Search results for: transportation electrification

Authors: Oktay Celenk, Ugur Karanfil, Iskender Demir, Samir Lamrini, Jorg Neumann, Arif Demir

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Due to its favourable material characteristics, fiber reinforced plastics are amongst the main topics of all actual lightweight construction megatrends. Especially in transportation trends ranging from aeronautics over the automotive industry to naval transportation (yachts, cruise liners) the expected economic and environmental impact is huge. In naval transportation components like yacht bodies, antenna masts, decorative structures like deck lamps, light houses and pool areas represent cheap and robust solutions. Commercially available laser tools like carbon dioxide gas lasers (CO₂), frequency tripled solid state UV lasers, and Neodymium-YAG (Nd:YAG) lasers can be used. These tools have emission wavelengths of 10 µm, 0.355 µm, and 1.064 µm, respectively. The scientific goal is first of all the generation of a parameter matrix for laser processing of each used material for a Tm-fiber laser system (wavelength 2 µm). These parameters are the heat affected zone, process gas pressure, work piece feed velocity, intensity, irradiation time etc. The results are compared with results obtained with well-known material processing lasers, such as a Yb-fiber lasers (wavelength 1 µm). Compared to the CO₂-laser, the Tm-laser offers essential advantages for future laser processes like cutting, welding, ablating for repair and drilling in composite part manufacturing (components of cruise liners, marine pipelines). Some of these are the possibility of beam delivery in a standard fused silica fiber which enables hand guided processing, eye safety which results from the wavelength, excellent beam quality and brilliance due to the fiber nature. There is one more feature that is economically absolutely important for boat, automotive and military projects manufacturing that the wavelength of 2 µm is highly absorbed by the plastic matrix and thus enables selective removal of it for repair procedures.

Keywords: Thulium (Tm) fiber laser, laser processing of fiber-reinforced plastics (FRP), composite, heat affected zone

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Authors: Dermot O'Brien, Vasileios Christaras, Georgios Fontaras, Igor Nai Fovino, Ioannis Kounelis

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With the rise of the Internet of Things (IoT), 5G, and blockchain (BC) technologies, vehicles are becoming ever increasingly connected and are already transmitting substantial amounts of data to the original equipment manufacturers (OEMs) servers. This data could be used to help detect mileage fraud and enable more accurate vehicle emissions monitoring. This would not only help regulators but could enable applications such as permitting efficient drivers to pay less tax, geofencing for air quality improvement, as well as pollution tolling and trading platforms for transport-related businesses and EU citizens. Other applications could include traffic management and shared mobility systems. BC enables the transmission of data with additional security and removes single points of failure while maintaining data provenance, identity ownership, and the possibility to retain varying levels of privacy depending on the requirements of the applied use case. This research performs simulations of vehicles interacting with European member state authorities and European Commission BC nodes that are running hyperleger fabric and explores whether the technology is currently feasible for transport applications such as the emission monitoring use-case.

Keywords: future transportation systems, technological innovations, policy approaches for transportation future, economic and regulatory trends, blockchain

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Authors: Eric Neidhardt

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A well-functioning public transport system that is accepted and used by the general population contributes a lot to a sustainable city. Especially young and elderly people rely on public transport to get to work, go shopping, visit a doctor, and take advantage of entertainment options. The sustainability of a public transport system can be considered from different points of view. In urban areas, acceptance is particularly important. As many people as possible should use public transport and not their private vehicle. This reduces traffic jams and increases air quality. In rural areas, the cost efficiency of public transport is especially important. Longer distances and a low population density mean that these modes of transportation can rarely be used cost-effectively. It is crucial to avoid a low utilization, because empty rides are neither sustainable nor cost-effective. With a demand-oriented approach, we try to both improve flexibility and therefore attractiveness for the user and improve cost- efficiency. The vehicles only operate when they are needed and only where they are needed. Empty rides are avoided to improve sustainability. In the subproject "Autonomous public driving" of the project RealLabHH, such a system was implemented and tested in Hamburg-Bergedorf, a suburb of Hamburg. In this paper, some of the steps necessary for this are considered from a technical point of view, and problems that arose in real-life use are addressed.

Keywords: public transport, demand-oriented, autonomous driving, RealLabHH

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Authors: Cihat Aşan

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Istanbul Strait is a crucial and narrow waterway, not only having a role in linking two continents but also has a crossover mission for the petroleum, which is the biggest energy resource, between its supply and demand sources. Besides its substantial features, sensitivities like around 18 million populations in surroundings, military facilities, ports, oil lay down areas etc. also brings the high risk to use of Istanbul Strait. Based on the statistics of Turkish Ministry of Transportation, Maritime and Communication, although the number of vessel passage in Istanbul Strait is declining, tonnage of hazardous and flammable cargo like oil and chemical transportation is increasing and subsequently the risk of oil pollution, loss of life and property is also rising. Based on the mentioned above; it is crucial to be prepared for the initial and subsequent response to eventual ship sourced oil spill which may cause to block the Strait for an unbearable duration. In this study; preconditioned Istanbul Strait sensitive areas studies has been taken into account and possible oil spill scenario is loaded to PISCES 2 (Potential Incident Simulation Control and Evaluation System) decision support system for the determined specific sea area. Consequences of the simulation like oil expanding process, required number and types of assets to response, had in hand and evaluated.

