Search results for: road traffic incidents

Authors: U. Chattaraj, D. Meena

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Growth of traffic brings various negative effects, such as road accidents. To avoid such problems, a model is developed for the purpose of highway safety. In such areas, fuzzy logic is the most well-known simulation in the larger field. A model is accomplished for hilly and steep terrain based on Fuzzy Inference System (FIS), for which output is super elevation and input data is horizontal radius, vertical gradient, accident rate (AR). This result shows that the system can be efficaciously applied as for highway safety tool distinguishing hazards components correlated to the characteristics of the highway and has a great influence to the making of decision for accident precaution in transportation models. From this model, a positive relationship between geometric elements, accident rate, and super elevation is also identified.

Keywords: accident rate, fuzzy inference system, fuzzy logic, gradient, radius, super elevation

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Authors: Samiah H. Ghounaim

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The topic of this paper is significant because of the increasing need for intercultural training for foreign language teachers due to the continuous challenges they face in their diverse classrooms. First, the structure of the intercultural training program designed will be briefly described, and the structure of a 3D vignette and its intended purposes will be elaborated on. This was the first stage where the program was designed and implemented on the period of three months with a group of local and expatriate foreign language teachers/practitioners at a university in the Middle East. After that, a set of primary data collected during the first stage of this research on the design and co-construction process of a 3D vignette will be reviewed and analysed in depth. Each practitioner designed a personal incident into a 3D vignette where each dimension of the vignette viewed the same incident from a totally different perspective. Finally, the results and the implications of having participant construct their personal incidents into a 3D vignette as a reflective practice will be discussed in detail as well as possible extensions for the research. This process proved itself to be an effective reflective practice where the participants were stimulated to view their incidents in a different light. Co-constructing one’s own critical incidents –be it a positive experience or not– into a structured 3D vignette encouraged participants to decentralise themselves from the incidents and, thus, creating a personal reflective space where they had the opportunity to see different potential outcomes for each incident, as well as prepare for the reflective discussion of their vignette with their peers. This provides implications for future developments in reflective writing practices and possibilities for educators’ continuous professional development (CPD).

Keywords: 3D vignettes, intercultural competence training, reflective practice, teacher training

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

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Authors: Amara Rafik, Bougherara Maamar, Belhadj Aissa Mostefa

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Radar data is one of the many data sources used by ATM Air Traffic Management systems. These data come from air navigation radar antennas. These radars intercept signals emitted by the various aircraft crossing the controlled airspace and calculate the position of these aircraft and retransmit their positions to the Air Traffic Management System. For greater reliability, these radars are positioned in such a way as to allow their coverage areas to overlap. An aircraft will therefore be detected by at least one of these radars. However, the position coordinates of the same aircraft and sent by these different radars are not necessarily identical. Therefore, the ATM system must calculate a single position (radar track) which will ultimately be sent to the control position and displayed on the air traffic controller's monitor. There are several techniques for calculating the radar track. Furthermore, the geographical nature of the problem requires the use of a Geographic Information System (GIS), i.e. a geographical database on the one hand and geographical processing. The objective of this work is to propose a GIS for traffic simulation which reconstructs the evolution over time of aircraft positions from a multi-source radar data set and by applying these different techniques.

Keywords: ATM, GIS, radar data, air traffic simulation

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Authors: Mariam Shah

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‘Honour’ crime has commonly been perceived in the UK as being a ‘domestic violence’ related issue due to incidents perceived to take place within a domestic context, and commonly by familial perpetrators. The lack of differentiation between domestic violence and ‘honour’ related incidents has several negative implications. Firstly, the prevalence and extent of ‘honour’ related crime within the UK cannot be accurately quantified due to ‘honour’ incidents being classed statistically as domestic violence incidents. Secondly, lack of differentiation means that the negative stereotypical attitudes ascribed to domestic violence which has resulted in lower criminal conviction rates that are also impacting the conviction of perpetrators of ‘honour’ crime. Thirdly, ‘honour’ related crime is innately distinct from domestic violence due to the perpetrator’s resolute intent of cleansing perceived ‘shame’ in any way possible, often with the involvement and collusion of multiple perpetrators from within the family and/or community. Domestic violence is typically restricted to the ‘home’, but ‘honour’ crime can operate between national and international boundaries. This paper critically examines the current academic literature and concludes that the few similarities between domestic violence and ‘honour’ related crime are not sufficient to warrant identical treatment under UK criminal law. ‘Honour’ related crime is a distinct and stand-alone offence which should be recognised as such. The appropriate identification and treatment of ‘honour’ crime are crucial, particularly in light of the UK’s first ‘white’ honour killing which saw a young English woman murdered after being deemed to have brought ‘shame’ on her ex-boyfriend’s family. This incident highlights the possibility of ‘honour’ crime extending beyond its perceived ‘ethnic minority’ roots and becoming more of a ‘mainstream’ issue for the multi-cultural and multi-racial UK.

