Search results for: traffic situation awareness

Authors: Mamatha M. N.

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Traffic problems, congested traffic, and flow management were recognized as major problems mostly in all the areas, which have caused a problem for the ambulance which carries the emergency patient. The proposed paper aims in the development of ambulance which reaches the nearby hospital faster even in heavy traffic scenario. This process is activated by implementing hardware in an ambulance as well as in traffic post thus allowing a smooth flow to the ambulance to reach the hospital in time. 1) The design of the vehicle to have a communication between ambulance and traffic post. 2)Electronic Health Record with Data-acquisition system 3)Telemetry of acquired biological parameters to the nearest hospital. Thus interfacing all these three different modules and integrating them on the ambulance could reach the hospital earlier than the present ambulance. The system is accurate and efficient of 99.8%.

Keywords: bio-telemetry, data acquisition, patient database, automatic traffic control

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Authors: Anna Dolinayova, Jozef Danis, Juraj Camaj

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The report deals with comparison of traffic accidents in Slovak republic in road and rail transport since year 2009 until 2014, with evaluation of external costs and consequently with the possibilities of their internalization. The results of road traffic accidents analysis are realized in line with after-effects they have caused; in line with main cause, place of origin (within or out of town) and in accordance to age of people they were killed or hard, eventually easy injured in traffic accidents. Evaluation of individual after-effects is carried in terms of probability of traffic accidents occurrence.

Keywords: external costs, traffic accident, rail transport, road transport

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Authors: Abdelfetah Laouzai, Rachid Ouafi

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In a traffic network, users usually choose their way so that it reduces their travel time between pairs origin-destination. This behavior might seem selfish as it produces congestions in different parts of the network. The traffic assignment problem (TAP) models the interactions between congestion and user travel decisions to obtain vehicles flows over each axis of the traffic network. The resolution methods of TAP serve as a tool allows predicting users’ distribution, identifying congesting points and affecting the travelers’ behavior in the choice of their route in the network following dynamic data. In this article, we will present a review about specific resolution approach of TAP. A comparative analysis is carried out on those approaches so that it highlights the characteristics, advantages and disadvantages of each.

Keywords: network traffic, travel decisions, approaches, traffic assignment, flows

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Authors: S. K. Hashemi, M. A. Bradford, H. R. Valipour

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The Recent collapse of bridges has raised the awareness about safety and robustness of bridges subjected to extreme loading scenarios such as intentional/unintentional blast loads. The air blast generated by the explosion of bombs or fuel tankers leads to high-magnitude short-duration loading scenarios that can cause severe structural damage and loss of critical structural members. Hence, more attentions need to put towards bridge structures to develop guidelines to increase the resistance of such structures against the probable blast. Recent advancements in numerical methods have brought about the viable and cost effective facilities to simulate complicated blast scenarios and subsequently provide useful reference for safeguarding design of critical infrastructures. In the previous studies common bridge responses to blast load, the traffic load is sometimes not included in the analysis. Including traffic load will increase the axial compression in bridge piers especially when the axial load is relatively small. Traffic load also can reduce the uplift of girders and deck when the bridge experiences under deck explosion. For more complicated structures like cable-stayed or suspension bridges, however, the effect of traffic loads can be completely different. The tension in the cables increase and progressive collapse is likely to happen while traffic loads exist. Accordingly, this study is an attempt to simulate the effect of traffic load cases on the maximum local and global response of an entire cable-stayed bridge subjected to blast loadings using LS-DYNA explicit finite element code. The blast loads ranged from small to large explosion placed at different positions above the deck. Furthermore, the variation of the traffic load factor in the load combination and its effect on the dynamic response of the bridge under blast load is investigated.

