Search

Problem definition: Early research has documented significant growth in ride-hailing services worldwide and allied benefits. However, growing evidence of their negative externalities is leading to significant policy scrutiny. Despite demonstrated socioeconomic benefits and consumer surplus worth billions of dollars, cities are choosing to curb these services in a bid to mitigate first order urban mobility problems. Existing studies on the congestion effects of ride-hailing are limited, report mixed evidence, and exclusively focus on the United States, where the supply consists primarily of part-time drivers. Methodology/results: We study how the absence of ride-hailing services affects congestion levels in three major cities in India, a market where most ride-hailing drivers participate full time. Using rich real-time traffic and route trajectory data from Google Maps, we show that in, all three cities, periods of ride-hailing unavailability due to driver strikes see a discernible drop in travel time. The effects are largest for the most congested regions during the busiest hours, which see 10.1%–14.8% reduction in travel times. Additionally, we provide suggestive evidence for some of the mechanisms behind the observed effects, including deadheading elimination, substitution with public transit, and opening up of shorter alternative routes. Managerial implications: These results suggest that despite their paltry modal share, ride-hailing vehicles are substituting more sustainable means of transport and are contributing significantly to congestion in the cities studied. The reported effect sizes quantify the maximum travel time gains that can be expected on curbing them. Funding: This work was supported by the Srini Raju Center for Information Technology and the Networked Economy at Indian School of Business. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1158. [ABSTRACT FROM AUTHOR]

Copyright of Revista Fatec Zona Sul (REFAS) is the property of Revista Fatec Zona Sul (REFAS) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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 significant advancements in intelligent transportation systems (ITS) have contributed to the increased development in traffic modeling. These advancements include prediction and simulation models that are used to simulate and predict traffic behaviors on highway roads and urban networks. These models are capable of precise modeling of the current traffic status and accurate predictions of the future status based on varying traffic conditions. However, selecting the appropriate traffic model for a specific environmental setting is challenging and expensive due to the different requirements that need to be considered, such as accuracy, performance, and efficiency. In this research, we present a comprehensive literature review of the research related to traffic prediction and simulation models. We start by highlighting the challenges in the long-term and short-term prediction of traffic modeling. Then, we review the most common nonparametric prediction models. Lastly, we look into the existing literature on traffic simulation tools and traffic simulation algorithms. We summarize the available traffic models, define the required parameters, and discuss the limitations of each model. We hope that this survey serves as a useful resource for traffic management engineers, researchers, and practitioners in this domain. [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]

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]

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]

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]

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]

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]

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]

The article is focused on dynamic driving in road transport. Current systems on the market are referred to as dynamic but have their limitations. Traffic management is an important aspect to ensure the proper functioning and safety of transport as an element of critical infrastructure. Ensuring the prevention of possible threats can minimize the possibility of threatening other elements of critical infrastructure. The proposed method deals with dynamic driving in road transport. Dynamically controlled traffic lights should ensure greater smoothness, safety and reduce the number of harmful substances emitting vehicles. [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]

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]

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]

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]

In this research, we analysed the impact of road traffic on air quality at the Cluj-Napoca border. For this purpose, the road traffic on the North ring road was monitored: Floreşti (Pădurii Street) - Cluj-Napoca (Donath Street) at the same time with the measurement of the particulate matter PM10. The daily average road traffic was determined according to 'AND 584-2002 normative: "Normative for the calculation of the traffic for the design of the roads from the point of view of the carrying capacity and traffic capacity". For the measurement of particulate matter concentrations PM10, two Dusttrak DRX Aerosol Monitor Model 8533 instruments were used, capable of simultaneously providing mass concentration data for all particle size fractions over a wide range of concentrations (0.001-150 mg/m3) in real time. These were located in two different areas of the ring road: the first instrument was about 20 m from the road on Donath Street in Cluj-Napoca, and the second at a distance of about 80 meters from the road, outside the city. [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]

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]

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]

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]

