Traffic Junctions Research Articles

Auditory and non-auditory health effects of noise exposure among people working near traffic junctions in Mysuru city, Karnataka

Background: To assess the prevalence of health effects of noise exposure and the factors associated with it among people occupationally exposed to traffic noise in Mysuru city in Karnataka.Methods: A community based crossectional study was conducted for two months in Mysuru city in Karnataka. The sample size was calculated to be 280 and study participants were recruited from 70 selected locations in the city including all major traffic junctions with signal or traffic police control, covering all regions in the city. Four samples were assessed from each location by history taking and the ambient sound level was recorded from each location using a sound level meter. Data were entered in microsoft excel and analysed using SPSS version 22.Results: The prevalence of hearing loss among the study participants was 5.7% and 1.8% of people complained of tinnitus. Among the study participants, 8.9% had hypertension, 1.1% had cardiovascular disorders, 8.2% had sleeplessness, 6.4% had anxiety, 2.9% had irritability, and 5.7% reported a reduction working efficiency. The proportion of study participants with at least one health effect noise exposure was 26.07%. Only age group was significantly associated with the development of health effects among the exposed individuals.Conclusions: An alarming proportion of people working near traffic areas in Mysuru city are exposed to higher levels of noise and more than 25% of them show symptoms of auditory and/ or non-auditory health effects of noise pollution.

Ambient bioaerosol distribution and associated health risks at a high traffic density junction at Dehradun city, India.

Traffic junctions are one of the crowded places where commuters are at high risk of developing respiratory infections, due to their greater exposure to airborne and human transmitted microbial pathogens. An airborne bioaerosol assessment study was carried out at a high traffic density junction focusing on their concentration, contribution in respirable particulate matter (PM), and factors influencing the distribution and microbial diversity. Andersen six-stage viable cascade impactor and a wide-range aerosol spectrometer were used for microbial and particulate matter measurements, respectively. Statistical analysis was conducted to evaluate the relationship between bioaerosol concentration, vehicular count, PM concentration, and meteorological parameters. The mean bacteria concentration (1962.95 ± 651.85 CFU/m3) was significantly different than fungi (1118.95 ± 428.34 CFU/m3) (p < 0.05). The temporal distribution showed maximum concentration for bacteria and fungi during monsoon and postmonsoon seasons, respectively. In terms of bioaerosol loading, a considerable fraction of fungi (3.25%) and bacteria (5.65%) contributed to the total airborne PM. Most abundant bioaerosols were Aspergillus (27.58%), Penicillium (23%), and Cladosporium (14.05%) (fungi), and Micrococcus (25.73%), Staphylococcus (17.98%), and Bacillus (13.8%) (bacteria). Traffic-induced roadside soil resuspension and microbial aerosolizations from the human body were identified as the chief sources of bioaerosol emissions. The risk of lower respiratory tract infections caused by anthroponotic (human transmitted) transfer of bacterial pathogens is very high. The results of the study can be used to trace sources of microbial mediated communicable diseases, and to recommend appropriate safety measures to avoid pathogenic bioaerosol exposure.Electronic supplementary materialThe online version of this article (10.1007/s10661-020-8158-9) contains supplementary material, which is available to authorized users.

Traffic density estimation using progressive neural architecture search

The current research work is to develop an automated system for estimating the traffic density of roads at traffic junctions and proposed a traffic control algorithm for smooth movement of vehicles based upon the information provided by the density estimation algorithm. The existing methodologies of hand-crafted features and rule-based estimation to count the number of vehicles has been replaced here by Convolutional Neural Network (CNN). The conventional CNN has been replaced by Progressive Neural Architecture (PNAS) which is based on sequential model-based optimization (SMBO) strategy.

Akurasi Citra Data Foto Udara UAV Quadcopter Persimpangan Lalu Lintas Kota Kendari

The use of the Unnamed Aerial Vehicle (UAV) called “Drone” has been widely used in various areas of planning, one of them by mapping the highway traffic junction. The range of remote roaming, adjustable spatial resolution greatly gives flexibility in the effectiveness of field surveys. The mapping accuracy test conducted on 7 (seven) Unsignaling junction in Kendari City by Omisi and Komisi Equation method gives significant output and quite accurate to serve as further planning data. The difference between image and field measurement results, obtained accuracy of 96%, so that the use of UAV in supporting mapping, survey and field planning still prioritize effectiveness and accuracy of the measurement.