Keywords: blast, cable-stayed bridge, LS-DYNA, numerical, traffic load

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Authors: Haoyang Liang, Dandong Ge

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With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

Procedia PDF Downloads 127

Authors: Mohammad Mahbub Alam Talukder, Shahnewaz, Hasanat-E-Rabbi, Mohammed Nazrul Islam

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Road traffic accident is a global problem which is severe in the developing countries like Bangladesh. In consequence, in developing countries road trauma has now been recognized as an increasing public health hazards and economic burning issue. And after road traffic accidents the lack of management and economic costs related with health seeking behavior have a disproportionate impact on lower income groups, thus contributing to the persistence of poverty in conjunction with disability. This cross sectional study, carried out during July 2012 to June 2013, aimed to explore health seeking decision and culture of handling the road traffic accident related victims, as taken from experiences of the poor disabled people of slum dwellers of Dhaka city. The present study has been designed based on qualitative techniques such as in-depth interview and case studies. Additionally, a survey questionnaire was used to collect the demographic characteristics of the study population (n=150) and to select participants purposely for in-depth interview (n=50) and case study (n=30). Content analysis of qualitative data was done through theme coding and matrix analysis of case study was done to use relevant verbatim. Most of the time the health seeking decision totally depended on the surrounded people of the accidental place, their knowledge, awareness and remaining facility and capacity regarding proper management of the victims. However, most of the cases the victims did not get any early treatment and it took 2-12 hours to get even the first aid because of distance, shortage of money, lack of availability of getting the aid, lack of mass awareness etc. Under the reality of discriminated and unaffordable health service provision better treatment could not turn out due to economic inability of the poor victims. To avoid the severe trauma, treatment delay must be reduced by providing first aid within very short time and to do so, mass awareness campaign is necessary for handing the victims. Moreover, necessary measures should be taken to ensure cost free health service provision to treat the chronic disabled condition of the road traffic accident related poor victims.

Keywords: accident, injury, disabled, qualitative, slum

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Authors: Antonio D. Lee, Steven X. Jiang

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A variety of techniques and methods are available to evaluate cognitive performance in Urban Search and Rescue (USAR) applications. However, traditional cognitive performance evaluation techniques typically incorporate either the conscious or systematic aspect, failing to take into consideration the subconscious or intuitive aspect. This leads to incomplete measures and produces ineffective designs. In order to fill the gaps in past research, this study developed a theoretical framework to facilitate the integration of situation awareness (SA) and intuitive pattern recognition (IPR) to enhance the cognitive performance representation in USAR applications. This framework provides guidance to integrate both SA and IPR in order to evaluate the cognitive performance of the USAR responders. The application of this framework will help improve the system design.

Keywords: cognitive performance, intuitive pattern recognition, situation awareness, urban search and rescue

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Maja Čović, Josipa Bojčić, Bruna Bacalja, Gorana Jelić Mrčelić

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The appearance of the COVID-19 disease and its fast-spreading brought global pandemic and health crisis. In order to prevent the further spreading of the virus, the governments had implemented mobility restriction rules which left a negative mark on the world’s economy. Although there is numerous research on the impact of COVID-19 on marine traffic around the world, the objective of this paper is to consider the impact of COVID-19 on passenger and cargo traffic in Port of Split, in the Republic of Croatia. Methods used to make the theoretical and research part of the paper are descriptive method, comparative method, compilation, inductive method, deductive method, and statistical method. Paper relies on data obtained via Port of Split Authority and analyses trends in passenger and cargo traffic, including the year 2020, when the pandemic broke. Significant reductions in income, disruptions in transportation and traffic, as well as other maritime services are shown in the paper. This article also observes a significant decline in passenger traffic, cruising traffic and also observes the dynamic of cargo traffic inside the port of Split.

Keywords: COVID-19, pandemic, passenger traffic, ports, trends, cargo traffic

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Authors: Musthaya Patchanee

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This research aimed to study form of traffic distribution and environmental factors of road that affect traffic accidents in Dusit District, only areas responsible of Samsen Police Station. Data used in this analysis is the secondary data of traffic accident case from year 2011. Observed area units are 15 traffic lines that are under responsible of Samsen Police Station. Technique and method used are the Cartographic Method, the Correlation Analysis, and the Multiple Regression Analysis. The results of form of traffic accidents show that, the Samsen Road area had most traffic accidents (24.29%), second was Rachvithi Road (18.10%), third was Sukhothai Road (15.71%), fourth was Rachasrima Road (12.38%), and fifth was Amnuaysongkram Road (7.62%). The result from Dusit District, only areas responsible of Samsen police station, has suggested that the scale of accidents have high positive correlation with statistic significant at level 0.05 and the frequency of travel (r=0.857). Traffic intersection point (r=0.763)and traffic control equipments (r=0.713) are relevant factors respectively. By using the Multiple Regression Analysis, travel frequency is the only one that has considerable influences on traffic accidents in Dusit district only Samsen Police Station area. Also, a factor in frequency of travel can explain the change in traffic accidents scale to 73.40 (R2 = 0.734). By using the Multiple regression summation from analysis was Y ̂=-7.977+0.044X6.