Size resolved emission factors for submicrometer particles related to trace gases have been obtained from measurement data at a suburban road side, with a traffic intensity of 18,000 vehicles per day. Number of particles with diameter 10–368 nm, trace gases (NO, NOx,O3 and SO2), traffic and meteorology parameters were measured outside of Göteborg, Sweden. Size distributions of small particles at the site are presented and their relation to meteorological and traffic related variables was evaluated. Wind speed correlated negatively with 10–368 nm particles and temperature correlated negatively with the smaller particles (10–60 nm). Nitric oxide was shown to be a better tracer for traffic related ultrafine particles, than traffic intensity itself.The calculated emission factor, with errors at 95% confidence level, for particles in the range 10–368 nm is presented in relation to nitrogen oxides. The emission factors were 268±60 and 176±37 particles cm-3 per ppb NO and NOx, respectively. The particle emission factors for 10–100, 10–50, 50–170 and 170–368 nm were 260±70, 228±52, 41±11 and <1 particle cm-3 per ppb NO, respectively. The size distribution of the emissions is given by number of particles normalised by the width of the size bin, i.e. in units of dNd log Dp-1 ppb-1. The maximum normalised emission factor was 450 cm-3 per ppb NO for 20 nm particles. The shape of the size distribution of emissions revealed one sharp peak at 20 nm, with a small shoulder at 70 nm. [Copyright &y& Elsevier]

The primary purpose of the speed limit system is to enforce reasonable and safe speed. To reduce secondary problems such as accidents and queuing, Variable Speed Limits (VSL) has been suggested. In this paper VSL is used to better safety and traffic parameters. Traffic parameters including speed, queue length and stopping time have been pondering. For VLS, an optimization decision tree algorithm with the function of microscopic simulation was used. The results in case of sub saturated, saturated and supersaturated at a bottleneck are examined and compared with the Allaby logic tree. The results show that the proposed decision tree shows an improved performance in terms of safety and comfort along the highway. The VSL pilot project is part of the Road Safety Improvement Program included in Iran's road safety action plan that is in the research process in the BHRC Research Institute, Road and Housing & Urban Development Research that is planned for next 10-year Transportation safety view Plan. [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]

This study attempts to make use of traffic behaviour on the aggregate level to estimate congestion on urban arterial and sub-arterial roads of a city exhibiting heterogeneous traffic conditions by breaking the route into independent segments and approximating the origin-destination based traffic flow behaviour of the segments. The expected travel time in making a trip is modelled against sectional traffic characteristics (flow and speed) at origin and destination points of road segments, and roadway and segment traffic characteristics such as diversion routes are also tried in accounting for travel time. Predicted travel time is then used along with free flow time to determine the state of congestion on the segments using a congestion index (CI). A development of this kind may help in understanding traffic and congestion behaviour practically using easily accessible inputs, limited only to the nodes, and help in improving road network planning and management. [ABSTRACT FROM AUTHOR]

Abstract: Large scale road traffic is a complex system that could be modelled with a multilevel approach. Most of the multilevel models from the literature have fixed a priori the two levels of detail (micro-meso, micro-macro, meso-macro). This paper has two goals: it presents the state of the art related to large scale traffic models, and it gives the main research direction to create a novel multilevel model that support dynamic selection of the level during the simulation. Our proposal is based on an organizational modelling approach and the use of the concept of holon (agent composed of agents). [ABSTRACT FROM AUTHOR]