Keywords: differentiation, domestic violence, honour crime, United Kingdom

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Authors: Raj Kumar Kama, Rajshree Kamat

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Traffic congestion is a serious problem that is to be considered, and it is increasing day-by-day in urban areas that is seriously affecting the urban society. From the study, it is understood that increased urbanization and growth of population are the principal causes of congestion. It has adverse effects on society, economy, environment, and health. This study mainly focussed on studying and understanding the causes of congestion, consequences faced by urban society, and planning solutions to mitigate congestion. Techniques like transit oriented development (TOD) and integrated transport systems are more effective in mitigating traffic congestion.

Keywords: traffic congestion, transit oriented development, integrated transport system, urbanization

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Authors: Susana Aragoneses Garrido

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Every day, the roads are scenery of numerous accidents involving vehicles, producing thousands of deaths and serious injuries all over the world. Investigations have revealed that Human Factors (HF) are one of the main causes of road accidents in modern societies. Distracted driving (including external or internal aspects of the vehicle), which is considered as a human factor, is a serious and emergent risk to road safety. Consequently, a further analysis regarding this issue is essential due to its transcendence on today’s society. The objectives of this investigation are the detection and assessment of the HF in order to provide solutions (including a better vehicle design), which might mitigate road accidents. The methodology of the project is divided in different phases. First, a statistical analysis of public databases is provided between Spain and The UK. Second, data is classified in order to analyse the major causes involved in road accidents. Third, a simulation between different paths and vehicles is presented. The causes related to the HF are assessed by Failure Mode and Effects Analysis (FMEA). Fourth, different car models are evaluated using the Rapid Upper Body Assessment (RULA). Additionally, the JACK SIEMENS PLM tool is used with the intention of evaluating the Human Factor causes and providing the redesign of the vehicles. Finally, improvements in the car design are proposed with the intention of reducing the implication of HF in traffic accidents. The results from the statistical analysis, the simulations and the evaluations confirm that accidents are an important issue in today’s society, especially the accidents caused by HF resembling distractions. The results explore the reduction of external and internal HF through the global analysis risk of vehicle accidents. Moreover, the evaluation of the different car models using RULA method and the JACK SIEMENS PLM prove the importance of having a good regulation of the driver’s seat in order to avoid harmful postures and therefore distractions. For this reason, a car redesign is proposed for the driver to acquire the optimum position and consequently reducing the human factors in road accidents.

Keywords: analysis vehicles, asssesment, ergonomics, car redesign

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Authors: Zhang Cong, Cai Runlin, Jia Fengjiao

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The evolution of the urban agglomeration spatial structure requires strong support of the inter-city traffic system. And the inter-city traffic system can not only meet the demand of the urban agglomeration transportation but also guide the economic development. To correctly understand the relationship between inter-city traffic planning and urban agglomeration can help the urban agglomeration coordinated developing with the inter-city traffic system. The Yangtze River Delta is one of the most representative urban agglomerations in China with strong economic vitality, high city levels, diversified urban space form, and improved transport infrastructure. With the promotion of industrial division in the Yangtze River Delta and the regional travel facilitation brought by inter-city traffic, the urban agglomeration is characterized by highly increasing of inter-city transportation demand, the urbanization of regional traffic, adjacent regional transportation links breaking administrative boundaries, the networked channels and so on. Therefore, the development of inter-city traffic system presents new trends and challenges. This paper studies the interactions between inter-city traffic system and regional economic growth, regional factor flow, and regional spatial structure evolution in the Yangtze River Delta from two dimensions of time and space. On this basis, the adaptability of inter-city traffic development mode and urban agglomeration space structure is analyzed. First of all, the coordination between urban agglomeration planning and inter-city traffic planning is judged from the planning level. Secondly, the coordination between inter-city traffic elements and industries and population distributions is judged from the perspective of space. Finally, the coordination of the cross-regional planning and construction of inter-city traffic system is judged. The conclusions can provide an empirical reference for intercity traffic planning in Yangtze River Delta region and other urban agglomerations, and it is also of great significance to optimize the allocation of urban agglomerations and the overall operational efficiency.