Keywords: form of traffic distribution, environmental factors of road, traffic accidents, Dusit district

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Authors: Bin Wang, Jian Kang

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After years of development, the study of soundscape has been refined to the types of urban space and building. Traffic complex takes traffic function as the core, with obvious design features of architectural space combination and traffic streamline. The acoustic environment is strongly characterized by function, space, material, user and other factors. Traffic complex integrates various functions of business, accommodation, entertainment and so on. It has various forms, complex and varied experiences, and its acoustic environment is turned rich and interesting with distribution and coordination of various functions, division and unification of the mass, separation and organization of different space and the cross and the integration of multiple traffic flow. In this study, it made field recordings of each space of various traffic complex, and extracted and analyzed different acoustic elements, including changes in sound pressure, frequency distribution, steady sound source, sound source information and other aspects, to make cluster analysis of each independent traffic complex buildings. It divided complicated traffic complex building space into several typical sound space from acoustic environment perspective, mainly including stable sound space, high-pressure sound space, rhythm sound space and upheaval sound space. This classification can further deepen the study of subjective evaluation and control of the acoustic environment of traffic complex.

Keywords: soundscape, traffic complex, cluster analysis, classification

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Authors: Qiang Zhang, Xiaojian Hu

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Aiming at the problem of the existing real-time evaluation methods for traffic safety status, a video information-based urban road section traffic safety status evaluation method was established, and the rapid detection method of traffic flow parameters based on video information is analyzed. The concept of the speed dispersion of the road section that affects the traffic safety state of the urban road section is proposed, and the method of evaluating the traffic safety state of the urban road section based on the speed dispersion of the road section is established. Experiments show that the proposed method can reasonably evaluate the safety status of urban roads in real-time, and the evaluation results can provide a corresponding basis for the traffic management department to formulate an effective urban road section traffic safety improvement plan.

Keywords: intelligent transportation system, road traffic safety, video information, vehicle speed dispersion

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Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

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Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: automated external defibrillator, medical emergency, response time, unmanned aerial system

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Authors: Sang-Tae Ji, Jeong-Woo Park, Jun-Ho Park, Kwang-Woo Nam

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This study aims is to suggest the basic factors by considering the priority of intersection in the diffusion project of Smart intersection. Busan Metropolitan City is conducting a smart intersection project for efficient traffic management. The smart intersection project aims to make breakthrough improvement of the intersection congestion by optimizing the signal system using CCTV (closed-circuit television camera) image analysis technology. This study investigated trends of existing researches and analyzed by setting three things of traffic volume, characteristics of intersection road, and whether or not to conduct the main arterial road as factors for selecting new intersection when spreading smart intersection. Using this, we presented the priority of the newly installed intersection through the present situation and analysis for the Busan Metropolitan City which is the main destination of the spreading project of the smart intersection. The results of this study can be used as a consideration in the implementation of smart intersection business.

Keywords: CCTV, GIS, ICT, Smart City, smart intersection

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Authors: Asanka U. K. Godamunne

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Road traffic accidents (RTA) are a leading cause of death globally as well as in Sri Lanka and results in a large proportion of disability especially among young people. Ninety-percent of world’s road traffic deaths occur in low- and middle-income countries. The gross disparities in injury outcomes relate to immediate post-crash and hospital management. Emergency management, methods of patient transportation following road traffic accidents and safety measures are important factors to reduce mortality and morbidity. Studies in this area are limited in Sri Lanka. The main objective of this research was to assess the emergency management and proper method of transportation of road traffic accident victims. This offers the best way to explore the ways to reduce the mortality and morbidity and raise the public awareness. This study was conducted as a descriptive cross-sectional study. All the consecutive road traffic accident victims admitted to surgical wards at District General Hospital, Matale, Sri Lanka, over a period of three months were included in the study. Data from 387 victims were analyzed. The majority were in the 20-30 year age group. Seventy six percent of the patients were males. Motorcycles and trishaws were most affected. First-aid was given to only 2% of patients and it was given by non-medical persons. A significant proportion of patients (75%) were transported to the hospital by trishaws and only 1% transported by ambulance. About 86% of the patients were seated while transport and 14% were flat. Limbs and head were the most affected areas of the body. As per this study, immediate post-crash management and patient transportation were not satisfactory. There is a need to strengthen certain road safety laws and make sure people follow them.