This paper presents a method for defining and improving the traffic conditions in a set of cross section in the city of Cluj-Napoca, using microsimulation software for the traffic. Simulation models are designed to mimic the behavior of traffic in a time and space transport system in order to predict the system's performance. A simulation model studies a real world system, considering mathematical and logical concepts associated with the system operation and analyzes them using complex computer programming. Each simulation model presents a set of advantages such as: it can be more accurate than an analytical approach, it is able to test new conditions, it can improve the perspective concerning the significance of variables and of the way these variables interact. A case study is presented, using a set of three street intersections. In these intersections measurements of traffic during morning peak hours were performed. The measurements were acquired both manually and automatically, using time slots of 15 minutes each. The collected data was also used for model calibration. With the help of microsimulation software and a well-balanced model, information regarding traffic conditions can be found, resulting in analyses of the traffic evolutions. Some traffic conditions issues are identified and a set of improvement suggestions are presented. The measures proposed in this paper need to be tested and further optimized also by means of microsimulation, before being implemented, in order to obtain satisfactory results. The area under investigation exhibits quite large delays in traffic, in present-day conditions. This means smaller displacement speed, and, implicitly, more toxic emissions, that make the system be farther from the idea of sustainable transportation. [ABSTRACT FROM AUTHOR]

The continuous increase of vehicle fleet along with the development of road transport networks has associated a wide range of externalities. Main types of externalities refer to environmental impact, expressed as Greenhouse Gas Emissions, raw materials depletion, energy and fuel consumption or disruption of ecosystem equilibrium, social impact, expressed as quality of people life, human health and economic impact, expressed as economic growth. The current development of road transport promotes a growing interest for sustainable and eco-friendly transportation worldwide. In the context of a wide range of externalities, the present paper aims to emphasize the ecological impact associated with road transportation traffic, customized for specific road networks from North-East Region of Romania and expressed in atmospheric polluting emissions. In correlation with traffic pollution, the current research highlights the exponential increase of the greenhouse gas effect and fuel consumption, providing specific strategies, necessary for the improvement of road network sustainability, based on the results of the undertaken study. The analysis of the environmental impact implies a quantitative assessment of energy consumption and CO2e emissions produced by road traffic. In this respect has been carried out the evaluation of atmospheric pollution produced by the traffic recorded in 2010, using the annual daily average traffic for the year in question. Based on the coefficients of traffic evolution it has been forecasted the pollution level for 2015, 2020 and 2030. The calculations have been performed based on the current configuration of the vehicle fleet from NE Region of Romania, investigated for two types of roads, namely a road with an optimum pavement condition in comparison with a road pavement with distresses. For the first case study, was considered a road pavement suitable rehabilitated, by intervention works of maintenance and rehabilitation, applied to an optimum moment. This case study presents the ideal situation, from traffic sustainability point of view, since the vehicles speed isn’t influenced by the pavement condition, the road level of service is free flow. The evaluation performed for this particular case study showed that, for the current vehicle fleet and average vehicles speed, the environmental impact expressed in pollutant emissions registers the lowest values. For the second case study, the evaluation focused on the ecological impact associated with the road traffic, based on the current road network pavement condition. Considering the traffic congestion and pollution increase due to road distresses, the studies in the present paper were focused on the pollution level, specific to County of Iaşi road network. For a proper analysis of pollutant emissions, associated with road transport traffic, has been used European Environment Agency (EEA) computer software COPERT 4. The software was developed to perform evaluations of air pollutant and greenhouse gas emissions specific to road transport, the deliverables being consistent with the latest regulations in the field. The research objective was to deliver intervention strategies and scenarios, related with the high increase in vehicles fleet, usage of alternative fuels and CO2e emissions level, towards sustainable road transportation. [ABSTRACT FROM AUTHOR]

Increasing the intensity of transport traffic, changing in restructuring and high-speed modes of transport flows more stringent requirements for controls and traffic management impose to ensure the necessary level of efficiency and safety of the transport traffic. To resolve this problem, it is necessary to build road network optimal in length, density and on transport performance indicators. Aim: The aim of the study is to evaluate the workload and analysis of capacity of the road network of modern regional center. Materials and Methods: All studies and calculations in paper, the authors conducted on the example of the road network of the Primorsky district of Odessa (Ukraine). Few streets that are transit arteries of the historic center were chosen to assess the road network capacity. On these streets the movement to the main passenger and transport creating unit - Railway Station is happening. To assess the capacity of the considered road network the methods of field observations were used, because they are based on direct measurements of traffic characteristics in different parts of the road network. Results: The study gave an objective picture of important correspondences. An assessment of degree of loading the considered road network was made; for that the capacity of multilane roadway was calculated. Analysis of the data showed that the state of traffic in the study area is densely saturated. It was made the recommendation for improvement of traffic of modern regional center. [ABSTRACT FROM AUTHOR]