Keywords: evolution, interaction, inter-city traffic system, spatial structure

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Authors: Jean Felix Tuyisingize

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Speeding or inappropriate speed is a major problem worldwide, contributing to 10-15% of road crashes and 30% of fatal injury crashes. The consequences of speeding put the driver's life at risk and the lives of other road users like motorists, cyclists, and pedestrians. To control vehicle speeds, governments, and traffic authorities enforced speed regulations through speed cameras and speed section control, which monitor all vehicle speeds and detect plate numbers to levy penalties. However, speed limit violations are prevalent, even on motorways with speed cameras. The problem with speed cameras is that they alter driver behaviors, and their effect declines with increasing distance from the speed camera location. Drivers decelerate short distances before the camera and vigorously accelerate above the speed limit just after passing by the camera. The sudden decelerating near cameras causes the drivers to try to make up for lost time after passing it, and they do this by speeding up, resulting in a phenomenon known as the "Kangaroo jump" or "V-profile" around camera/ASSC areas. This study investigated the impact of speed enforcement devices, specifically Average Speed Section Control (ASSCs) and fixed cameras, on acceleration and deceleration events within their vicinity. The research employed advanced statistical and Geographic Information System (GIS) analysis on naturalistic driving data, to uncover speeding patterns near the speed enforcement systems. The study revealed a notable concentration of events within a 600-meter radius of enforcement devices, suggesting their influence on driver behaviors within a specific range. However, most of these events are of low severity, suggesting that drivers may not significantly alter their speed upon encountering these devices. This behavior could be attributed to several reasons, such as consistently maintaining safe speeds or using real-time in-vehicle intervention systems. The complexity of driver behavior is also highlighted, indicating the potential influence of factors like traffic density, road conditions, weather, time of day, and driver characteristics. Further, the study highlighted that high-severity events often occurred outside speed enforcement zones, particularly around intersections, indicating these as potential hotspots for drastic speed changes. These findings call for a broader perspective on traffic safety interventions beyond reliance on speed enforcement devices. However, the study acknowledges certain limitations, such as its reliance on a specific geographical focus, which may impact the broad applicability of the findings. Additionally, the severity of speed modification events was categorized into low, medium, and high, which could oversimplify the continuum of speed changes and potentially mask trends within each category. This research contributes valuable insights to traffic safety and driver behavior literature, illuminating the complexity of driver behavior and the potential influence of factors beyond the presence of speed enforcement devices. Future research directions may employ various categories of event severity. They may also explore the role of in-vehicle technologies, driver characteristics, and a broader set of environmental variables in driving behavior and traffic safety.

Keywords: acceleration, deceleration, speeding, inappropriate speed, speed enforcement cameras

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Authors: Aswin V. J., Sreeja S., R. Harikumar

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Ship collision is one of the major concerns while navigating in the ocean. In congested sea routes where there are hectic offshore operations, ships are often forced to take close encounter maneuvers. Maritime rules for preventing collision at sea are defined in the International Regulations for Preventing Collision at Sea. Traffic Separation Schemes (TSS) are traffic management route systems ruled by International Maritime Organization (IMO), where the traffic lanes indicate the general direction of traffic flow. The Rule 10 of International Regulations for Preventing Collision at Sea prescribes the conduct of vessels while navigating through TSS. But no quantitative criteria regarding the procedures to detect and evaluate collision risk is specified in International Regulations for Preventing Collision at Sea. Most of the accidents that occur are due to operational errors affected by human factors such as lack of experience and loss of situational awareness. In open waters, the traffic density is less when compared to that in TSS, and hence the vessels can be operated in autopilot mode. A collision avoidance method that uses the possible obstacle trajectories in advance to predict “collision occurrence” and can generate suitable maneuvers for collision avoidance is presented in this paper. The suitable course and propulsion changes that can be used in a TSS considering International Regulations for Preventing Collision at Sea are found out for various obstacle scenarios.

Keywords: collision avoidance, maneuvers, obstacle trajectories, traffic separation scheme

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Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

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The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow

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Authors: Oscar Nieto-Garzón, Angélica Lozano

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In urban areas, on-road freight transportation creates several social and environmental externalities. Then, it is crucial that freight transport considers not only economic aspects, like retailer distribution cost reduction and service improvement, but also environmental effects such as global CO2 and local emissions (e.g. Particulate Matter, NOX, CO) and noise. Inadequate infrastructure development, high rate of urbanization, the increase of motorization, and the lack of transportation planning are characteristics that urban areas from developing countries share. The Metropolitan Area of Mexico City (MAMC), the Metropolitan Area of São Paulo (MASP), and Bogota are three of the largest urban areas in Latin America where air pollution is often a problem associated with emissions from mobile sources. The effect of the lockdown due to COVID-19 was analyzedfor these urban areas, comparing the same period (January to August) of years 2016 – 2019 with 2020. A strong reduction in the concentration of primary criteria pollutants emitted by road traffic were observed at the beginning of 2020 and after the lockdown measures.Daily mean concentration of NOx decreased 40% in the MAMC, 34% in the MASP, and 62% in Bogota. Daily mean ozone levels increased after the lockdown measures in the three urban areas, 25% in MAMC, 30% in the MASP and 60% in Bogota. These changes in emission patterns from mobile sources drastically changed the ambient atmospheric concentrations of CO and NOX. The CO/NOX ratioat the morning hours is often used as an indicator of mobile sources emissions. In 2020, traffic from cars and light vehicles was significantly reduced due to the first lockdown, but buses and trucks had not restrictions. In theory, it implies a decrease in CO and NOX from cars or light vehicles, maintaining the levels of NOX by trucks(or lower levels due to the congestion reduction). At rush hours, traffic was reduced between 50% and 75%, so trucks could get higher speeds, which would reduce their emissions. By means an emission model, it was found that an increase in the average speed (75%) would reduce the emissions (CO, NOX, and PM) from diesel trucks by up to 30%. It was expected that the value of CO/NOXratio could change due to thelockdownrestrictions. However, although there was asignificant reduction of traffic, CO/NOX kept its trend, decreasing to 8-9 in 2020. Hence, traffic restrictions had no impact on the CO/NOX ratio, although they did reduce vehicle emissions of CO and NOX. Therefore, these emissions may not adequately represent the change in the vehicle emission patterns, or this ratio may not be a good indicator of emissions generated by vehicles. From the comparison of the theoretical data and those observed during the lockdown, results that the real NOX reduction was lower than the theoretical reduction. The reasons could be that there are other sources of NOX emissions, so there would be an over-representation of NOX emissions generated by diesel vehicles, or there is an underestimation of CO emissions. Further analysis needs to consider this ratioto evaluate the emission inventories and then to extend these results forthe determination of emission control policies to non-mobile sources.