Keywords: Istanbul strait, oil spill, PISCES simulator, initial response

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Authors: Pornpimol Chaiwuttisak, Honora Smith, Yue Wu

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Blood is a perishable product which suffers from physical deterioration with specific fixed shelf life. Although its value during the shelf life is constant, fresh blood is preferred for treatment. However, transportation costs are a major factor to be considered by administrators of Regional Blood Centres (RBCs) which act as blood collection and distribution centres. A trade-off must therefore be reached between transportation costs and short-term holding costs. In this paper we propose a number of algorithms for online allocation and routing of blood supplies, for use in conditions of variable and insufficient blood supply. A case study in northern Thailand provides an application of the allocation and routing policies tested. The plan proposed for daily allocation and distribution of blood supplies consists of two components: firstly, fixed routes are determined for the supply of hospitals which are far from an RBC. Over the planning period of one week, each hospital on the fixed routes is visited once. A robust allocation of blood is made to hospitals on the fixed routes that can be guaranteed on a suitably high percentage of days, despite variable supplies. Secondly, a variable daily route is employed for close-by hospitals, for which more than one visit per week may be needed to fulfil targets. The variable routing takes into account the amount of blood available for each day’s deliveries, which is only known on the morning of delivery. For hospitals on the variables routes, the day and amounts of deliveries cannot be guaranteed but are designed to attain targets over the six-day planning horizon. In the conditions of blood shortage encountered in Thailand, and commonly in other developing countries, it is often the case that hospitals request more blood than is needed, in the knowledge that only a proportion of all requests will be met. Our proposal is for blood supplies to be allocated and distributed to each hospital according to equitable targets based on historical demand data, calculated with regard to expected daily blood supplies. We suggest several policies that could be chosen by the decision makes for the daily distribution of blood. The different policies provide different trade-offs between transportation and holding costs. Variations in the costs of transportation, such as the price of petrol, could make different policies the most beneficial at different times. We present an application of the policies applied to a realistic case study in the RBC at Chiang Mai province which is located in Northern region of Thailand. The analysis includes a total of more than 110 hospitals, with 29 hospitals considered in the variable route. The study is expected to be a pilot for other regions of Thailand. Computational experiments are presented. Concluding remarks include the benefits gained by the online methods and future recommendations.

Keywords: online algorithm, blood distribution, developing country, insufficient blood supply

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Authors: Ida Zubaidah

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With the advancement of information and communication technologies, in many cases, geographical distance is no longer considered as a main barrier in distance education. Geographical distance, even from a continent to another, between students and their instructor or students and their campus can be connected by the Internet, telephone or any other means of communication technology. Managing distance learning in an archipelagic country like Indonesia, however, has some different stories. Comprising more than 17,000 islands and 6.000 of them inhabited, Indonesia is considered as one of the most archipelagic countries in the world. In some areas or islands that have adequate public transportation and communication facilities the courses can be delivered quite well. In other areas that geographically very remote and dispersed islander, Universitas Terbuka, an open university in Indonesia, has to have very different strategies in overcoming the specific and even emergency situations in learning delivery. This ongoing research paper aims to share experiences of how Universitas Terbuka makes serious and unique efforts in overcoming the barriers and obstacles in providing educational service in part of difficult areas, especially in eastern areas of Indonesia. The data collection methods are observation of sample areas and in-depth interview with the head of regional offices of Universitas Terbuka in eastern Indonesia, staff, and tutors. Conducting educational deliveries in in difficult areas with no regular and adequate transportation has made the regional office have specific strategies in making the learning process run as smooth as possible. Sending a tutor to an area to meet some students and conducting a series of tutorial, which are supposed to be weekly, in several days is one of the strategies. Recruiting local people to manage the students in the area is another strategy. The absence of regular transportation from island to island, high tides, hurricanes, are among the obstacles faced by the regional offices in doing their job. Non geographical barriers such as unavailability of qualified tutor, inadequate tutor payment, are problems as well. The learning process, however, has to be done in any way, otherwise the distance education mission to reach unreachable cannot be achieved.

