study considers travelers by both modes simultaneously, and makes comparisons between these two groups. A number of new empirical findings are reported. [ABSTRACT FROM AUTHOR]

Atmospheric emission inventories are important tools for studying air quality and to set up possible remediation plans in areas characterised by nonattainment of the limit values established by legislation. In industrialised countries a considerable fraction of the emissions is due to road traffic, in particular in urban areas. For this reason emissions from road traffic must be estimated as accurately as possible, a task that can be performed, for the European vehicle fleet, thanks to the availability of the COPERT III methodology. This methodology is powerful and accurate, even if its algorithms can be difficult to apply in a regional emission inventory; moreover the collection of the necessary input data requires a lot of resources and time. This paper describes the road traffic emission inventory estimated for Region Sardinia (Italy) with a bottom-up approach. The estimation has been done by means of a software tool (EMITRA—EMIssions from road TRAnsport) which implements the COPERT III methodology. The resulting emission inventory has been compared against another emission inventory for Sardinia and against emission inventories for other Italian regions, to evaluate its reliability. [Copyright &y& Elsevier]

Abstract: Residents perception of road traffic noise loudness in relation to the measured noise indices close to their dwellings was studied. Percentile distributions of five loudness categories as a function of the Day–Night noise index L DN were obtained. Hearing sensitivity was considered as a factor in loudness perception. In addition, the prevalence of people’s perception of traffic noise in the “Extremely Loud” loudness category was compared with percentage of people stating that they were “Highly Annoyed” by noise. It is concluded that hearing sensitivity for noise is one of the variables that explains the loudness classification difference in different L DN index ranges and that the percentages of people “Highly Annoyed” by noise are slightly higher than the percentages obtained in the “Extremely Loud” category of loudness perception. [Copyright &y& Elsevier]