Keywords: COVID-19, emissions, freight transport, latin American metropolis

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Authors: Saeed Sayyad Hagh Shomar

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Traffic congestion pricing as one of the demand management strategies constrains expenditure to network users so that it helps reduction in traffic congestion and environment pollution like air pollution. Despite the development of congestion pricing schemes for traffic in our country, the matters of traditional toll collection, drivers’ waste of time and delay in traffic are still widespread. Electronic toll collection as a part of the intelligent transportation system provides the possibility of collecting tolls without car-stop and traffic disruption. Unlike the satisfying outcomes of using intelligent systems in congestion pricing schemes, implementation costs and technological problems are the barriers in these schemes. In this research first, a variety of electronic pay toll systems and their components are introduced then their functional usage is discussed. In the following, by analyzing and comparing the barriers, limitations and advantages, the selection criteria of intelligent systems are described and the results show that the choice of the best technology depends on the various parameters which, by examining them, it is concluded that in a long-term run and by providing the necessary conditions, DSRC technology as the main system in the schemes and ANPR as a major backup system of the main one can be employed.

Keywords: congestion pricing, electronic toll collection, intelligent systems, technology, traffic

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Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab

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Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.

Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning

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Authors: Francisco Toledo-Castillo, Pilar Peiró-Torres, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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The communication presented is about tasks that are been developed in the research project “safeRoute”, “Information safety system for professional road driving” (IPT-2012-110-370000). This R&D project was proposed by the consortium formed by Fagor Electronica la SEU 3 and the University of Valencia to the Ministry of Economy and Competitiveness, which approved it inside the INNPACTO subprogramme grants. Through this type of calls, the Ministry promote the innovative capacity of the Spanish companies and turn on the mechanism for competing internationally. With this kind of calls, private investments for technological and industrial development join their R & D resources with public entities to implement innovative project that could have an international exposure. Thus INNPACTO subprogramme promotes the creation of research projects with public-private partnerships that create exploitable final products. The “safeRoute” Project pretends develop a tool to help to make more safety the travels of commercial transport vehicles of goods and passengers. To achieve its objectives, the project is focused in three main lines of research: vehicle safety, the safety of the roads that they are using, and the safety which drivers do their job, their behaviour while they are driving. To improve safety, the project gives information about these three factors to all people that are involved in the safety of the professional transport. These three factors have influence to the occurrence of traffic accidents, thanks to the information provided and treated about these factors, we can achieve a significant reduction in occupational accidents in the transport sector. SafeRoute provide information about routes, vehicles, and driver behaviours, and in this manner pretends provide to transport companies a tool which could result in a safer driving results and could reduce their costs related to traffic accidents of their vehicles, in that way, this tool could help them to be more competitive, and give a more reliable service. This paper will focus mainly on the information about routes that drivers use to travel in their professional work, and how the researchers of this project have catalogued and evaluated these routes, and finally how that information will be provided to users.

Keywords: driver support systems, professional drivers, road safety, safeRoute

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Authors: Ezil Sam Leni, Shalen S.