Keywords: distance education, Terbuka University, difficult area, geographical barrier, learning services

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Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Engineer Dilnawaz Shah

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Solid Waste Management (SWM) is perhaps one of the most important elements constituting the environmental health and sanitation of the urban developing sector. The management system has several components that are integrated as well as interdependent; thus, the efficiency and effectiveness of the entire system are affected when any of its functional components fails or does not perform up to the level mark of operation. Sindh Solid Waste Management Board (SSWMB) is responsible for the management of solid waste in the entire city. There is a need to adopt the engineered approach in the redesigning of the existing system. In most towns, street sweeping operations have been mechanized and done by machinery operated by vehicles. Construction of Garbage Transfer Stations (GTS) at a number of locations within the city will cut the cost of transportation of waste to disposal sites. Material processing, recovery of recyclables, compaction, volume reduction, and increase in density will enable transportation of waste to disposal sites/landfills via long vehicles (bulk transport), minimizing transport/traffic and environmental pollution-related issues. Development of disposal sites into proper sanitary landfill sites is mandatory. The transportation mechanism is through garbage vehicles using either hauled or fixed container systems employing crew for mechanical or manual loading. The number of garbage vehicles is inadequate, and due to comparatively long haulage to disposal sites, there are certain problems of frequent vehicular maintenance and high fuel costs. Foreign investors have shown interest in enterprising improvement schemes and proposed operating a solid waste management system in Karachi. The waste to Energy option is being considered to provide a practical answer to be adopted to generate power and reduce waste load – a two-pronged solution for the increasing environmental problem. The paper presents results and analysis of a recent study into waste generation and characterization probing into waste-to-energy options for Karachi City.

Keywords: waste to energy option, integrated approach, solid waste management, physical and chemical composition of waste in Karachi

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Authors: Adedayo Ajayi, Patrick Luk, Liyun Lao

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This paper studies the supportive needs for the electrical infrastructure of the green airport. In particular, the core objective revolves around the choice of electric grid configuration required to meet the expected electrified loads, i.e., the taxiing and charging loads of hybrid /pure electric aircraft in the airport. Further, reliability and resilience are critical aspects of a newly proposed grid; the concept of mobile energy storage as energy as a service (EAAS) for grid support in the proposed green airport is investigated using an autonomous electric taxiing robot (A-ETR) at a case study (Cranfield Airport). The performance of the model is verified and validated through DigSILENT power factory simulation software to compare the networks in terms of power quality, short circuit fault levels, system voltage profile, and power losses. Contingency and reliability index analysis are further carried out to show the potential of EAAS on the grid. The results demonstrate that the low voltage a.c network ( LVAC) architecture gives better performance with adequate compensation than the low voltage d.c (LVDC) microgrid architecture for future green airport electrification integration. And A-ETR can deliver energy as a service (EaaS) to improve the airport's electrical power system resilience and energy supply.

Keywords: reliability, voltage profile, flightpath 2050, green airport

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Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

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Authors: A. J. Francisco, K. C. Gallosa, R. J. Gasacao, J. R. Ros, B. J. Viado

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The study focuses on the use of quality indicators (QI)s based on the standards made by the (IFCC), that could effectively identify and minimize errors occurring throughout the total testing process (TTP), in order to improve patient safety. The study was conducted through a survey questionnaire that was given to a random sample of 19 respondents (eight privately-owned and eleven government-owned hospitals), mainly CMTs, MTs, and Supervisors from UST-affiliated hospitals. The pre-analytical laboratory errors, which include misidentification errors, transcription errors, sample collection errors and sample handling and transportation errors, were considered as variables according to the IFCC WG-LEPS. Data gathered were analyzed using the Mann-Whitney U test, Percentile, Linear Regression, Percentage, and Frequency. The laboratory performance of both hospitals is High level. There is no significant difference between the laboratory performance between the two stated variables. Moreover, among the four QIs, sample handling and transportation errors contributed most to the difference between the two variables. Outcomes indicate satisfactory performance between both variables. However, in order to ensure high-quality and efficient laboratory operation, constant vigilance and improvements in pre-analytical QI are still needed. Expanding the coverage of the study, the inclusion of other phases, utilization of parametric tests are recommended.

Keywords: pre-analytical phase, quality indicators, laboratory performance, pre-analytical error

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Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

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Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

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Authors: Mohammad Idrees Yusofzai, Hirobata Yasuhiro, Matsuo Kojiro

