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The physiological response in moss samples is often used as an early warning signal of environmental stress caused by air pollution. This study aimed to test the efficiency of photosynthesis-related parameters in Leucobryum aduncum moss bags as bioindicators of environmental stress related to road traffic. The moss samples were collected and prepared in a relatively unpolluted area and then transplanted at 7 sites in forested, rural, and urban areas. The moss samples were picked up after being exposed for 1 and 3 months for physiological measurements. The results showed that the average values of all physiological parameters were highest in the forested area and lowest in the urban area. All parameters at most roadside (R site) sites were lower or significantly lower than those at the site away from the road (A site). This was particularly true for the 3-month exposure period, suggesting that the length of exposure should be longer than 1 month, but exposure up to 3 months could fully damage the photosystem II and destroy the moss bags. The vitality index also clearly indicated that the moss bags were more affected in the urban area, at the R sites, and at the 3-month exposure. Among six parameters, the most susceptible parameter was the chlorophyll fluorescence parameter, followed by the total carotenoids, chlorophyll a, total chlorophylls, chlorophyll b, and chlorophyll a degradation (OD435/OD415). The moss bag technique used in this study did not negatively affect the studied physiological parameters, but a great elevation difference could affect the moss bag physiology. This study illustrated that the photosynthesis-related parameters of L. aduncum moss bags can be used as effective bioindicators of environmental stress caused by road traffic. This study is among the priority studies of moss bioindication of air pollution in Thailand and can pave the way for future studies.

Severe spatiotemporal heterogeneity of emissions sources and limited measurement networks have been hampering the monitoring and understanding of CO2 fluxes in large cities, a great concern in climate research as big cities are among the major sources of anthropogenic CO2 in the climate system. To understand the CO2 fluxes in Seoul, Korea, CO2 fluxes at eight surface energy balance sites, six urban (vegetation-area fraction < 15%) and two suburban (vegetation-area fraction > 60%), for 2017–2018 are analyzed and attributed to the local land-use and business types. The analyses show that the CO2 flux variations at the suburban sites are mainly driven by vegetation and that the CO2 flux differences between the urban and suburban sites originate from the differences in the vegetation-area fraction and anthropogenic CO2 emissions. For the CO2 fluxes at the urban sites; (1) vehicle traffic (traffic) and heating-fuel consumption (heating) contribute > 80% to the total, (2) vegetation effects are minimal, (3) the seasonal cycle is driven mainly by heating, (4) the contribution of heating is positively related to the building-area fraction, (5) the annual total is positively (negatively) correlated with the commercial-area (residential-area) fraction, and (6) the traffic at the commercial sites depend further on the main business types to induce distinct CO2 flux weekly cycles. This study shows that understanding and estimation of CO2 fluxes in large urban areas require careful site selections and analyses based on detailed consideration of the land-use and business types refined beyond the single representative land-use type widely-used in contemporary studies. [ABSTRACT FROM AUTHOR]

The impact of the piston wind caused by vehicle traffic on the temperature field distribution of the tunnel cannot be ignored, especially in spiral tunnels, where the temperature field distribution is more complicated than that in straight tunnels. Based on the world's longest highway spiral tunnel, this study explores the influence of traffic on the temperature fields of spiral and straight tunnels, and proposes a new design method for laying length of insulation layer. The results show that traffic has a significant effect on the temperature field distribution in the tunnel. The influence degree of different traffic elements decreases in the following order: average vehicle speed > daily traffic > morning rush hour > evening rush hour. The temperature field distribution of spiral tunnels is asymmetry on the left and right compared with straight tunnels, while the influence degree of traffic on the outside of spiral tunnels is similar to that of straight tunnels. Due to the difference of wind direction and traffic direction at different tunnel openings, an asymmetric insulation layer laying method is proposed. It is suggested that the lengths of the insulation layers of the Jinjiazhuang Tunnel should be 1200 m for the right tunnel inlet, 700 m for the right tunnel outlet, 700 m for the left tunnel inlet, and 1400 m for the left tunnel outlet.