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Transport service monitoring and upkeep are essential components of smart city initiatives. The main risks to the relevant departments and authorities are the ever-increasing vehicular traffic and the conditions of the roads. In India, the economy is greatly impacted by the road transport sector. In 2021, the Ministry of Road Transport and Highways Transport, Government of India, produced a report with statistical data on traffic accidents. The data included the number of fatalities, injuries, and other pertinent criteria. This study proposes a distributed infrastructure for the monitoring, detection, and reporting of potholes to the appropriate authorities. In a distributed environment, the nodes are the edge devices, and local edge servers, and global servers. The edge devices receive the initial model to be employed from the global server. The YOLOv8 model for pothole detection is used in the edge devices. The edge devices run the pothole detection model, gather the pothole images on their path, and send the updates to the nearby edge server. The local edge server selects the clients for its aggregation process, aggregates the model updates and sends the updates to the global server. The global server collects the updates from the local edge servers, performs aggregation and derives the updated model. The updated model has the information about the potholes received from the local edge servers and notifies the updates to the local edge servers and concerned authorities for monitoring and maintenance of road conditions. The entire process is implemented in FedCV distributed environment with the implementation using the client-server model and aggregation entities. After choosing the clients for its aggregation process, the local edge server gathers the model updates and transmits them to the global server. After gathering the updates from the regional edge servers, the global server aggregates them and creates the updated model. Performance indicators and the experimentation environment are assessed, discussed, and presented. Accelerometer data may be taken into consideration for improved performance in the future development of this study, in addition to the images captured from the transportation routes.

Keywords: federated Learning, pothole detection, distributed framework, federated averaging

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Authors: Hossein Arfaeinia, Ahmad Jonidi Jafari, Sina Dobaradaran, Sadegh Niazi, Mojtaba Ehsanifar, Amir Zahedi

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Street dust and surface soil samples were collected from very heavy, heavy, medium and low traffic areas and natural site in Tehran, Iran. These samples were analyzed for some physical–chemical features, total and chemical speciation of selected metals and metalloids (Zn, Al, Sr, Pb, Cu, Cr, Cd, Co, Ni, and V) to study the effect of traffic on their mobility and accumulation in the environment. The pH, electrical conductivity (EC), carbonates and organic carbon (OC) values were similar in soil and dust samples from similar traffic areas. The traffic increases EC contents in dust/soil matrixes but has no effect on concentrations of metals and metalloids in soil samples. Rises in metal and metalloids levels with traffic were found in dust samples. Moreover, the traffic increases the percentage of acid soluble fraction and Fe and Mn oxides associated fractions of Pb and Zn. The mobilization of Cu, Zn, Pb, Cr in dust samples was easier than in soil. The speciation of metals and metalloids except Cd is mainly affected by physicochemical features in soil, although total metals and metalloids affected the speciation in dust samples (except chromium and nickel).

Keywords: street dust, surface soil, traffic, metals, metalloids, chemical speciation

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Authors: Okanlawon Simon Ayorinde, Odunjo Oluronke Omolola, Fadamiro Joseph Akinlabi, Adedibu Afolabi Adebgite

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A road is a path established over land, especially prepared way between places for the use of pedestrian, riders, and vehicles: a hard surface built for vehicles to travel on. The social, economic and health importance of roads in any community and nation cannot be underestimated. Roads provide access to properties and they also provide mobility which is ability to transport goods and services from one place to another. In the residential zones of many indigenous cities in Nigeria, roads are usually blocked for social ceremonies. Road blocked for ceremonies as used in this study are a temporary barrier across a road, used to stop or hinder traffic from passing through to the other side. Social ceremonies that could warrant road blockage include marriage, child naming, funeral, celebration of life’s achievement, birthday anniversary etc. These activities are likely to generate environmental hazards and their attendant risks. The assessment of these hazards and risks in residential zones of indigenous cities in Nigeria becomes imperative. The study is focused on Ogbomoso, Oyo State, Nigeria. The town has two local government councils namely Ogbomoso North and Ogbomoso South. Urban tracts that are easy to identify are political wards in the absence of land use segregation, houses numbering and street naming. The wards that had residential having a minimum of 60% of their land use components were surveyed and fifteen out of twenty wards identified in the town were surveyed. The study utilized primary data collected through questionnaire administration The three major road categories (Trunk A-Federal; Trunk B- State; Trunk C-Local) were identified and trunk C-Local roads were purposively selected being the concern of this study because they are the ones often blocked for social activities. The major stakeholders interviewed and the respective sampling methods are residents (random and systematic), social ceremony organizers (purposive), government officials (purposive) and road users namely commercial motorists and commercial motor cyclists (random and incidental). Data analysis was mainly descriptive. Two indices to measure respondents’ perception were developed. These are ‘Hazard Severity Index’ (HSI) and ‘Relative Awareness Index’ (RAI).Thereafter, policy implications and recommendations were provided.