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Kabul is the capital of Afghanistan. It is the focal point of educational, industrial, etc. of Afghanistan. Additionally, the population of Kabul has grown recently and will increase because of return of refugees and shifting of people from other province to Kabul city. However, this increase in population, the issues of urban congestion and other related problems of urban transportation in Kabul city arises. One of the problems is public transport (large buses) service and needs to be modified and enhanced especially large bus routes that are operating in each zone of the 22 zone of Kabul City. To achieve the above mentioned goal of improving public transport, Spatial Accessibility Analysis is one of the important attributes to assess the effectiveness of transportation system and urban transport policy of a city, because accessibility indicator as an alternative tool to support public policy that aims the reinforcement of sustainable urban space. The case study of this research compares the present model (present bus route) and the modified model of public transport. Furthermore, present model, the bus routes in most of the zones are active, however, with having low frequency and unpublished schedule, and accessibility result is analyzed in four cases, based on the variables of accessibility. Whereas in modified model all zones in Kabul is taken into consideration with having specified origin and high frequency. Indeed the number of frequencies is kept high; however, this number is based on the number of buses Millie Bus Enterprise Authority (MBEA) owns. The same approach of cases is applied in modified model to figure out the best accessibility for the modified model. Indeed, the modified model is having a positive impact in congestion level in Kabul city. Besides, analyses of person trip and trip distribution have been also analyzed because how people move in the study area by each mode of transportation. So, the general aims of this research are to assess the present movement of people, identify zones in need of public transport and assess equity level of accessibility in Kabul city. The framework of methodology used in this research is based on gravity analysis model of accessibility; besides, generalized cost (time) of travel and travel mode is calculated. The main data come from person trip survey, socio-economic characteristics, demographic data by Japan International Cooperation Agency, 2008, study of Kabul city and also from the previous researches on travel pattern and the remaining data regarding present bus line and routes have been from MBEA. In conclusion, this research explores zones where public transport accessibility level is high and where it is low. It was found that both models the downtown area or central zones of Kabul city is having high level accessibility. Besides, the present model is the most unfavorable compared with the modified model based on the accessibility analysis.

Keywords: accessibility, bus generalized cost, gravity model, public transportation network

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Authors: Umar Hayatu Sidik

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Application of liquid base petroleum fuel (petrol and diesel) for transportation fuel causes emissions of greenhouse gases (GHGs), while natural gas (NG) reduces the emissions of greenhouse gases (GHGs). At present, compression and liquefaction are the most matured technology used for transportation system. For transportation use, compression requires high pressure (200–300 bar) while liquefaction is impractical. A relatively low pressure of 30-40 bar is achievable by adsorbed natural gas (ANG) to store nearly compressed natural gas (CNG). In this study, adsorbents for high-pressure adsorption of methane (CH4) was prepared from coconut shells and polyetheretherketone (PEEK) using potassium hydroxide (KOH) and microwave-assisted activation. Design expert software version 7.1.6 was used for optimization and prediction of preparation conditions of the adsorbents for CH₄ adsorption. Effects of microwave power, activation time and quantity of PEEK on the adsorbents performance toward CH₄ adsorption was investigated. The adsorbents were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric (TG) and derivative thermogravimetric (DTG) and scanning electron microscopy (SEM). The ideal CH4 adsorption capacities of adsorbents were determined using volumetric method at pressures of 5, 17, and 35 bar at an ambient temperature and 5 oC respectively. Isotherm and kinetics models were used to validate the experimental results. The optimum preparation conditions were found to be 15 wt% amount of PEEK, 3 minutes activation time and 300 W microwave power. The highest CH4 uptake of 9.7045 mmol CH4 adsorbed/g adsorbent was recorded by M33P15 (300 W of microwave power, 3 min activation time and 15 wt% amount of PEEK) among the sorbents at an ambient temperature and 35 bar. The CH4 equilibrium data is well correlated with Sips, Toth, Freundlich and Langmuir. Isotherms revealed that the Sips isotherm has the best fit, while the kinetics studies revealed that the pseudo-second-order kinetic model best describes the adsorption process. In all scenarios studied, a decrease in temperature led to an increase in adsorption of both gases. The adsorbent (M33P15) maintained its stability even after seven adsorption/desorption cycles. The findings revealed the potential of coconut shell-PEEK as CH₄ adsorbents.

Keywords: adsorption, desorption, activated carbon, coconut shells, polyetheretherketone

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Authors: Gabriella Fardhiyanti, Victor Wee

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Air connectivity is the crucial factors to boost a region economics growth. It will open the accessibility to support regional competitiveness and helps to achieve ASEAN (Association of Southeast Asian Nations) integration in term of economic integration, business investment, promote intra-regional trade, and creates the sense of belongingness among ASEAN people in the region. An increasing number of air connectivity and transportation will be benefiting the region because air transportation is a vital hub for ASEAN. The aim of this paper is to address the importance of air connectivity in promoting ASEAN Integration, by focusing on the ASEAN vision for a more integrated region. The assessment uses based on the Netscan Air connectivity model based on the flight destination and airport connectivity index, further analysis present that air connectivity significantly influence ASEAN tourism sector. Follow by the implications of open skies policy for the liberation of the aviation industry and the growth of low cost-carriers (LCCs) in the region. This paper provides recommendation and strategy for overcoming the challenges faced by ASEAN to boost ASEAN tourism integration successfully. The findings can assist in guiding policy and industry stakeholders in the future decision relating to air liberalization and more integrated system in the region.