Out-Door Air Pollution Levels in Vehicular-Traffic Junctions in Nsukka Metropolis, Enugu Metropolis and Awgu Semi-Urban Area in Enugu State, Nigeria

Studies were carried out to investigate the outdoor air pollution levels in vehicular traffic junctions in the major cities of Nsukka, Enugu and semi-urban area of Awgu all in Enugu State, Nigeria using standard analytical procedures. PM2.5 was collected using Envirotech air sampler, APM 550 and analyzed gravimetrically. Other determined air pollutant gases such as SO2, NO2, O3 and CO were analyzed using colorimetric techniques. The mean hourly traffic density in the vehicular traffic junctions in Nsukka metropolis, Enugu metropolis and Awgu were 2015, 2873 and 587 respectively. The mean range of values of PM2.5, NO2, SO2, O3 and CO in vehicular traffic junctions within the investigated environments were 1.67 - 12.16 μg/m3, 3.72 - 23.83 μg/m3, 2.96 - 30.09 μg/m3, 5.45 - 66.54 μg/m3 and 1.18 - 15.17 ppm respectively. The mean levels of the determined air pollutants in the air around vehicular traffic junctions in Nsukka metropolis, Enugu metropolis and Awgu semi-urban area differed significantly. The mean levels of PM2.5, and CO in the air around vehicular traffic junctions in Enugu metropolis and CO in the air around traffic junctions in Nsukka metropolis were above the recommended permissible limits. Traffic density was therefore seen as the single most important factor contributing to the varying air pollution levels observed in the investigated environments.

Traffic Avoidance System for High Priority Vehicles

India and most of the developing countries have unplanned cities in which roads are narrow and unkempt. Due to increasing vehicular density, repair of roads and traffic rules violation, traffic congestion is increasing at an alarming rate. Delay in arrival of High Priority Vehicles (HPV) like ambulances and fire engines cause severe loss to life and property. Although most HPVs are equipped with sirens, it is not efficient to guarantee a clear road to HPVs due to its audibility range. Hence, we propose a system by which the vehicles near the traffic junction will be alerted about the oncoming of HPV much in advance of its arrival so that they can make way for the HPV. In this system, every HPV is provided with an active RFID tag. Few kilometers before the main signal, an active RFID reader would be placed which would detect the vehicle and send this information to the display screen placed near the traffic junction signal via LoRa wirelessly, starting to make way for the HPV. Therefore, this project proposes to streamline the traffic and allow HPV to pass easily.

Real-time multiple model joint estimation for an urban traffic junction subject to jump dynamics

Traffic conditions in signalized junctions are highly dynamic and may be subject to abrupt changes due to unanticipated traffic incidents or network obstructions. These abrupt changing conditions are represented as different regimes or modes where each mode is represented by its own distinct model, forming a set of multiple models. At any instance in time, only one model of the set has the potential of representing the physical system dynamics at that time. However the dynamics may arbitrarily jump over to a different regime when an abnormal condition arises. Furthermore, it might be impossible to identify these models a priori. Hence, a multiple model approach is developed to self-detect these abrupt changes, identify which member of the set best represents the actual system and automatically self-configure and add a new model to the set when a previously unmodelled regime arises. This approach makes use of a real-time joint (dual) estimation algorithm to estimate traffic state variables such as queue lengths and traffic flow, as well as model parameters such as turning ratios, saturation flow values and noise covariance resulting from unmodelled dynamics and measurement errors. The proposed algorithm is validated through simulations on signalized 3-arm and 4-arm junctions with typical day-to-day traffic conditions including several network irregularities occuring at different times of the day such as arm closures as a result of traffic incidents. This work is aimed to form part of adaptive control loops for traffic light systems that are able to autonomously adjust to changing traffic conditions so as to ensure efficient vehicle flows.

Automatic Path Maker for Emergency Vehicles

Automatic path maker for emergency vehicles” is the most convenient solution for the people. It is adequate condition into the traffic lights systems, as the emergency vehicles as route concerned in the higher priorities among the junctions as the road. At emergency vehicles as included into ambulances, rescue vehicles, fire brigades, polices, &amp; VIP persons. Which is many problem for then the problems, in while it is depended at the injury at the patients, personal accidents, fire fighting’s, robbery, &amp; several vital situation. And can compulsory as implementing at techniques as to solve into situation. The proposed system is for interrupt the running traffic signal when ambulance or VIP is near traffic signals lane. This RFID readed will send these messages to the traffic signal junction to release the news.