Keywords: road, residential zones, indigenous cities, blocked, social ceremonies

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Authors: Yuxiao Jiang, Lingjun Meng, Mengyu Zhan, Lichunyi Zhang, Yingxia Yun

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On August 8th of 2015, a serious explosion occurred in Binhai New Area of Tianjin. This explosion led to the suspension of Tianjin-Binhai Light Rail Line 9 which was an important transportation mean connecting the old and new urban areas and the suspension causes inconvenience to commuters traveling from Tianjin to Binhai or Binhai to Tianjin and residents living by Line 9. On this regard, this paper intends to give suggestions on how to develop multi-mode transportation system rapidly and effectively after a disaster and tackle with the problems in terms of transportation infrastructure facilities. The paper proposes the idea of traffic resilience which refers to the city’s ability to restore its transportation system and reduce risks when the transportation system is destroyed by a disaster. By doing questionnaire research, on the spot study and collecting data from the internet, a GIS model is established so as to analyze the alternative traffic means used by different types of residents and study the transportation supply and demand. The result shows that along the Line 9, there is a larger demand for alternative traffic means in the place which is nearer to the downtown area. Also, the distribution of bus stations is more reasonable in the place nearer to downtown area, however, the traffic speed in the area is slower. Based on traffic resilience, the paper raises strategies to develop post-disaster multi-mode transportation system such as establishing traffic management mechanism timely and effectively, building multi-mode traffic networks, improving intelligent traffic systems and so on.

Keywords: traffic resilience, multi-mode transportation system, public traffic, transportation demand

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: false negative rate, intrusion detection system, machine learning methods, performance

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Authors: Dogaru-Ulieru Valentin, Sălișteanu Ioan Corneliu, Ardeleanu Mihăiță Nicolae, Broscăreanu Ștefan, Sălișteanu Bogdan, Mihai Mihail

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The SiaMOTO system is a communications and data processing platform for vehicle traffic. The human factor is the most important factor in the generation of this data, as the driver is the one who dictates the trajectory of the vehicle. Like any trajectory, specific parameters refer to position, speed and acceleration. Constant knowledge of these parameters allows complex analyses. Roadways allow many vehicles to travel through their confined space, and the overlapping trajectories of several vehicles increase the likelihood of collision events, known as road accidents. Any such event has causes that lead to its occurrence, so the conditions for its occurrence are known. The human factor is predominant in deciding the trajectory parameters of the vehicle on the road, so monitoring it by knowing the events reported by the DiaMOTO device over time, will generate a guide to target any potentially high-risk driving behavior and reward those who control the driving phenomenon well. In this paper, we have focused on detailing the communication infrastructure of the DiaMOTO device with the traffic data collection server, the infrastructure through which the database that will be used for complex AI/DLM analysis is built. The central element of this description is the data string in CODEC-8 format sent by the DiaMOTO device to the SiaMOTO collection server database. The data presented are specific to a functional infrastructure implemented in an experimental model stage, by installing on a number of 50 vehicles DiaMOTO unique code devices, integrating ADAS and GPS functions, through which vehicle trajectories can be monitored 24 hours a day.

Keywords: DiaMOTO, Codec-8, ADAS, GPS, driver monitoring

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Authors: Sumit Roy

Abstract:

A clear understanding of pedestrian behaviour at road crossing at intersections is needed for providing necessary infrastructure and also for enhancing pedestrian safety at any intersection. Pedestrian road crossing behaviour is studied at Motijheel and Kakrail intersections where Motijheel intersection is a controlled roundabout, and Kakrail intersection is a signalized intersection. Around 60 people at each intersection were interviewed for a questionnaire survey and video recording at different time of a day was done for observation at each intersection. In case of Motijeel intersection, we got pedestrian road crossings were much higher than Kakrail intersection. It is because the number of workplaces here is higher than Kakrail. From questionnaire survey, it is found that 80% of pedestrians crosses at intersection to avail buses and their loading and unloading locations are at intersection, whereas at Kakrail intersection only 25% pedestrian crosses the road for buses as buses do not slow down here. At Motijheel intersection 25 to 40% of pedestrians choose to jump over the barricade for crossing instead of using overbridge for saving time and labour. On the other hand, the pedestrians using overbridge told that they use overbridge for safety. Moreover, pedestrian crosses at the same pace for both red and green interval with vehicle movement in the range of 12.5 to 14.5 km/h and gaps between vehicle were more than 4 m. Here pedestrian crossing speed varies from 3.5 to 7.2 km/h. In Kakrail intersection the road crossing situation can be classified into 4 categories. In case of red time, pedestrians do not wait to cross the road, and crossing speed varies from 3.5 to 7.2 km/h. When vehicle speed varies from 5.4 to 7.4 km/h, and gaps between vehicle vary from 1.5 to 2 m, most of the pedestrians initially choose to wait and try to cross the road in group with crossing speed 2.7 to 3.5 km/h. When vehicle speed varies from 10.8 to 18 km/h, and gaps between vehicles varies from 2 to 3 m most of the people waits and cross the road in group with crossing speed 3.5 to 5.4 km/h. When vehicle speed varies from 25.2 to 32.4 km/h and gaps between vehicles vary from 4 to 6 m most of the pedestrians choose to wait until red time. In Kakrail intersection 87% of people said that they cross the road with risk and 60% of pedestrians told that it is risky to get on and off the bus at this intersection. Planned location of loading and unloading area for buses can improve the pedestrian road crossing behaviour at intersections.