Keywords: air connectivity, ASEAN integration, low-cost carries, NetScan connectivity model, open skies policy

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Authors: Margareth Guimaraes Lima, Marilisa Berti A. Barros, Deborah Carvalho Malta

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The relationship between physical activity (PA) and depression has been investigated, in both, observational and clinical studies: PA can integrate the treatments for depression; the physical inactivity (PI) may contribute to increase depression symptoms; and on the other hand, emotional problems can decrease PA. The main of this study was analyze the association among leisure and transportation PI and time watching television (TV) according to depression (minor and major), evaluated with the Patient Health Questionnaire (PHQ-9). The association was also analyzed by gender. This is a cross-sectional study. Data were obtained from the National Health Survey 2013 (PNS), performed with representative sample of the Brazilian adult population, in 2013. The PNS collected information from 60,202 individuals, aged 18 years or more. The independent variable were: leisure time physical inactivity (LTPI), considering inactive or insufficiently actives (categories were linked for analyzes), those who do not performed a minimum of 150 or 74 minutes of moderate or vigorous LTPA, respectively, by week; transportation physical inactivity (TPI), individuals who did not reached 150 minutes, by week, travelling by bicycle or on foot to work or other activities; daily time watching TV > 5 hours. The principal independent variable was depression, identified by PHQ-9. Individuals were classified with major depression, with > 5 symptoms, more than seven days, but one of the symptoms was “depressive mood” or “lack of interest or pleasure”. The others had minor depression. The variables used to adjustment were gender, age, schooling and chronic disease. The prevalence of LTPI, TPI and TV time were estimated according to depression, and differences were tested with Chi-Square test. Adjusted prevalence ratios were estimated using multiple Poisson regression models. The analyzes also had stratification by gender. Mean age of the studied population was 42.9 years old (CI95%:42.6-43.2) and 52.9% were women. 77.5% and 68.1% were inactive or insufficiently active in leisure and transportation, respectively and 13.3% spent time watching TV 5 > hours. 6% and 4.1% of the Brazilian population were diagnosed with minor or major depression. LTPI prevalence was 5% and 9% higher among individuals with minor and major depression, respectively, comparing with no depression. The prevalence of TPI was 7% higher in those with major depression. Considering larger time watching TV, the prevalence was 45% and 74% higher among those with minor and major depression, respectively. Analyzing by gender, the associations were greater in men than women and TPI was note be associated, in women. The study detected the higher prevalence of leisure time physical inactivity and, especially, time spent watching TV, among individuals with major and minor depression, after to adjust for a number of potential confounding factors. TPI was only associated with major disorders and among men. Considering the cross-sectional design of the research, these associations can point out the importance of the mental problems control of the population to increase PA and decrease the sedentary lifestyle; on the other hand, the study highlight the need of interventions by encouraging people with depression, to practice PA, even to transportation.

Keywords: depression, physical activity, PHQ-9, sedentary lifestyle

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Authors: Nalinee B. Suryawanshi, Vinay M. Bhandari, Laxmi Gayatri Sorokhaibam, Vivek V. Ranade

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Deep desulphurization of transportation fuels is a major environmental concern all over the world and recently prescribed norms for the sulphur content require below 10 ppm sulphur concentrations in fuels such as diesel and gasoline. The existing technologies largely based on catalytic processes such as hydrodesulphurization, oxidation require newer catalysts and demand high cost of deep desulphurization whereas adsorption based processes have limitations due to lower capacity of sulphur removal. The present work is an attempt to provide alternatives for the existing methodologies using a newer non-catalytic process based on hydrodynamic cavitation. The developed process requires appropriate combining of organic and aqueous phases under ambient conditions and passing through a cavitating device such as orifice, venturi or vortex diode. The implosion of vapour cavities formed in the cavitating device generates (in-situ) oxidizing species which react with the sulphur moiety resulting in the removal of sulphur from the organic phase. In this work, orifice was used as a cavitating device and deep desulphurization was demonstrated for removal of thiophene as a model sulphur compound from synthetic fuel of n-octane, toluene and n-octanol. The effect of concentration of sulphur (up to 300 ppm), nature of organic phase and effect of pressure drop (0.5 to 10 bar) was discussed. A very high removal of sulphur content of more than 90% was demonstrated. The process is easy to operate, essentially works at ambient conditions and the ratio of aqueous to organic phase can be easily adjusted to maximise sulphur removal. Experimental studies were also carried out using commercial diesel as a solvent and the results substantiate similar high sulphur removal. A comparison of the two cavitating devices- one with a linear flow and one using vortex flow for effecting pressure drop and cavitation indicates similar trends in terms of sulphur removal behaviour. The developed process is expected to provide an attractive environmental engineering alternative for deep desulphurization of transportation fuels.