Assessment Helmet Usage among Two Wheeler Users in the South India

Background: In India, road traffic injuries are one of the top four leading causes of death and health loss among persons of age group 15-49 years. The share of two wheelers in total road accidents has increased from 28.8% in 2015 to 33.8% in 2016. Out of total of 52,500 two wheeler riders killed in road accidents during the calendar year 2016, 10,135 two-wheeler riders (19.3%) were reported to be not wearing helmets. Aims: Mandatory helmet usage law was enforced in January 2016 for both riders and pillions in Bangalore. Settings and Design: Randomly selected Traffic Junctions of Bangalore city, Karnataka, India. Purposive sampling technique was used to obtain the helmet usage among two wheeler users. Method and Materials: It is a cross sectional study, where 1471 two wheeler riders, pillions were observed at selected 6 traffic junctions using an observation checklist with different intervals of the time in weekdays and weekends. Information regarding socio demographic details and helmet compliance will be collected. Results: In observational survey 1471 two wheeler users were observed at the 6 selected traffic junctions, among riders (82.18%) ,pillions (72.82%) wore helmet. Helmet usage (riders-87.64%) (pillions-76.03%) in inner city junction and in outer ring road junction (riders-74.88%) (pillions-55.12%) respectively. helmet usage in weekdays was 6% more than in weekends among riders. Conclusion: Nearly 20% of riders and 30%of pillions were not wearing helmets. Compliance to ISI (Indian Standard) helmets and buckling of the helmets was poor in both the users.

Design and Experimental Validation of a Distributed Interaction Protocol for Connected Autonomous Vehicles at a Road Intersection

This paper presents a fully distributed interaction protocol for connected self-driving cars negotiating the access a traffic junction. The vehicles coordination has been reformulated as an equivalent virtual platoon control problem. The desired vehicles spacing within the platoon is chosen so to avoid the side and rear-end collisions and is controlled by a cooperative non-linear control algorithm, based on potential functions. The asymptotic stability of the closed-loop system has been analytically proved by leveraging the LaSalle's Invariance Principle. The analysis of the convergence rate has resulted in an effective tuning tool ensuring that the desired formation is achieved before vehicles reach the intersection. Most notably, results from an in-vehicle experimental validation are presented. The experiments were carried out on three self-driving cars connected through a V2V communication infrastructure based on the IEEE 802.11p protocol. The experimental results confirm the theoretical analysis and reveal the effectiveness of the control approach for autonomously and safely negotiating a generic traffic junction.

Smart Real-Time Traffic Optimization System

Today’s traffic situations in busy cities require a smarter traffic signal optimization methodology to regulate the traffic in an orderly manner. Traffic signals are set to a fixed time limit in most of the road junctions. This leads to a dead lock in many junctions because they do not recognize the density of traffic in each road. People want to reach their destinations as quickly as possible. Our proposed Smart Real-Time Traffic Optimization System (SRTOS) provides optimization of traffic signals based on real time Google traffic data. In Google maps, traffic data is indicated through different colors (dark red, red, yellow, orange and green). These colors are processed to find out the traffic around a particular traffic junction and preference is given to the road that has a maximum traffic in the traffic junction, thereby easing out the congestion in that junction. Following similar patterns of activities for all other traffic junctions, wherever possible, will be helpful to drastically ease the flow of traffic patterns of a particular city. This is to fulfill the objective of smoother traffic flow without making people to wait and waste their valuable time

Real-Time Detection of Spatial Disorientation in Persons with Mild Cognitive Impairment and Dementia