To investigate the vibrational impact of vehicular traffic on the ancient Qiantang River seawall, on-site measurements of the seawall’s pulsation and forced vibrations under different vehicle speeds and axle loads were conducted. The acquired data were analyzed in the time domain, frequency domain, and 1/3 octave bands, revealing the time-frequency vibrational characteristics of the ancient seawall structure. The results indicate that the characteristic frequencies of the ancient seawall are 3 Hz and 10 Hz, with the primary frequency band of the structural vibrations induced by vehicular traffic ranging from 0 to 30 Hz. Vehicle traffic primarily caused vertical vibrations in the seawall structure, with along-dike horizontal vibrations being significantly higher than cross-dike vibrations. Based on the measurement results, an empirical relationship between the peak vibration velocity of the ancient seawall and variations in vehicle speed and axle load was established. It was found that, compared to axle load, increased vehicle speed had a more pronounced amplification effect on the structural vibrations of the ancient seawall. To ensure the vibrational safety of the ancient seawall relics, maximum vehicle speeds for different loading conditions of tri-axle trucks were provided based on vibration limits: for an axle load of 10 t, speeds should be below 34 km/h; for 11.52 t, below 24 km/h; for 13.04 t, below 20 km/h; and for 14.56 t, below 15 km/h.

The problems of vehicular traffic on the beaches are increasingly severe since the influx of visitors during the high season increases coastal erosion. This study aimed to analyze the morphological changes occurring on the beach in two sectors of Area 2 within the Pehuén Co-Monte Hermoso Provincial Geological, Archaeological, and Paleontological Reserve (Buenos Aires, Argentina). To compare and assess the beach's behavior in response to the prohibition of vehicular traffic in one sector of Area 2, beach profiles were conducted seasonally during the periods of 2008-2009 (prior to closure) and 2022-2023. Additionally, the geomorphology, slope, volumes of the beach profiles, as well as the spatiotemporal movement of the frontal dune, were studied. The results showed that the average slope increased by 0.4° in profile inclination. It was also observed in the closed sector (where traffic was restricted) an expansion of the frontal dune area from 24 hectares to 29 hectares and a more significant accumulation of sediments (295.4 cubic meters) on the beach over the last 14 years. [ABSTRACT FROM AUTHOR]

Traffic prediction is a topic of increasing importance for research and applications in the domain of routing and navigation. Unfortunately, open data are rarely available for this purpose. To overcome this, the authors explored the possibility of using geo-tagged social media data (Twitter), land-use and land-cover point of interest data (from OpenStreetMap) and an adapted betweenness centrality measure as feature spaces to predict the traffic congestion of eleven world cities. The presented framework and workflow are termed as SocialMedia2Traffic. Traffic congestion was predicted at four tile spatial resolutions and compared with Uber Movement data. The overall precision of the forecast for highly traffic-congested regions was approximately 81%. Different data processing steps including ways to aggregate data points, different proxies and machine learning approaches were compared. The lack of a universal definition on a global scale to classify road segments by speed bins into different traffic congestion classes has been identified to be a major limitation of the transferability of the framework. Overall, SocialMedia2Traffic further improves the usability of the tested feature space for traffic prediction. A further benefit is the agnostic nature of the social media platform's approach. [ABSTRACT FROM AUTHOR]

Abstract A cross-sectional study was carried out to estimate the prevalence of miscarriages in a population of 360 women distributed in areas exposer to higher and lower vehicle traffic air pollution on the Island of São Luís, MA, Brazil, and identify associated variables. Participants were interviewed and bivariate and multivariate logistic regressions were conducted. The overall miscarriage prevalence was of 15.83%, totaling 25.56% (n=180) in the higher exposure area and 6.11% (n=180) in the lower exposure area. Maternal alcohol consumption (OR=3.11), STIs during pregnancy (OR=2.74), living in a high-exposure area (OR=8.32), having suffered physical or psychological distress during pregnancy (OR=4.25) and repeated miscarriages (OR=39.11) were all associated to the miscarriage outcome. The findings reported herein thus indicate potential vehicle traffic air pollution contribution as a risk factor in the etiology of miscarriages.

Most of the cities at the old urban fabric heritage area featured with specific characteristics. Sulaymaniyah city has such an old and heritage area. The fabric features similar specifications to those of the most cities of the Islamic world, in terms of its streets, alleys and lanes. Since roads and alleys where forming a nested organic shape served the urban movement in full conformity which meets the complete walkability requirements through alleys and streets. The change and development of the transport systems and then the penetration of these modern systems in old alleys which are not designed and not suitable for such systems have made distraction in general traffic and the walkability in particular. This research tries to focus on this point by studying the factors that affect walkabilty at the old city of Sulaymaniyah and looks at the impact of vehicular traffic on this possibility by examining a specific zone of the old city and comparing this with global criteria and standards used in wakability at such similar areas. To reach the goal of the impact of vehicular traffic on walkability at the traditional area of Sulaymaniyah, the research concluded that because of the nature of the alleys and streets of this area with specific privacy, the walkability is adversely affected.

