Search results for: road transportation

Authors: Dmitrii Glushkov, Aleksandr G. Nigay, Olga S. Yashutina

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In recent years, due to the intensive development of the Arctic and Antarctic areas, the actual task is to develop technology for the effective utilization of solid and liquid combustible wastes in an environment with low temperatures. Firstly, such technology will help to prevent the dumping of waste into the World Ocean and reduce the risks of causing environmental damage to the Far North areas. Secondly, promising actions will help to prepare fuel compositions from the waste in the places of their production. Such kind of fuels can be used as energy resources. It will reduce waste utilization costs when transporting them to the mainland. In the present study, we suggest a solution to the problem of waste utilization by the preparation of gel fuels based on solid and liquid combustible components with the addition of the thickener. Such kind of fuels is characterized by ease of preparation, storage, transportation and use (as energy resources). The main regularities and characteristics of physical and chemical processes are established with varying parameters of gel fuels and heating sources in wide ranges. The obtained results let us conclude about the prospects of gel fuels practical application for combustible wastes utilization. Appropriate technology will be characterized by positive environmental, operational and economic effects. The composition of the gel fuels can vary in a wide range. The fuels preparation based on one type of a combustible liquid or a several liquids mixture with the finely dispersed components addition makes it possible to obtain compositions with predicted rheological, energy or environmental characteristics. Besides, gel fuels have a lower level of the fire hazard compared to common solid and liquid fuels. This makes them convenient for storage and transportation. In such conditions, it is not necessary to transport combustible wastes from the territory of the Arctic and the Antarctic to the mainland for processing, which is now quite an expensive procedure. The research was funded by the Russian Science Foundation (project No. 18-13-00031).

Keywords: combustible liquid waste, gel fuel, ignition and combustion, utilization

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Authors: Alessandro Balbo, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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Hydrogen is expected to become a game changer in the energy transition, especially enabling sector coupling possibilities and the decarbonization of hard-to-abate end-uses. The Italian National Recovery and Resilience Plan identifies hydrogen as one of the key elements of the ecologic transition to meet international decarbonization objectives, also including it in several pilot projects for the early development in Italy. This matches the European energy strategy, which aims to make hydrogen a leading energy carrier of the future, setting ambitious goals to be accomplished by 2030. The huge efforts needed to achieve the announced targets require to carefully investigate of their feasibility in terms of economic expenditures and technical aspects. In order to quantitatively assess the hydrogen potential within the Italian context and the feasibility of the planned investments and projects, this work uses the TEMOA-Italy energy system model to study pathways to meet the strict objectives above cited. The possible hydrogen development has been studied both in the supply-side and demand-side of the energy system, also including storage options and distribution chains. The assessment comprehends alternative hydrogen production technologies involved in a competition market, reflecting the several possible investments declined by the Italian National Recovery and Resilience Plan to boost the development and spread of this infrastructure, including the sector coupling potential with natural gas through the currently existing infrastructure and CO2 capture for the production of synfuels. On the other hand, the hydrogen end-uses phase covers a wide range of consumption alternatives, from fuel-cell vehicles, for which both road and non-road transport categories are considered, to steel, and chemical industries uses and cogeneration for residential and commercial buildings. The model includes both high and low TRL technologies in order to provide a consistent outcome for the future decades as it does for the present day, and since it is developed through the use of an open-source code instance and database, transparency and accessibility are fully granted.

Keywords: decarbonization, energy system optimization models, hydrogen, open-source modeling, TEMOA

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Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

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Authors: Ibrahim Ellithy, Mauricio Esguerra, , Rewanth Radhakrishnan

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In this study, the effects of hydrostatic stress on the magnetic properties of MnZn ferrite rings of different power grades, were measured and analyzed in terms of the magneto-mechanical effect on core losses was modeled via the Hodgdon-Esguerra hysteresis model. The results show excellent agreement with the model and a correlation between the permeability drop and the core loss increase in dependence of the material grade properties. These results emphasize the vulnerabilities of MnZn ferrites when subjected to mechanical perturbations, especially in real-world scenarios like under-road embedding for WPT.

Keywords: hydrostatic stress, power ferrites, core losses, wireless power transfer