Keywords: emergency management, patient transportation, road traffic accident victims, Sri Lanka

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Authors: Xiang Li, Jian-Qiao Sun

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As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

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Authors: Tesfaye Dagne, Dagmawit Solomon, Firmaye Bogale, Yosef Gebreyohannes, Samson Mideksa, Mamuye Hadis, Desalegn Ararso, Ermias Woldie, Tsegaye Getachew, Sabit Ababor, Zelalem Kebede

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Globally, road traffic accident (RTA) is causing millions of deaths and injuries every year. It is one of the leading causes of death among people of all age groups and the problem is worse among young reproductive age group. Moreover the problem is increasing with an increasing number of vehicles. The majority of the problem happen in low and middle income countries (LMIC), even if the number of vehicles in these countries is low compared to their population. So, the objective of this paper is to summarize the best available evidence on interventions that can reduce road traffic accidents in low and middle income countries (LMIC). Method: A rapid evidence synthesis approach adapted from the SURE Rapid Response Service was applied to search, appraise and summarize the best available evidence on effective intervention in reducing road traffic injury. To answer the question under review, we searched for relevant studies from databases including PubMed, the Cochrane Library, TRANSPORT, Health system evidence, Epistemonikos, and SUPPORT summary. The following key terms were used for searching: Road traffic accident, RTA, Injury, Reduc*, Prevent*, Minimiz*, “Low and middle-income country”, LMIC. We found 18 articles through a search of different databases mentioned above. After screening for the titles and abstracts of the articles, four of them which satisfy the inclusion criteria were included in the final review. Then we appraised and graded the methodological quality of systematic reviews that are deemed to be highly relevant using AMSTAR. Finding: The identified interventions to reduce road traffic accidents were legislation and enforcement, public awareness/education, speed control/ rumble strips, road improvement, mandatory motorcycle helmet, graduated driver license, street lighting. Legislation and Enforcement: Legislation focusing on mandatory motorcycle helmet usage, banning cellular phone usage when driving, seat belt laws, decreasing the legal blood alcohol content (BAC) level from 0.06 g/L to 0.02 g/L bring the best result where enforcement is there. Public Awareness/Education: focusing on seat belt use, child restraint use, educational training in health centers and schools/universities, and public awareness with media through the distribution of videos, posters/souvenirs, and pamphlets are effective in the short run. Speed Control: through traffic calming bumps, or speed bumps, rumbled strips are effective in reducing accidents and fatality. Mandatory Motorcycle Helmet: is associated with reduction in mortality. Graduated driver’s license (GDL): reduce road traffic injury by 19%. Street lighting: is a low-cost intervention which may reduce road traffic accidents.

Keywords: evidence synthesis, injury, rapid review, reducing, road traffic accident

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Authors: Iraj Mantegh, Charles Vidal

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This paper considers Unmanned Aircraft Systems (UAS) Traffic Management system from a service-oriented architecture point of view and proposes a framework for its performance requirements. The architecture specifically considered is related to the Remotely Piloted Aircraft Systems (RPAS) Traffic Management that is adapted by Transport Canada, in close collaboration with other jurisdictions in the United States and European Union. First, the functional performances for each individual service that comprises the Traffic Management system are defined here, and then quantitative parameters to gauge the performances of individual services are proposed.

Keywords: UAV, drone, UAS, traffic management, UTM

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Authors: Sanja Bracun, Nikolina Kasunic

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After graduation, the student population of applied sciences will become the population of employees on IT experts’ positions or "just" business users of certain IT technologies for which the level of awareness of existing cybersecurity risks is extremely important. This research results define the current cybersecurity awareness level of students at Zagreb University of Applied Sciences (TVZ), what can be useful not only for teaching staff to form a curriculum related to cybersecurity more accurately but also to employers to know what to expect from their future employees regarding cybersecurity awareness level.