Keywords: crossing speed, pedestrian behaviour, road crossing, use of overbridge

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Authors: Katherine Carl Payne, Moshe Dror

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The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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Authors: Ramesh Chandra Majhi

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Saturation flow is a very important input variable for the design of signalized intersections. Saturation flow measurement is well established for homogeneous traffic. However, saturation flow measurement and modeling is a challenging task in heterogeneous characterized by multiple vehicle types and non-lane based movement. Present study focuses on proposing a field procedure for Saturation flow measurement and the effect of typical mixed traffic behavior at the signal as far as non-lane based traffic movement is concerned. Data collected during peak and off-peak hour from five intersections with varying approach width is used for validating the saturation flow model. The insights from the study can be used for modeling saturation flow and delay at signalized intersection in heterogeneous traffic conditions.

Keywords: optimization, passenger car unit, saturation flow, signalized intersection

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Authors: M. Mokhber, J. Hedayati

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From the managerial perspective, it is important to devise an operational plan based on top priorities due to limited resources, diversity of measures and high costs needed to improve safety in infrastructure. Dealing with the high-risk corridors across Iran, this study prioritized the corridors according to statistical data on accidents involving fatalities, injury or damage over three consecutive years. In collaboration with the Iranian Police Department, data were collected and modified. Then, the prioritization criteria were specified based on the expertise opinions and international standards. In this study, the prioritization criteria included accident severity and accident density. Finally, the criteria were standardized and weighted (equal weights) to score each high-risk corridor. The prioritization phase involved the scoring and weighting procedure. The high-risk corridors were divided into twelve groups out of 50. The results of data analysis for a three-year span suggested that the first three groups (150 corridors) along with a quarter of Iranian road network length account for nearly 60% of traffic accidents. In the next step, according to variables including weather conditions particular roads for the purpose of winter safety measures were extracted from the abovementioned categories. According to the results ranking, ‎‏9‏‎ roads with the overall ‎length of about ‎‎‏1000‏‎ Km of high-risk corridors are considered as preferences of ‎safety measures‎.

Keywords: high-risk corridors, HRCs, road safety rating, road scoring, winter safety measures

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Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: H. M. Liman, Y. M. Suleiman A. A. David

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Poor air quality often considered one of the greatest environmental threats facing the world today is caused majorly by the emission of carbon monoxide into the atmosphere. The principal air pollutant is carbon monoxide. One prominent source of carbon monoxide emission is the transportation sector. Not much was known about the emission levels of carbon monoxide, the primary pollutant from the road transportation in the study area. Therefore, this study assessed the levels of carbon monoxide emission from road transportation in the Minna, Niger State. The database shows the carbon monoxide data collected. MSA Altair gas alert detector was used to take the carbon monoxide emission readings in Parts per Million for the peak and off-peak periods of vehicular movement at the road intersections. Their Global Positioning System (GPS) coordinates were recorded in the Universal Transverse Mercator (UTM). Bar chart graphs were plotted by using the emissions level of carbon dioxide as recorded on the field against the scientifically established internationally accepted safe limit of 8.7 Parts per Million of carbon monoxide in the atmosphere. Further statistical analysis was also carried out on the data recorded from the field using the Statistical Package for Social Sciences (SPSS) software and Microsoft excel to show the variance of the emission levels of each of the parameters in the study area. The results established that emissions’ level of atmospheric carbon monoxide from the road transportation in the study area exceeded the internationally accepted safe limits of 8.7 parts per million. In addition, the variations in the average emission levels of CO between the four parameters showed that morning peak is having the highest average emission level of 24.5PPM followed by evening peak with 22.84PPM while morning off peak is having 15.33 and the least is evening off peak 12.94PPM. Based on these results, recommendations made for poor air quality mitigation via carbon monoxide emissions reduction from transportation include Introduction of the urban mass transit would definitely reduce the number of traffic on the roads, hence the emissions from several vehicles that would have been on the road. This would also be a cheaper means of transportation for the masses and Encouraging the use of vehicles using alternative sources of energy like solar, electric and biofuel will also result in less emission levels as the these alternative energy sources other than fossil fuel originated diesel and petrol vehicles do not emit especially carbon monoxide.