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Authors: Sînziana Iancu

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In an era marked by rapid urbanization and technological advancement, the concept of smart cities has emerged as a pivotal solution to address the complex challenges faced by urban centres. As cities strive to enhance the quality of life for their residents, the development of smart cities has gained prominence. This study embarks on a comparative analysis of two distinct smart city models, Singapore and Bucharest, to assess their resilience and technological advancements. The significance of this study lies in its potential to provide valuable insights into the strategies, strengths, and areas of improvement in smart city development, ultimately contributing to the advancement of urban planning and sustainability. Methodologies: This comparative study employs a multifaceted approach to comprehensively analyse the smart city development in Singapore and Bucharest: * Comparative Analysis: A systematic comparison of the two cities is conducted, focusing on key smart city indicators, including digital infrastructure, integrated public services, urban planning and sustainability, transportation and mobility, environmental monitoring, safety and security, innovation and economic resilience, and community engagement; * Case Studies: In-depth case studies are conducted to delve into specific smart city projects and initiatives in both cities, providing real-world examples of their successes and challenges; * Data Analysis: Official reports, statistical data, and relevant publications are analysed to gather quantitative insights into various aspects of smart city development. Major Findings: Through a comprehensive analysis of Singapore and Bucharest's smart city development, the study yields the following major findings: * Singapore excels in digital infrastructure, integrated public services, safety, and innovation, showcasing a high level of resilience across these domains; * Bucharest is in the early stages of smart city development, with notable potential for growth in digital infrastructure and community engagement.; * Both cities exhibit a commitment to sustainable urban planning and environmental monitoring, with room for improvement in integrating these aspects into everyday life; * Transportation and mobility solutions are a priority for both cities, with Singapore having a more advanced system, while Bucharest is actively working on improving its transportation infrastructure; * Community engagement, while important, requires further attention in both cities to enhance the inclusivity of smart city initiatives. Conclusion: In conclusion, this study serves as a valuable resource for urban planners, policymakers, and stakeholders in understanding the nuances of smart city development and resilience. While Singapore stands as a beacon of success in various smart city indicators, Bucharest demonstrates potential and a willingness to adapt and grow in this domain. As cities worldwide embark on their smart city journeys, the lessons learned from Singapore and Bucharest provide invaluable insights into the path toward urban sustainability and resilience in the digital age.

Keywords: bucharest, resilience, Singapore, smart city

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Authors: Hatem Abou-Senna, Essam Radwan

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With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

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Authors: Samuel Quick

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The purpose of this paper is to examine future urban street design in the context of developing technologies, evolving street typologies, and projected transportation trends. The goal was to envision a future urban street in the year 2060 that addresses the advent and implementation of autonomous vehicles, the promotion of new street typologies, and the projection of current transportation trends. Using a hierarchy of functional needs for urban streets, the future street was designed and evaluated based on the functions the street provides to the surrounding community. The site chosen for the future street design is an eight-block section of West North Avenue in the city of Baltimore, Maryland. Three different conceptual designs were initially completed and evaluated leading to a master plan for West North Avenue as well as street designs for connecting streets that represent different existing street types. Final designs were compared with the existing street design and evaluated with the adapted ‘Hierarchy of Needs’ theory. The review of the literature and the results from this paper indicate that urban streets will have to become increasingly multi-functional to meet the competing needs of the environment and community. Future streets will have to accommodate multimodal transit which will include mass transit, walking, and biking. Furthermore, a comprehensive implementation of green infrastructure within the urban street will provide access to nature for urban communities and essential stormwater management. With these developments, the future of an urban street will move closer to a greenway typology. Findings from this study indicate that urban street design will have to be policy-driven to promote and implement autonomous bus-rapid-transit in order to conserve street space for other functions. With this conservation of space, urban streets can then provide more functions to the surrounding community, taking a holistic approach to urban street design.

Keywords: autonomous vehicle, greenway, green infrastructure, multi-modality, street typology

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Authors: Priya Jaswal, Vivek, S. K. Sinha

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One of the most important and complicated factors influencing the functional performance of unpaved roads is traffic loading. The complexity of traffic loading is caused by the variable magnitude and frequency of load, which causes unpaved roads to fail prematurely. Unpaved roads are low-volume roads, and as peri-urbanization increases, unpaved roads act as a means to boost the rural economy. This has also increased traffic on unpaved roads, intensifying the issue of settlement, rutting, and fatigue failure. This is a major concern for unpaved roads built on poor subgrade soil, as excessive rutting caused by heavy loads can cause driver discomfort, vehicle damage, and an increase in maintenance costs. Some researchers discovered that when a consistent static load is exerted as opposed to a rapidly changing load, the rate of deformation of unpaved roads increases. Previously, some of the most common methods for overcoming the problem of rutting and fatigue failure included chemical stabilisation, fibre reinforcement, and so on. However, due to their high cost, engineers' attention has shifted to geotextiles which are used as reinforcement in unpaved roads. Geotextiles perform the function of filtration, lateral confinement of base material, vertical restraint of subgrade soil, and the tension membrane effect. The use of geotextiles in unpaved roads increases the strength of unpaved roads and is an economically viable method because it reduces the required aggregate thickness, which would need less earthwork, and is thus recommended for unpaved road applications. The majority of geotextiles used previously were polymeric, but with a growing awareness of sustainable development to preserve the environment, researchers' focus has shifted to natural fibres. Coir is one such natural fibre that possesses the advantage of having a higher tensile strength than other bast fibres, being eco-friendly, low in cost, and biodegradable. However, various researchers have discovered that the surface of coir fibre is covered with various impurities, voids, and cracks, which act as a plane of weakness and limit the potential application of coir geotextiles. To overcome this limitation, chemical surface modification of coir geotextiles is widely accepted by researchers because it improves the mechanical properties of coir geotextiles. The current paper reviews the effect of using treated coir geotextiles as reinforcement on the load-deformation behaviour of a two-layered unpaved road model.