Keywords: student population cybersecurity awareness, cybersecurity awareness, cybersecurity, applied sciences students

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Authors: Chih-Wei Pai, Rong-Chang Jou

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Using A1 A2 police-reported accident data for years 2003–2010 in Taiwan, the paper examines anatomic injuries and crash characteristics specific to pedestrians in “facing traffic” and “back to traffic” crashes. There were 2768 and 7558 accidents involving pedestrians walking along with/against traffic respectively. Injuries sustained by pedestrians and crash characteristics in these two crash types were compared with those in other crash types (nearside crash, nearside dart-out crash, offside crash, offside dart-out crash). Main findings include that “back to traffic” crashes resulted in more severe injuries, and pedestrians in “back to traffic” crashes had increased head, neck, and spine injuries than those in other crash types; and there was an elevated risk of head injuries in unlit darkness and NBU (non-built-up) roadways. Several crash features (e.g. unlit darkness, overtaking maneuvers, phone use by pedestrians and drivers, intoxicated drivers) appear to be over-involved in “back to traffic” crashes. The implications of the research findings regarding pedestrian/driver education, enforcement, and remedial engineering design are discussed.

Keywords: pedestrian accident, crash characteristics, injury, facing traffic, back to traffic

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

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Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: augmented reality, situation awareness, decision-making, problem-solving

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Authors: Aleksandar Jovanovic, Katarina Kukic, Ana Uzelac, Dusan Teodorovic

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Wisdom of the Crowd (WoC) is a decentralized method that uses the collective intelligence of humans. Individual guesses may be far from the target, but when considered as a group, they converge on optimal solutions for a given problem. We will utilize WoC to address the challenge of controlling traffic lights within intersections from the streets of Kragujevac, Serbia. The problem at hand falls within the category of NP-hard problems. We will employ an algorithm that leverages the swarm intelligence of bees: Bee Colony Optimization (BCO). Data regarding traffic signal timing at a single intersection will be gathered from citizens through a survey. Results obtained in that manner will be compared to the BCO results for different traffic scenarios. We will use Vissim traffic simulation software as a tool to compare the performance of bees’ and humans’ collective intelligence.

Keywords: wisdom of the crowd, traffic signal control, combinatorial optimization, bee colony optimization

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Sayed Abdul Rahman Sadaat, Nsenda Lukumwena

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Traffic congestion is a worldwide issue, especially in developing countries. This is also the case of Afghanistan, especially in Kabul-the capital city, whose rapid population growth makes it the fifth fastest growing city in the world. Traffic congestion affects not only the mobility of people and goods but also the air quality that leads to numerous deaths (3000 people) every year. There are many factors that contribute to traffic congestion. The insufficiency and inefficiency of public transportation system along with the increase of private vehicles can be considered among the most important contributing factors. This paper addresses the traffic congestion and attempts to suggest possible solutions that can help improve the current public transportation system in Kabul. To this end, the methodology used in this paper includes field work conducted in Kabul city and literature review. The outcome suggests that improving the public transportation system is likely to contribute to the reduction of traffic congestion and the improvement of air quality, thereby reducing the number of death related to air quality.

Keywords: air quality, Kabul, Afghanistan, public transportation system, improvements, traffic congestion

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Authors: Toni Raurich-Marcet, Joan Llonch-Andreu

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This research is focused on the relationship between Search Engine Marketing (SEM) and traditional advertising. The dominant assumption is that SEM does not help brand awareness and only does it in session as if it were the cost of manufacturing the product being sold. The study is methodologically developed using an experiment where the effects were determined to analyze the billboard effect. The research allowed the cross-linking of theoretical and empirical knowledge on digital marketing. This paper has validated this marketing generates retention as traditional advertising would by measuring brand awareness and its improvements. This changes the way performance and brand campaigns are split within marketing departments, effectively rebalancing budgets moving forward.