Keywords: cavitation, petroleum, separation, sulphur removal

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Authors: Leah Wright, Trevor Townsend

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Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

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Authors: Maslan Lamria, Ralph E. H. Sims, Tatang H. Soerawidjaja

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In increasing its self-sufficiency on transportation fuel, Indonesia is currently developing commercial production and use of drop-in biofuel (DBF) from vegetable oil. To maximize the level of success, it is necessary to get insights on how the implementation would develop as well as any important factors. This study assessed the dynamics of transition from existing fossil fuel system to a renewable fuel system, which involves the transition from existing biodiesel to projected DBF. A systems dynamics approach was applied and a model developed to simulate the dynamics of liquid biofuel transition. The use of palm oil feedstock was taken as a case study to assess the projected DBF implementation by 2045. The set of model indicators include liquid fuel self-sufficiency, liquid biofuel share, foreign exchange savings and green-house gas emissions reduction. The model outputs showed that supports on DBF investment and use play an important role in the transition progress. Given assumptions which include application of a maximum level of supports over time, liquid fuel self-sufficiency would be still unfulfilled in which palm biofuel contribution is 0.2. Thus, other types of feedstock such as algae and oil feedstock from marginal lands need to be developed synergically. Regarding support on DBF use, this study recommended that removal of fossil subsidy would be necessary prior to applying a carbon tax policy effectively.

Keywords: biofuel, drop-in biofuel, energy transition, liquid fuel

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Authors: M. Taghavi Zavareh, H. Saremi

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Railway transportation is one of the types of transportation systems which, due to the advantages such as the ability to transport a large number of passengers, environmental protection, low energy consumption, and contribution to tourism, has importance. The existence of suitable and accessible stations is one of the requirements that leads to better performance and plays a significant role in the economic, social, political, and cultural development of urban areas. This paper aims to propose a framework for locating railway passenger stations. This research used descriptive-analytical methods and library tools to answer which definitions and theoretical approaches are suitable for the location of railway passenger stations. The results showed that theoretical approaches such as Transit-Oriented Development and Urban Regeneration are of the utmost importance theoretical bases in the field of research. Moreover, we studied three stations in Iran to find out about real trends and criteria in this research. This study also proposed four major criteria including accessibility, development, rail related and economics, and environmental harmony. Ultimately with an emphasis on the proposed criteria, the study concludes that the combination of Transit-Oriented Development and Urban Regeneration is the most suitable framework to locate railway passenger stations.

Keywords: railway passenger station, railway station, site selection, transit-oriented development, urban regeneration

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Authors: Eric Wilson Santos Cabral, Marta Monteiro Da Costa Cruz, Fabio Luis Maciel Machado, Henrique Andrade, Rodrigo Pirola Pestana, Vivian Andrea Parreira

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The large variation in the price of diesel in Brazil directly affects the variable cost of companies operating in the transportation sector. In rail transport, the great challenge is to overcome the annual budget, cargo and ore transported with cost reduction in relation to previous years, becoming more efficient every year. Some effective measures are necessary to achieve the reduction of the liter ratio consumed by KTKB (Gross Ton per Kilometer multiplied by thousand). This acronym represents the indicator of energy efficiency of some railroads in the world. This study is divided into two parts: the first, to identify using statistical tools, part of the controlled variables in the railways, which have a correlation with the energy efficiency indicator, seeking to aid decision-making. The second, with the use of the train dynamics simulator, within scenarios defined in the operational reality of a railroad, seeks to optimize the train formations and the train stop model for the change of train drivers. With the completion of the study, companies in the rail sector are expected to be able to reduce some of their transportation costs.

Keywords: railway transport, railway simulation, energy efficiency, fuel consumption

Procedia PDF Downloads 318

Authors: Samet Sen, Yalcin Alver

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Before Izmir Commuter Rail System (IZBAN), most of the respondents along the railway were making their trips by city buses, minibuses or private cars. After IZBAN was put into service, some people changed their previous trip behaviors and they started travelling by IZBAN. Therefore a big travel demand in IZBAN occurred. In this study, the characteristics of passengers and their trip behaviors are found out based on the longitudinal data conducted via two wave trip surveys. Just after one year from IZBAN's opening, the first wave of the surveys was carried out among 539 passengers at six stations during morning peak hours between 07.00 am-09.30 am. The second wave was carried out among 669 passengers at the same six stations two years after the first wave during the same morning peak hours. As a result of this study, the respondents' socio-economic specifications, the distribution of trips by region, the impact of IZBAN on transport modes, the changes in travel time and travel cost and satisfaction data were obtained. These data enabled to compare two waves and explain the changes in socio-economic factors and trip behaviors. In both waves, 10 % of the respondents stopped driving their own cars and they started to take IZBAN. This is an important development in solving traffic problems. More public transportation means less traffic congestion.