Keywords: carbon monoxide, climate change emissions, road transportation, vehicular

Procedia PDF Downloads 360

Authors: Evangelos Kaisar, Anika Tabassum, Taraneh Ardalan, Majed Al-Ghandour

Abstract:

The economy of any country is dependent on its ability to accommodate the movement and delivery of goods. The demand for goods movement and services increases truck traffic on highways and inside the cities. The livability of most cities is directly affected by the congestion and environmental impacts of trucks, which are the backbone of the urban freight system. Better operation of heavy vehicles on highways and arterials could lead to the network’s efficiency and reliability. In many cases, roundabouts can respond better than at-level intersections to enable traffic operations with increased safety for both cars and heavy vehicles. Recently emerged, the concept of turbo-roundabout is a viable alternative to the two-lane roundabout aiming to improve traffic efficiency. The primary objective of this study is to evaluate the operation and performance level of an at-grade intersection, a conventional two-lane roundabout, and a basic turbo roundabout for freight movements. To analyze and evaluate the performances of the signalized intersections and the roundabouts, micro simulation models were developed PTV VISSIM. The networks chosen for this analysis in this study are to experiment and evaluate changes in the performance of the movement of vehicles with different geometric and flow scenarios. There are several scenarios that were examined when attempting to assess the impacts of various geometric designs on vehicle movements. The overall traffic efficiency depends on the geometric layout of the intersections, which consists of traffic congestion rate, hourly volume, frequency of heavy vehicles, type of road, and the ratio of major-street versus side-street traffic. The traffic performance was determined by evaluating the delay time, number of stops, and queue length of each intersection for varying truck percentages. The results indicate that turbo-roundabouts can replace signalized intersections and two-lane roundabouts only when the traffic demand is low, even with high truck volume. More specifically, it is clear that two-lane roundabouts are seen to have shorter queue lengths compared to signalized intersections and turbo-roundabouts. For instance, considering the scenario where the volume is highest, and the truck movement and left turn movement are maximum, the signalized intersection has 3 times, and the turbo-roundabout has 5 times longer queue length than a two-lane roundabout in major roads. Similarly, on minor roads, signalized intersections and turbo-roundabouts have 11 times longer queue lengths than two-lane roundabouts for the same scenario. As explained from all the developed scenarios, while the traffic demand lowers, the queue lengths of turbo-roundabouts shorten. This proves that turbo roundabouts perform well for low and medium traffic demand. The results indicate that turbo-roundabouts can replace signalized intersections and two-lane roundabouts only when the traffic demand is low, even with high truck volume. Finally, this study provides recommendations on the conditions under which different intersections perform better than each other.

Keywords: At-grade intersection, simulation, turbo-roundabout, two-lane roundabout

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Authors: Ruchi Sharma, Rajasekhar Balasubramanian

Abstract:

Motor vehicles emit a number of air pollutants, among which fine particulate matter (PM₂.₅) is of major concern in cities with high population density due to its negative impacts on air quality and human health. Typically, people spend more than 80% of their time indoors. Consequently, human exposure to traffic-related PM₂.₅ in indoor environments has received considerable attention. Most of the public residential buildings in tropical countries are designed for natural ventilation where indoor air quality tends to be strongly affected by the migration of air pollutants of outdoor origin. However, most of the previously reported traffic-related PM₂.₅ exposure assessment studies relied on ambient PM₂.₅ concentrations and thus, the health impact of traffic-related PM₂.₅ on occupants in naturally ventilated buildings remains largely unknown. Therefore, a systematic field study was conducted to assess indoor human exposure to traffic-related PM₂.₅ with and without mitigation measures in a typical naturally ventilated residential apartment situated near a road carrying a large volume of traffic. Three PM₂.₅ exposure scenarios were simulated in this study, i.e., Case 1: keeping all windows open with a ceiling fan on as per the usual practice, Case 2: keeping all windows fully closed as a mitigation measure, and Case 3: keeping all windows fully closed with the operation of a portable indoor air cleaner as an additional mitigation measure. The indoor to outdoor (I/O) ratios for PM₂.₅ mass concentrations were assessed and the effectiveness of using the indoor air cleaner was quantified. Additionally, potential human health risk based on the bioavailable fraction of toxic trace elements was also estimated for the three cases in order to identify a suitable mitigation measure for reducing PM₂.₅ exposure indoors. Traffic-related PM₂.₅ levels indoors exceeded the air quality guidelines (12 µg/m³) in Case 1, i.e., under natural ventilation conditions due to advective flow of outdoor air into the indoor environment. However, while using the indoor air cleaner, a significant reduction (p < 0.05) in the PM₂.₅ exposure levels was noticed indoors. Specifically, the effectiveness of the air cleaner in terms of reducing indoor PM₂.₅ exposure was estimated to be about 74%. Moreover, potential human health risk assessment also indicated a substantial reduction in potential health risk while using the air cleaner. This is the first study of its kind that evaluated the indoor human exposure to traffic-related PM₂.₅ and identified a suitable exposure mitigation measure that can be implemented in densely populated cities to realize health benefits.

Keywords: fine particulate matter, indoor air cleaner, potential human health risk, vehicular emissions

Procedia PDF Downloads 110