This article describes the methods of mathematical modeling and simulation of processes of local interaction in transport systems. Described transport flow models, developed by the author, based on extension of the microscopic Treiber's model and on the queuing theory. These models cover more details of behavior of flow participants on signal-controlled crossroads. modification. The article describes a model of traffic on the ring road. [ABSTRACT FROM AUTHOR]

Case study on adaptive traffic lights solution implementation at the intersection of Routh Bihar with Street Starlings. Description of the chosen solution for traffic lights at the current intersection between Routh Bihar with Street Starlings. [ABSTRACT FROM AUTHOR]

Microblogs like Twitter 1 are sources for a lot of useful information. But these information are unstructured. To automatically process it, these information have to be extracted with the help of natural language processing techniques. Corresponding systems for information extraction have to be trained and validated with manual annotated data. This paper presents an approach for the cooperative creation of annotated corpora for training and validation of information extraction systems supported by statistical analyses. 1 https://twitter.com/ [ABSTRACT FROM AUTHOR]

Air quality information such as the concentration of PM2.5 is of great significance for human health and city management. It affects the way of traveling, urban planning, government policies and so on. However, in major cities there is typically only a limited number of air quality monitoring stations. In the meantime, air quality varies in the urban areas and there can be large differences, even between closely neighboring regions. In this paper, a random forest approach for predicting air quality (RAQ) is proposed for urban sensing systems. The data generated by urban sensing includes meteorology data, road information, real-time traffic status and point of interest (POI) distribution. The random forest algorithm is exploited for data training and prediction. The performance of RAQ is evaluated with real city data. Compared with three other algorithms, this approach achieves better prediction precision. Exciting results are observed from the experiments that the air quality can be inferred with amazingly high accuracy from the data which are obtained from urban sensing. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Many transportation agencies such as Departments of Transportation in the USA are using Asset Management Optimization models to plan their maintenance and rehabilitation projects. Currently available commercial solutions are often focused only on global asset performance/money spent aspect of the problem and do not take into account the benefits of synergy between the projects, i.e. the benefits of scheduling nearby projects in the same year in order to take advantage of fixed cost savings due to economies of scale. At the strategic level adding variables and constraints to account for these economies of scale are not practical since such models often already have millions of variables and constraints and adding anything new could reduce the performance significantly. Looking at the problem from a tactical perspective however it is possible to run an analysis on the global work plan that can improve cost savings from economies of scale with subtle changes to the originally analyzed performance. For example, in case of pavement management it is a common result to see gaps in the produced theoretical work plans along a route that would result in increased mobilizations to accomplish the plan. This results in extra costs both for the agency and road user. A common result might suggest fixing miles 1-8 and 9-10 in the one year and then fixing mile 8-9 in a subsequent year. Even if this solution provided the best performance for the money it is impractical to actually do it, it would make much more sense to simply fix entire 10 mile segment while achieving almost the same performance and saving mobilization costs which can be significant cost savings. A project coordination optimization model would analyze economies of scale problems such as these while also considering network constraints such as limited budgets and resources available within the administrative unit managing the work plan. This paper proposes an optimization model, referred to as Project Coordination model throughout the paper, that would attempt to improve an already created work plan by slightly changing the project schedules such that the adjusted plan would achieve similar performance while providing a more practical solution by maximizing economies of scale with reduced delivery and mobilization costs. The results of applying proposed model to one illustrative example and two real life work plans are presented and thoroughly analyzed. [ABSTRACT FROM AUTHOR]

Copyright of Baltic Journal of Road & Bridge Engineering (Baltic Journal of Road & Bridge Engineering) is the property of Baltic Journal of Road & Bridge Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)