Background: Detecting manifestations of spatial disorientation in real time is a key requirement for adaptive assistive navigation systems for people with dementia. Objective: To identify predictive patterns of spatial disorientation in cognitively impaired people during unconstrained locomotion behavior in an urban environment. Methods: Accelerometric data and GPS records were gathered during a wayfinding task along a route of about 1 km in 15 people with amnestic mild cognitive impairment or clinically probable Alzheimer’s disease dementia (13 completers). We calculated a set of 48 statistical features for each 10-s segment of the acceleration sensor signal to characterize the physical motion. We used different classifiers with the wrapper method and leave-one-out cross-validation for feature selection and for determining accuracy of disorientation detection. Results: Linear discriminant analysis using three features showed the best classification results, with a cross-validated ROC AUC of 0.75, detecting 65% of all scenes of spatial disorientation in real time. Consideration of an additional feature that informed about a person’s distance to the next traffic junction did not provide an additional information gain. Conclusions: Accelerometric data are able to capture the uniformity and activity of a person’s walking, which are identified as the most informative locomotion features of spatially disoriented behavior. This serves as an important basis for real-time navigation assistance. To improve the required accuracy of real-time disorientation prediction, as a next step we will analyze whether location-based behavior is able to inform about person-centered habitual factors of orientation.

Density based Automatic Traffic Junction Synchronization

Traffic congestion nowadays has become a chronic issue in the Metropolitan cities due to which it takes more time to travel than the same distance travelled during the off peak hours. This decreases the productivity of an individual by instances such as delayed delivery of services, unnecessary fuel consumption, air and noise pollution, delay in the case of emergency. The traffic congestion has become a predominant problem due to the rapid increase in the demand of vehicles. In places where junctions are closely spaced, encounter a typical issue of lingering in the same traffic signal for multiple times due to the slow moving vehicle caused by congestion. In order to control this issue, research works have been carried out in automating the traffic control system with the help of sensors, image or video processing and also by prioritizing emergency vehicles approaching the junctions. However, employing camera to monitor the traffic is an expensive task. Thus, we are proposing the Density based synchronous of junctions that are closely placed which helps us to save our commuting time significantly and thus enhancing one’s productivity.

Assessment of heavy metals in roadside dust along the Abu Dhabi–Al Ain National Highway, UAE

Concentrations of key heavy metals (Pb, Zn, Cd, Ni, Cr, Mn, As, and Hg) have been investigated in roadside dust collected from Abu Dhabi–Al Ain National Highway in UAE. The heavy metals contents were analyzed by atomic absorption spectrometer. Heavy metal levels varied widely from 227.9 to 2765, 19 to 1540, 37.4 to 398.6, 20.1 to 123, 0.3 to 0.7, 0.1 to 0.9, 0.1 to 0.7, and 0.1 to 0.5 mg/kg for Mn, Cr, Zn, Pb, Cd, Hg, Ni, and As, respectively. The spatial distribution pattern showed that different sources of roadway metal emissions dominate at specific locations. Peaks in heavy metal concentrations were frequently observed in locations with high traffic volume, road intersections and junctions, gas and bus stations. Decreased levels of heavy metals were measured in locations with low traffic loadings and in close proximity to farm and forest areas. In addition to traffic-related heavy metals, emissions from fossil fuel and industries remain of significance. Natural sources, through regular dust storms, are important contributors to the observed metal levels. Enrichment factor indicated that As and Ni were entirely originated from crustal sources. Cd, Zn, Pb, and Mn were moderately enriched and are probably derived from mixed sources (traffic flows, gas stations, construction and agricultural activities, among others). Road dust was significantly enriched in Cr and Hg indicating their dominant anthropogenic origin. The average geo-accumulation index values suggested that road dust are uncontaminated with Mn, Ni, and As, uncontaminated to moderately contaminated with Zn and Pb, and moderately contaminated with Cr, Cd, and Hg. The contamination factors indicated very highly contaminated road dust with Cr and Hg, considerably contaminated with Cd, and moderately contaminated with Mn, Zn, and Pb. Results of ecological risk assessment revealed that all heavy metals in road dust pose low risk to local ecosystems, except for Cd and Hg, which constitute potentially considerable risk and high risk, respectively.

Elucidating Traffic Junction Effects in MFI Zeolite Using Kinetic Monte Carlo Simulations

Published experimental studies on the diffusion of n-butane (nC4)/iso-butane (iC4), n-hexane (nC6)/2-methylpentane (2MP), and methane/benzene mixtures in MFI zeolite show that the self-diffusivity of the more mobile (linear) alkanes is diminished by about 1–3 orders of magnitude with increasing proportion of the tardier partners (iC4, 2MP, benzene) in the mixture. The strong reduction can be rationalized on the basis of the preferential location of the tardier partners iC4, 2MP, and benzene at the channel intersections of MFI, serving to slow down the molecular traffic. The primary objective of this article is to investigate, and quantify, such traffic junction effects with the aid of kinetic Monte Carlo (KMC) simulations. The KMC simulations show that the preferential location of branched molecules at the channel intersections can be effectively considered as an intersection blocking with attendant loss of connectivity of the MFI topology. Consequently, both the Maxwell–Stefan (M–S) diffusivity and self-...