Keywords: commuter rail system, comparative study, longitudinal survey, public transportation

Procedia PDF Downloads 414

Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: M. Baldini, H. K. Jacobsen, M. Jaccard

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In light of the international efforts to comply with the Paris agreement and emission targets for future energy systems, Denmark and Canada are among the front-runner countries dealing with climate change. The experiences in the energy sector have seen both countries coping with trade-offs between investments in renewable energy technologies and energy efficiency, thus tackling the climate issue from the supply and demand side respectively. On the demand side, the industrial sector is going through a remarkable transformation, with implementation of energy efficiency measures, change of input fuel for end-use processes and forecasted electrification as main features under the spotlight. By looking at Canada and Denmark's experiences as pathfinders on the demand and supply approach to climate change, it is possible to obtain valuable experience that may be applied to other countries aiming at the same goal. This paper presents a comparative study on industrial energy efficiency between Canada and Denmark. The study focuses on technologies and system options, policy design and implementation and modelling methodologies when implementing industrial energy savings in optimization models in comparison to simulation models. The study identifies gaps and junctures in the approach towards climate change actions and, learning from each other, lessen the differences to further foster the adoption of energy efficiency measurements in the industrial sector, aiming at reducing energy consumption and, consequently, CO₂ emissions.

Keywords: industrial energy efficiency, comparative study, CO₂ reduction, energy system modelling

Procedia PDF Downloads 153

Authors: F. Tang, S. Boskovich, A. Raheja, Z. Aliyazicioglu, S. Bhandari, N. Tsuchiya

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Calpoly Autonomous Transportation Experience (CATE) is a driverless vehicle that we are developing to provide safe, accessible, and efficient transportation of passengers throughout the Cal Poly Pomona campus for events such as orientation tours. Unlike the other self-driving vehicles that are usually developed to operate with other vehicles and reside only on the road networks, CATE will operate exclusively on walk-paths of the campus (potentially narrow passages) with pedestrians traveling from multiple locations. Safety becomes paramount as CATE operates within the same environment as pedestrians. As driverless vehicles assume greater roles in today’s transportation, this project will contribute to autonomous driving with pedestrian traffic in a highly dynamic environment. The CATE project requires significant interdisciplinary work. Researchers from mechanical engineering, electrical engineering and computer science are working together to attack the problem from different perspectives (hardware, software and system). In this abstract, we describe the software aspects of the project, with a focus on the requirements and the major components. CATE shall provide a GUI interface for the average user to interact with the car and access its available functionalities, such as selecting a destination from any origin on campus. We have developed an interface that provides an aerial view of the campus map, the current car location, routes, and the goal location. Users can interact with CATE through audio or manual inputs. CATE shall plan routes from the origin to the selected destination for the vehicle to travel. We will use an existing aerial map for the campus and convert it to a spatial graph configuration where the vertices represent the landmarks and edges represent paths that the car should follow with some designated behaviors (such as stay on the right side of the lane or follow an edge). Graph search algorithms such as A* will be implemented as the default path planning algorithm. D* Lite will be explored to efficiently recompute the path when there are any changes to the map. CATE shall avoid any static obstacles and walking pedestrians within some safe distance. Unlike traveling along traditional roadways, CATE’s route directly coexists with pedestrians. To ensure the safety of the pedestrians, we will use sensor fusion techniques that combine data from both lidar and stereo vision for obstacle avoidance while also allowing CATE to operate along its intended route. We will also build prediction models for pedestrian traffic patterns. CATE shall improve its location and work under a GPS-denied situation. CATE relies on its GPS to give its current location, which has a precision of a few meters. We have implemented an Unscented Kalman Filter (UKF) that allows the fusion of data from multiple sensors (such as GPS, IMU, odometry) in order to increase the confidence of localization. We also noticed that GPS signals can easily get degraded or blocked on campus due to high-rise buildings or trees. UKF can also help here to generate a better state estimate. In summary, CATE will provide on-campus transportation experience that coexists with dynamic pedestrian traffic. In future work, we will extend it to multi-vehicle scenarios.