Traffic prediction is a topic of increasing importance for research and applications in the domain of routing and navigation. Unfortunately, open data are rarely available for this purpose. To overcome this, the authors explored the possibility of using geo-tagged social media data (Twitter), land-use and land-cover point of interest data (from OpenStreetMap) and an adapted betweenness centrality measure as feature spaces to predict the traffic congestion of eleven world cities. The presented framework and workflow are termed as SocialMedia2Traffic. Traffic congestion was predicted at four tile spatial resolutions and compared with Uber Movement data. The overall precision of the forecast for highly traffic-congested regions was approximately 81%. Different data processing steps including ways to aggregate data points, different proxies and machine learning approaches were compared. The lack of a universal definition on a global scale to classify road segments by speed bins into different traffic congestion classes has been identified to be a major limitation of the transferability of the framework. Overall, SocialMedia2Traffic further improves the usability of the tested feature space for traffic prediction. A further benefit is the agnostic nature of the social media platform’s approach.

Intelligent traffic systems attempt to solve the problem of traffic congestion, which is one of the most important environmental and economic issues of urban life. In this study, we approach this problem via prediction of traffic status using past average traveler speed (ATS). Five different algorithms are proposed for predicting the traffic status. They are applied to real data provided by the Traffic Control Center of Istanbul Metropolitan Municipality. Algorithm 1 predicts future ATS on a highway section based on the past speed information obtained from the same road section. The other proposed algorithms, Algorithms 2 through 5, predict the traffic status as fluent, moderately congested, or congested, again using past traffic state information for the same road segment. Here, traffic states are assigned according to predetermined intervals of ATS values. In the proposed algorithms, ATS values belonging to past five consecutive 10-minute time intervals are used as input data. Performances of the proposed algorithms are evaluated in terms of root mean square error (RMSE), sample accuracy, balanced accuracy, and processing time. Although the proposed algorithms are relatively simple and require only past speed values, they provide fairly reliable results with noticeably low prediction errors.

In different parts of the world, it is verified that green areas provide an improvement in the quality and well-being of the population in the environmental and psychological aspects. In this study, the micronucleus test is performed in Tradescantia pallida (Rose) D.R. Hunt var. purpurea (TRAD-MCN) to detect the mutagenic potential of atmospheric gases in different situations of vehicular flow and urban green areas. Following the protocols for TRAD-MCN, the results obtained confirm the positive correlation between the intensity of vehicle traffic and the frequency of micronuclei. However, in regions with green areas, the results obtained with TRAD-MCN are inferior even with intense vehicular flow. The period of high temperatures and low relative humidity can potentiate the action of stressors on plant species used as a bioindicator. Because of the results found in this study, we can infer that green areas reduce the effects of polluting gases. We emphasize here the importance of preserving or creating parks and reserves in an urban environment to improve air quality and consequently the health of the population. [ABSTRACT FROM AUTHOR]

The development of the COVID-19 pandemic and the related lockdown had a major impact on vehicle traffic in cities. Based on available data from the selected city of Rzeszow, Poland, it was decided to assess changes in vehicle traffic and the impact of these changes on roadside environmental pollution. As part of the research, data from the first half of 2020 regarding vehicle traffic on selected streets of the city and on the city’s inlet routes were analyzed. For the selected road sections, changes in hourly traffic volume in 2020, compared with 2019, were also determined. With data on traffic volume, an attempt was made to estimate the impact of changes in traffic volume on air pollution in the city. Research on air pollution from motor vehicles was focused on a selected section of a city road that was equipped with an automatic air pollution measurement station located very close to the road. Additionally, at the road intersection and in the vicinity of the measuring station, a sensor was installed in the roadway to count passing vehicles. A preliminary analysis of air pollution data revealed that factors such as wind speed and direction and outside temperature had a large impact on measurement results. To eliminate the influence of these factors and to obtain data concerning only contamination originating from motor vehicles traveling along the road, an appropriate mathematical model of the traffic flow–roadside environment system was built. This model was designed to determine the air pollution in the vicinity of the road generated by traffic flow. The constructed model was verified, and the conditions for its use were determined in order to study the impact of traffic and roadside environment on the level of air pollution from harmful exhaust substances. It was shown that at certain times of the day, especially at low temperatures, other sources of harmful emissions related to home heating play a major role in air pollution in the city.