Keywords: attribution, performance marketing, SEM, marketplaces

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

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Authors: Hind Bouami

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Handling life-critical systems complexity requires to be equipped with appropriate technology and the right human agents’ functions such as knowledge, experience, and competence in problem’s prevention and solving. Human agents are involved in the management and control of human-machine system’s performance. Documenting human agent’s situation awareness is crucial to support human-machine designers’ decision-making. Knowledge about risks, critical parameters and factors that can impact and threaten automation system’s performance should be collected using preventive and retrospective approaches. This paper aims to document operators’ situation awareness through the analysis of automated organizations’ feedback. The analysis of automated hospital pharmacies feedbacks helps to identify and control critical parameters influencing human machine interaction in order to enhance system’s performance and security. Our human machine system evaluation approach has been deployed in Macon hospital center’s pharmacy which is equipped with automated drug dispensing systems since 2015. Automation’s specifications are related to technical aspects, human-machine interaction, and human aspects. The evaluation of drug delivery automation performance in Macon hospital center has shown that the performance of the automated activity depends on the performance of the automated solution chosen, and also on the control of systemic factors. In fact, 80.95% of automation specification related to the chosen Sinteco’s automated solution is met. The performance of the chosen automated solution is involved in 28.38% of automation specifications performance in Macon hospital center. The remaining systemic parameters involved in automation specifications performance need to be controlled.

Keywords: life-critical systems, situation awareness, human-machine interaction, decision-making

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Authors: Muhammad Nouman, Fahad Tiwana, Muhammad Irfan, Mohsin Tiwana

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Traffic congestion has been increasing significantly in major metropolitan areas as a result of increased motorization, urbanization, population growth and changes in the urban density. Traffic congestion compromises efficiency of transport infrastructure and causes multiple traffic concerns; including but not limited to increase of travel time, safety hazards, air pollution, and fuel consumption. Traffic management has become a serious challenge for federal and provincial governments, as well as exasperated commuters. Effective, flexible, efficient and user-friendly traffic information/database management systems characterize traffic conditions by making use of traffic counts for storage, processing, and visualization. While, the emerging data collection technologies continue to proliferate, its accuracy can be guaranteed through the comparison of observed data with the manual handheld counters. This paper presents the design of tablet based manual traffic counting application and framework for development of traffic database management system for Pakistan. The database management system comprises of three components including traffic counting android application; establishing online database and its visualization using Google maps. Oracle relational database was chosen to develop the data structure whereas structured query language (SQL) was adopted to program the system architecture. The GIS application links the data from the database and projects it onto a dynamic map for traffic conditions visualization. The traffic counting device and example of a database application in the real-world problem provided a creative outlet to visualize the uses and advantages of a database management system in real time. Also, traffic data counts by means of handheld tablet/ mobile application can be used for transportation planning and forecasting.

Keywords: manual count, emerging data sources, traffic information quality, traffic surveillance, traffic counting device, android; data visualization, traffic management

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Authors: Mona Afifi, Yara Al Qahtani, Afnan Al Dosari, Amnah Hamdi

Abstract:

Background: First aid is the care provided outside the hospital. It is important in saving lives. Delay in helping the victims may result in serious complication or even death. Many people die in Saudi Arabia because they don’t get proper first aid interventions. According to Traffic Safety council in KSA (2012), in the year of 2011 there was 7153 deaths from car accident in KAS. Subjects and method: Quasi-experimental research design was utilized to assess the effect of a structured 45-minute educational session on 82 undergraduate nursing students’ knowledge about first aid. Two tools were developed for the purpose of the current study. First tool containing the sociodemographic data including age, gender, level, and previous participation in a first aid course, and 55 statements specific to different situations that requires first aid. Concept and Knowledge of First Aid has 9 questions, cardiopulmonary resuscitation has 12 questions, Bleeding and Shock have 7 questions, Road Traffic Accidents has 5 questions, Fracture and Trauma have 4 questions, wound has 5 questions, sunstroke has 4 questions, bits and stings has 4 questions and burn has 5 questions. The second tool was to evaluate the campaign session. Result: The overall knowledge score showed significant difference between the pre and post awareness session (59.58 and 93.00 respectively, p=.000). Mean score shows significant difference in pre-tests between third and fourth year nursing students indicating that knowledge of fourth year students is higher compared to third year students with the mean knowledge scores of 69.56 and 60.88 respectively (p=0.006). Conclusion: Results of the current study indicate that the level of the knowledge in the post test session was higher than in the pre session. Also results showed that the fourth year student`s knowledge in pre-test was better compared to previous year.

Keywords: first aid, awareness campaign, undergraduate nursing students, knowledge

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

Abstract:

This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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