Adaptive real time traffic prediction using deep neural networks

&lt;span lang="EN-US"&gt;The ever-increasing sale of vehicles and the steady increase in population density in metropolitan cities have raised many growing concerns, most importantly commute time, air and noise pollution levels. Traffic congestion can be alleviated by opting using adaptive traffic light systems, instead of fixed-time traffic signals. In this paper, a system is proposed which can detect, classify and count vehicles passing through any traffic junction using a single camera (as opposed to multi-sensor approaches). The detection and classification are done using SSD Neural Network object detection algorithm. The count of each class (2-wheelers, cars, trucks, buses etc.) is used to predict the signal green-time for the next cycle. The model self-adjusts every cycle by utilizing weighted moving averages. This system works well because the change in the density of traffic on any given road is gradual, spanning multiple traffic stops throughout the day.&lt;/span&gt;

Automatic traffic light controller for emergency vehicle using peripheral interface controller

Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.

The Application of Number Theory to Determine Congruence in Traffic Lights

In everyday life many number theories are often used to solve problems. In this paper we will discuss the application of number theory in testing the suitability of traffic lights. Testing uses the Euclidean theorem which is part of number theory. Number theory as a theoretical basis for exposure to traffic light congruence. This paper presents a calculation of traffic intersections to determine the suitability of traffic junction lights. The results in this paper show, if a traffic junction has congruence between traffic lights.

Airborne PM10 and lead concentrations at selected traffic junctions in Khyber Pakhtunkhwa, Pakistan: Implications for human health

The airborne particulates pollution is a serious concern due to its adverse health impacts. This study was carried out to assess the PM10 mass concentration and PM10-bound lead (Pb) at two major traffic junctions in Charsadda and Upper Dir Districts of Khyber Pakhtunkhwa (KP), Pakistan. A high-volume Reference Ambient Air Sampler (RAAS) was used to collect PM10 samples (n = 30) on glass fiber filters from April 2017 to September 2017. The PM10 mass was determined by gravimetric analysis weighing each filter disc before and after sampling. The PM10-bound Pb concentrations were determined using graphite furnace atomic absorption spectroscopy after filters acid digestion. Health risks of PM10-bound Pb were evaluated numerically by hazard quotient (HQ) and hazard index (HI). The PM10 mass (24 h mean) was 4.6 times higher than the WHO guideline value for air quality. Likewise, the PM10-bound Pb was 1.3 times higher than the WHO guideline value. Mean PM10 concentrations were 254 ± 67 μg/m3 and 208 ± 85 μg/m3 and mean PM10-bound Pb concentrations were 709 ± 206 ng/m3 and 638 ± 231 ng/m3 at the traffic junctions in Charsadda and Upper Dir Districts respectively. The mean HI values were less than 1 for the exposed adults and children indicating that health effects are unlikely to occur in the exposed population. Measures should be taken to monitor the airborne PM10 on regular basis and reduce its emissions into the air.

Pollution and health risk assessment of road dust from Osogbo metropolis, Osun state, Southwestern Nigeria

This study assessed pollution and health risk associated with road dust samples collected from major roads in Osogbo metropolis, Osun State, Southwestern Nigeria. Road dust samples were collected from nine major traffic junctions. Soil samples were collected to serve as control. A total of 72 samples were collected and subjected to laboratory assays using standard procedures. The dust and soil samples were analyzed for pH, electrical conductivity, NO3−, SO42− and metals. Data obtained were subjected to simple descriptive statistics using SPSS for Windows. Health risk indices of hazard quotient (HQ), hazard index (HI) and cancer risk (CR) were assessed. Pollution assessment was also evaluated. Results showed the metal distributions in the road dust as follows: Zn > Mn > Cu > Pb > Ni > Na > K > Cd > Cr > Co > As > V. The pollution assessment indices presented Cd as the major road dust contaminant in the study area. The health risk assessment of non-carcinogenic effects showed HQ and HI values of metals less than 1.0 for children and adults, indicating no adverse effect but the sum of CR was higher than the permissible limit of 1.0 x 10−4 in children indicating possible cancer development.