Highlights • Novel correlation between pressure losses and traffic conditions in road tunnel. • Correlation was obtained by means of CFD model validated on experimental data. • Maximum error of the correlation is about 3% with respect to numerical values. • Friction total factor includes both the roughness and the aerodynamic effects. Abstract The main aim of the present work is to provide a novel correlation between different traffic jam conditions (Filling Traffic Tunnel) in road tunnel and pressure losses, in order to calculate the thrust required to the jet fan to induce the needed ventilation. The correlation refers to a longitudinal ventilation system of impulsive fans placed in a road tunnel with a rectangular cross section. The data necessary to build the novel correlation here proposed were obtained by means of 3-D model that was validated experimentally in previous studies. To evaluate the influence on required ventilation thrust, several traffic jam conditions and different average air velocities were considered. The proposed correlation provides pressure losses as function of FTT and average air velocity in the tunnel. The pressure losses were evaluated as difference between the thrust required by the ventilation system in empty tunnel conditions and the thrust required in traffic jam condition. The mean percentage error of the novel correlation here proposed is about of 3% respect to CFD simulation results. Furthermore, a friction factor for different FTT was provided. It allows to evaluate the pressure losses due to the traffic jam as distributed ones with an error value about of 3%. [ABSTRACT FROM AUTHOR]

We present an updated analysis of the size and demographic composition of the United States (U.S.) population living near high traffic volume roadways where the risk of negative health outcomes from traffic-related air pollution exposure is elevated using traffic data from 2018 and 2020 census data. We also evaluate disparities in traffic exposure by race, ethnicity, and income using refined equity analysis methods and break down our analysis by light-, medium-, and heavy-duty vehicle traffic. We find that 24 % of the U.S. population now lives near high-volume roadways, a larger share than 10 years ago. We also find statistically significant associations between higher levels of traffic exposure and greater proportions of people of color and lower household incomes in 89 % of U.S. counties. The increasing size of the near-roadway population, persistent and widespread inequities, and rapidly growing truck traffic raise significant public health and environmental justice concerns. [ABSTRACT FROM AUTHOR]

Objectives: Spatial assessment of traffic noise pollution intensity will provide urban planners with approximate estimation of citizens exposure to impermissible sound levels. They could identify critical noise pollution areas wherein noise barriers should be embedded. The present study aims at using the Geographic Information System (GIS) to assess spatial changes in traffic noise pollution in Tehran, the capital of Iran, and the largest city in the Middle East. Material and Methods: For this purpose, while measuring equivalent sound levels at different time periods of a day and different days of a week in District 14 of Tehran, wherein there are highways and busy streets, the geographic coordination of the measurement points was recorded at the stations. The obtained results indicated that the equivalent sound level did not show a statistically significant difference between weekdays, and morning, afternoon and evening hours as well as time intervals of 10 min, 15 min and 30 min. Then, 91 stations were selected in the target area and equivalent sound level was measured for each station on 3 occasions of the morning (7:00–9:00 a.m.), afternoon (12.00–3:00 p.m.) and evening (5:00–8:00 p.m.) on Saturdays to Wednesdays. Results: As the results suggest, the maximum equivalent sound level (Leq) was reported from Basij Highway, which is a very important connecting thoroughfare in the district, and was equal to 84.2 dB(A), while the minimum equivalent sound level (Leq), measured in the Fajr Hospital, was equal to 59.9 dB(A). Conclusions: The average equivalent sound level was higher than the national standard limit at all stations. The use of sound walls in Highways Basij and Mahallati as well as widening the Streets 17th Shahrivar, Pirouzi and Khavaran, benchmarked on a map, were recommended as the most effective mitigation measures. Additionally, the research findings confirm the outstanding applicability of the Geographic Information System in handling noise pollution data towards depicting noise pollution intensity caused by traffic.