Keywords: driverless vehicle, path planning, sensor fusion, state estimate

Procedia PDF Downloads 128

Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

Procedia PDF Downloads 275

Authors: Sridhar S, Govinda Raj Mandela, Aruna Mangalpady

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In the present day scenario, Indian underground mines are moving towards full scale mechanisation for improvement of production and productivity levels. These mines are employing a wide variety of earth moving machines for the transportation of ore and overburden (waste). Low Profile Dump Trucks (LPDTs) have proven more advantageous towards improvement of production levels in underground mines through quick transportation. During the operation of LPDT, different kinds of vibrations are generated which can affect the health condition of the operator. Keeping this in view, the present research work focuses on measurement and evaluation of Hand Arm Vibrations (HAVs) from the steering system of LPDTs. The study also aims to evaluate the HAVs of different job components of a work cycle in operating LPDTs. The HAVs were measured and evaluated according to ISO 5349-2: 2001 standards, and the daily vibration exposures A(8) were calculated. The evaluated A(8) results show that LPDTs of 60 and 50 tons capacity have vibration levels more than that of the Exposure Action Value (EAV) of 2.5 m/s2 in every job component of the work cycle. Further, the results show that the vibration levels were more during empty haulage especially during descending journey when compared to other job components in all LPDTs considered for the study.

Keywords: low profile dump trucks, hand arm vibrations, exposure action value, underground mines

Procedia PDF Downloads 117

Authors: H. N. S. Silva, S. N. Silva

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Introduction: The latest WHO data published in 2014 states that Sri Lanka has reached 2,773 of total deaths and over 14000 individuals’ sustained injuries due to RTAs each year. It was noticed in previous studies that policemen, three wheel drivers and also pedestrians were the first to respond to RTAs but the victim’s condition was aggravated due to unskilled attempts made by the responders while management of the victim’s wounds, moving and positioning of the victims and also mainly while transportation of the victims. Objective: To observe the practices of the urban public in Sri Lanka who are encountered with RTAs. Methods: A qualitative study was done to analyze public behavior seen on video recordings of scenes of accidents purposefully selected from social media, news websites, YouTube and Google. Results: The results showed that all individuals who tried to help during the RTA were middle aged men, who were mainly pedestrians, motorcyclists and policemen during that moment. Vast majority were very keen to actively help the victims to get to hospital as soon as possible and actively participated in providing 'aid'. But main problem was the first aid attempts were disorganized and uncoordinated. Even though all individuals knew how to control external bleeding, none of them was aware of spinal prevention techniques or management of limb injuries. Most of the transportation methods and transfer techniques used were inappropriate and more injury prone. Conclusions: The public actively engages in providing aid despite their inappropriate practices in giving first aid.

Keywords: encountered, pedestrians, road traffic accidents, urban public

Procedia PDF Downloads 268

Authors: Ma Lanting, S. Eguilior, A. Hurtado, Juan F. Llamas Borrajo

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Horizontal hydraulic fracturing is a technology to increase natural gas flow and improve productivity in the low permeability formation. During this drilling operation tons of flowback and produced water which contains many organic compounds return to the surface with a potential risk of influencing the surrounding environment and human health. A mathematical model is urgently needed to represent organic compounds in water transportation process behavior and the concentration change with time throughout the hydraulic fracturing operation life cycle. A comprehensive model combined Organic Matter Transport Dynamic Model with Two-Compartment First-order Model Constant (TFRC) Model has been established to quantify the organic compounds concentration. This algorithm model is composed of two transportation parts based on time factor. For the fast part, the curve fitting technique is applied using flowback water data from the Marcellus shale gas site fracturing and the coefficients of determination (R2) from all analyzed compounds demonstrate a high experimental feasibility of this numerical model. Furthermore, along a decade of drilling the concentration ratio curves have been estimated by the slow part of this model. The result shows that the larger value of Koc in chemicals, the later maximum concentration in water will reach, as well as all the maximum concentrations percentage would reach up to 90% of initial concentration from shale formation within a long sufficient period.

Keywords: model, shale gas, concentration, organic compounds

Procedia PDF Downloads 207

Authors: Sai Rajeev Reddy, Ishita Roy, M. Anji Reddy

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The paper describes the importance of preventive measures and immediate Emergency logistics during accidents and unfortunate Disasters for the Hyderabad Metro Rails in their various stages of construction. This is the need of the modern generation where accidents, explosions, attacks and sudden crisis are frequent casualties which take huge tolls of life in the present world. The paper utilizes the workflow and application of Geographical information System (GIS) to provide information about problems and crisis structures for efficient Metro Transportation in the city. The study analyzes the difficulties and problems which cause accidents during operation and maintenance stages of the Metro Rail. The paper focuses upon the intermediate and firsthand information of Crisis with the help of GIS technology to share Disaster data for effective measures by the Cyber Police stations, Emergency Responders, Hospitals and First Aid Centre to act immediately and save lives. The results and conclusions have nevertheless proved very informative and useful for the safety board authorities of the Hyderabad Metro Rail. The operation and Maintenance are integral stages in the development of any Multipurpose transportation Projects and are usually prone to various Disasters and tragedies. Hence, the GIS technologies help in distribution of information among the masses with the web Technologies and advanced software developed to prevent and manage crisis widely and in a cost-benefits manner.

Keywords: Geographical Information System, emergency assessment, accident zones, surveillance

Procedia PDF Downloads 552