In this study, road dust samples from state roads D-100 and D-655 passing through the city of Düzce, Turkey were analyzed using ICP-MS to ascertain heavy metal pollution, and also to evaluate possible risks to human health. Some pollution indices such as enrichment factors (EFs), geo-accumulation index (Igeo) and integrated pollution index (IPI) were calculated to determine the pollution levels of metals. According to the mean EF values, Zn, Mo, and Pb exhibited significant enrichment, while enrichment of As, Cd, Sn, and Sb was very high. The Igeo values for Pb, Ba, Mo, Zn, Cu, Mn, and Cr indicated an extremely polluted environment whereas those for Sc, V, Fe, As, Cd, Sn, and Sb indicated moderate to strong pollution of the environment. The IPI values of Pb and Mo were also at extreme levels due to vehicle traffic related contamination along the roads. Analysis of the road dust matrix indicated the mixed effect of the fossil fuel combustion for residential heating and industrial activities within the studied area as well as traffic originated pollution. Cluster analysis revealed that sampling area has been influenced by mainly three pollution sources: (i) traffic and industrial activities, (ii) polluted soil due to accumulation, and (iii) fossil fuel combustion. According to human health risk assessment studies, a level lower than 1.0 has been determined to be a non-cancer health risk. However, a total hazard index level of 1.4 poses a significant non-cancer health risk for children. Fortunately, a total lifetime cancer risk value of 8.8 × 10−8 was found, and this is considered safe. [ABSTRACT FROM AUTHOR]

The road network plays an important role in the birth and evolution of town planning and structuring of the landscape. It presents unique and original dynamics that encompass both its status and uses. Whatever their reality in the field, stratigraphic sequences are poorly studied using geoarchaeological methods. To document the formation processes of these road networks, micromorphological analyses were undertaken on a street in a Roman secondary town, Sains-du-Nord, on a road in a Roman civitas capital , Metz Divodurum, and on a lane created in medieval times in Lieusaint. Analyses of the Sains-du-Nord street and the Paille-Maille (Metz) road revealed intense vehicle traffic where traffic-related repairs and traffic layers were differentiated. Analyses of the Lieusaint site, enabled specialists to characterize the processes and layers resulting from vehicle traffic. Pedofeatures linked to passage and traffic presented in this paper, can be used to identify such types of space in other case studies. Finally, results show that the use of thin sections of archaeological layers can reveal not only the surface history, but also the original characteristics of traffic circulation space. The microscopic sequences are presented here as descriptive models of formation processes. The monophasic model appears to be the result of ongoing maintenance attributable to the status or continued use of the street (Sains-du-Nord) or lane (Lieusaint). Polyphasic and polycyclic models reflect rhythmic use and allow reconstruction of traffic levels (Paille-Maille (Metz) road). [ABSTRACT FROM AUTHOR]

Land degradation due to compaction is a critical issue facing 21st century agriculture. Deep ripping is a popular solution to remediate compacted Western Australian soils. However, these soils are particularly susceptible to recompaction under vehicle traffic: reliable methods to detect and monitor compaction are therefore needed to inform remediation strategies. Cone penetrometer testing (CPT) is a popular method to detect compaction under vehicle traffic in a range of soil conditions. However, traditional CPT equipment is unsuitable for large-scale use due to its expense and bulk. Dynamic penetrometers circumvent this issue by being inexpensive and man-portable. Such devices have seen recent success in determining properties of soft geotechnical materials but little is known of their performance in ripped soils. This study evaluated the ability of the “PANDA 2” dynamic penetrometer to detect compaction in ripped soils after the passage of aMassey Ferguson four-tonne tractor, which was typical of vehicles used at the test site. Two test sites of contrasting soil types were identified which had previously been ripped and left fallow and untrafficked for several years. Penetration resistance was measured along a high-resolution grid prior to trafficking and after one and five vehicle passes and compared to results from trial pits. Laboratory testing also examined the device's accuracy at shallow depths under controlled conditions. Results showed that the PANDA 2 was able to detect significant changes in penetration resistance after trafficking. However, several limitations on the device's use when interpreting field data were identified. Based on the findings of this study, dynamic penetrometers are not recommended to monitor compaction in ripped soilsfor the weight of vehicle used here. However, the devices may be of use when examining the passage of heavier vehicles. [ABSTRACT FROM AUTHOR]

Recreational activities can be an important source of anthropogenic disturbance in intertidal benthic assemblages. On rocky shores, activities such as trampling, snorkeling and the handling of organisms may have a negative effect on benthic communities by modifying the abundance and distribution of key species. Here, we describe and quantify impacts due to recreational activities on benthic communities on a Patagonian rocky shore by investigating their resilience to two types of human disturbance: vehicle traffic and human trampling. To evaluate the effects of these activities, we carried out an observational study and assessed post-disturbance assemblage recovery. The rocky shores is most intensively visited during summer, and marked differences in the distribution and abundance of benthic species among disturbed and control plots were found after this season. The benthic community on the high intertidal was weakly impacted by disturbance generated due to vehicle traffic in summer (one vehicle on a single occasion, pulse disturbance); which did not affect the cover of dominant species. This suggests that the high intertidal community would be resistant to the passage of one vehicle on a single occasion. The effects of continuous trampling (press disturbance) were drastic and the community of the mid intertidal level did not recover before the next recreational season. Mid intertidal communities exposed to press disturbances require more than one tourist season of human inactivity to recover from anthropogenic effects, suggesting that resilience mechanisms in this community operate at broad timescales. Our findings highlight the need to establish and implement management actions that contemplate the nature of the disturbance and intertidal level to minimize habitat degradation due to human recreational activities. [ABSTRACT FROM AUTHOR]

Amphibians are considered to be the most threatened group of vertebrates. Among the multiple factors involved in their decline, habitat loss and alteration as a result of human activities is a major threat. At the individual level the effects of habitat alteration are potentially multiple, including a range of morphological and physiological responses. Analysing and understanding these responses is therefore a critical challenge for amphibian conservation. We examined the influence of intensive vehicle traffic (motorbikes and trucks on unpaved pathways) on the body size and condition and on the production of glucocorticoids (i.e. corticosterone) in the yellow-bellied toad Bombina variegata. In particular, we tested the hypothesis that intensive vehicle traffic has a negative influence on body size and body condition, and postulated that it also increases corticosterone production. Using morphometric data and saliva samples collected from four populations in France, we found that intensive vehicle traffic is associated with a decrease in body size and body condition in both males and females. Furthermore, our analysis revealed that corticosterone production was lower in both sexes in populations experiencing intensive vehicle traffic. We suggest that measures should be applied to reduce vehicle traffic intensity on unpaved pathways during toad breeding activity. This is critical for B. variegata, for which man-made ruts and residual puddles could mitigate the loss of natural habitats. [ABSTRACT FROM AUTHOR]

This paper shows the application of the classic technique of digital signal processing (DSP), the cross-correlation, used for the detection of acoustic signatures of road traffic in Cali city, Colombia. Future goal is to build a detection software that through real time measures allows us estimate the levels of acoustic pollution in the city by using simulation models of road traffic, in the framework of environmentally-friendly smart cities. Final results of the experimental tests showed an accuracy of 71.43% for specific vehicle detection.

Diferentes estrategias para el control del tráfico urbano se han presentado a lo largo del tiempo. Este artículo presenta el diseño de un modelo de tráfico vehicular, el cual examina el tráfico existente en una vía a través de una serie de semáforos. A partir de este modelo se sincronizan los tiempos de duración y de desfase de los semáforos, utilizando para ello el Sistema de Inferencia Difusa Basado en Redes Adaptativas (ANFIS). El modelo es simulado y los resultados se evalúan a nivel macroscópico con el modelo de tiempos fijos, que funciona actualmente en Bogotá-Colombia.Different strategies for urban traffic control have been presented over time. This paper presents the design of a vehicular traffic model, examining the existing traffic through a serie of traffic lights on a road. From this model the times of duration and phase of the traffic lights are synchronized, using the Adaptive Network Based Fuzzy Inference Systems (ANFIS). The model is simulated and the results are evaluated at macroscopic level with the fixed time model, currently operating in Bogota-Colombia.

One of the most recently developed wireless technologies is Radio Tomographic Imaging (RTI). RTI employs a wireless sensor network that produces images of the change in the electromagnetic field of a monitored area using Received Signal Strength (RSS) measurements. This allows the tracking of devicefree objects such as humans and cars. This paper is the first to propose and validate a simulation model that simulates RSS measurements for arbitrary RTI networks, based on the ZigBee communication protocol. The simulation model allows the specification of an RTI network from the ground up, including node positions, network size and geometry and RSS measurement processing. Furthermore, this paper demonstrates the implementation of the simulation model to an enhancement of a recently proposed RTI system, which acts as a roadside surveillance system. The enhancement includes three newly proposed techniques, namely a new weight matrix calculation method, a new node spacing setup and a new vehicle detection method. The simulation results indicate that it is possible to detect both one or two family sized cars simultaneously. Using techniques that reduce RSS variance due to multipath effects and the newly proposed methods, simulated vehicle detection performance is demonstrated to be between 95% and 100%. [ABSTRACT FROM AUTHOR]

This paper presents the structure of a new system model for traffic inspection in Brazil. It shows the evolution of technological developments in order to help vehicles monitoring, and one of the approachs is the highway traffic monitoring. It was identified that this approach brings inconvenience for the society, like slow local traffic, complicating for the Traffic Agency, to accurately identify the cases that requires a traffic agent intervention. In this context, the project aims this market by optimizing agents' work, providing more effective local operations, improving accuracy on direct supervising to vehicles and providing a better life quality to citizens. In short words, it presents a solution to support traffic departments, regarding a direct approach, identification which vehicle should be inspected, type of inspection to be done, information of violations, resulting in improvement in the impact of vehicle traffic flow where the operation is done. Consequently, strategic decision-making can be done based with more accuracy. To build this solution, it is being applied the Rational Unified Process to the development of the software that integrates image capture with an IP Camera with embedded OCR. [ABSTRACT FROM AUTHOR]

Objectives: Spatial assessment of traffic noise pollution intensity will provide urban planners with approximate estimation of citizens exposure to impermissible sound levels. They could identify critical noise pollution areas wherein noise barriers should be embedded. The present study aims at using the Geographic Information System (GIS) to assess spatial changes in traffic noise pollution in Tehran, the capital of Iran, and the largest city in the Middle East. Material and Methods: For this purpose, while measuring equivalent sound levels at different time periods of a day and different days of a week in District 14 of Tehran, wherein there are highways and busy streets, the geographic coordination of the measurement points was recorded at the stations. The obtained results indicated that the equivalent sound level did not show a statistically significant difference between weekdays, and morning, afternoon and evening hours as well as time intervals of 10 min, 15 min and 30 min. Then, 91 stations were selected in the target area and equivalent sound level was measured for each station on 3 occasions of the morning (7:00-9:00 a.m.), afternoon (12.00-3:00 p.m.) and evening (5:00-8:00 p.m.) on Saturdays to Wednesdays. Results: As the results suggest, the maximum equivalent sound level (Leq) was reported from Basij Highway, which is a very important connecting thoroughfare in the district, and was equal to 84.2 dB(A), while the minimum equivalent sound level (Leq), measured in the Fajr Hospital, was equal to 59.9 dB(A). Conclusions: The average equivalent sound level was higher than the national standard limit at all stations. The use of sound walls in Highways Basij and Mahallati as well as widening the Streets 17th Shahrivar, Pirouzi and Khavaran, benchmarked on a map, were recommended as the most effective mitigation measures. Additionally, the research findings confirm the outstanding applicability of the Geographic Information System in handling noise pollution data towards depicting noise pollution intensity caused by traffic. [ABSTRACT FROM AUTHOR]

Different strategies for urban traffic control have been presented over time. This paper presents the design of a vehicular traffic model, examining the existing traffic through a serie of traffic lights on a road. From this model the times of duration and phase of the traffic lights are synchronized, using the Adaptive Network Based Fuzzy Inference Systems (ANFIS). The model is simulated and the results are evaluated at macroscopic level with the fixed time model, currently operating in Bogota-Colombia. [ABSTRACT FROM AUTHOR]

The main goal of this research was to characterize the range of noise pollution in Bogota. To achieve such objective, we selected eight microenvironments and several roadways in different zones of the city. In the selected locations, we conducted sound pressure measurements and documented the traffic congestion using a digital video camera. 75% of the time the determined noise levels were above the national standards. This was the case even for sensitive zones such as those nearby parks and hospitals. The results obtained through this research demonstrate both, the importance and complexity of the vehicle traffic impact over the noise pollution in the city. [ABSTRACT FROM AUTHOR]