Keywords: coir, geotextile, treated, unpaved

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Authors: Alireza Motamadnia, Roohollah Zohdi Oliayi, Hümeyra Bolakar, Ahmet Tortum

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Dynamic compression as a method of soil improvement in recent decades has been considered by engineers and experts. Three methods mainly, deep dynamic compaction, soil density, dynamic and rapid change have been proposed and implemented to improve subgrade conditions of highway road. Northern highway route in Tabriz (Pasdaran), Iran that was placed on the manual soil was the main concern. Engineering properties of soil have been investigated experimentally and theoretically. Among the three methods rapid dynamic compaction for highway has been suggested to improve the soil subgrade conditions.

Keywords: manual soil, subsidence, improvement, dynamic compression

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

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Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

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Authors: Sai Siddharth S., Prasanna Kumar G. M., Alagarsamy R.

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This research introduces an alternative approach to urban road maintenance by utilizing Blended Wing Body (BWB) design and Vertical Takeoff and Landing (VTOL) drones. The integration of this aerospace innovation, combining blended wing efficiency with VTOL maneuverability, aims to optimize fuel consumption and explore versatile applications in solving urban problems. A few problems are discussed along with optimization of the design and comparative study with other drone configurations.

Keywords: design optimization, CFD, CAD, VTOL, blended wing body

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Authors: S. Amanpour, F. Mohamadian, S. A. Tabatabai

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With the number of accidents and fatalities in recent years can be concluded that Iran is the status of road accidents, remains in a crisis. Investigate the causes of such incidents in all countries is a necessity. By doing this research, the results of the number and type of accidents and the location of the crash will be available. It is possible to prioritize economic and rational solutions to fix the flaws in the way of short-term the results are all the more strict rules about the desire to have black spots and cursory glance at the change of but results in long-term are desired to change the system or increase the width of the path or add extra track. In general, the relationship between the analysis of the accidents and near police statistics is the number of accidents in one year. This could prove the accuracy of the analysis done.

Keywords: traffic, IHSDM, crash, modeling, Khuzestan

Procedia PDF Downloads 263

Authors: Michael Heuer, Ayoub Al-Hamadi, Alexander Rain, Marc-Michael Meinecke

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Vulnerable road users, e.g. pedestrians, have a high impact on fatal accident numbers. To reduce these statistics, car manufactures are intensively developing suitable safety systems. Hereby, fast and reliable environment recognition is a major challenge. In this paper we describe a tracking approach that is only based on a 24 GHz radar sensor. While common radar signal processing loses much information, we make use of a track-before-detect filter to incorporate raw measurements. It is explained how the Range-Doppler spectrum can help to indicated pedestrians and stabilize tracking even in occultation scenarios compared to sensors in series.

Keywords: radar, pedestrian detection, active safety, sensor

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Authors: Thabo M. Bafitlhile, Adewole Oladele

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Botswana has been affected by floods since long ago and is still experiencing this tragic event. Flooding occurs mostly in the North-West, North-East, and parts of Central district due to heavy rainfalls experienced in these areas. The torrential rains destroyed homes, roads, flooded dams, fields and destroyed livestock and livelihoods. Palapye is one area in the central district that has been experiencing floods ever since 1995 when its greatest flood on record occurred. Heavy storms result in floods and inundation; this has been exacerbated by poor and absence of drainage structures. Since floods are a part of nature, they have existed and will to continue to exist, hence more destruction. Furthermore floods and highway plays major role in erosion and destruction of roads structures. Already today, many culverts, trenches, and other drainage facilities lack the capacity to deal with current frequency for extreme flows. Future changes in the pattern of hydro climatic events will have implications for the design and maintenance costs of roads. Increase in rainfall and severe weather events can affect the demand for emergent responses. Therefore flood forecasting and warning is a prerequisite for successful mitigation of flood damage. In flood prone areas like Palapye, preventive measures should be taken to reduce possible adverse effects of floods on the environment including road structures. Therefore this paper attempts to estimate return periods associated with huge storms of different magnitude from recorded historical rainfall depth using statistical method. The method of annual maxima was used to select data sets for the rainfall analysis. In the statistical method, the Type 1 extreme value (Gumbel), Log Normal, Log Pearson 3 distributions were all applied to the annual maximum series for Palapye area to produce IDF curves. The Kolmogorov-Smirnov test and Chi Squared were used to confirm the appropriateness of fitted distributions for the location and the data do fit the distributions used to predict expected frequencies. This will be a beneficial tool for urgent flood forecasting and water resource administration as proper drainage design will be design based on the estimated flood events and will help to reclaim and protect the road structures from adverse impacts of flood.

Keywords: drainage, estimate, evaluation, floods, flood forecasting

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Authors: Hassan Taimoor, Piotr Krajewski, Piotr Gabrielzcak

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Being responsible for the largest source of energy-related emissions, the transportation sector is driven by more than half of global oil demand and total energy consumption, making it a crucial factor in tackling climate change and environmental degradation. The present study empirically tests the effectives of the energy-related tax (TXEN) in curbing transport-related carbon emissions (CO2TRANSP) in Organization for Economic Cooperation and Development (OECD) economies over the period of 1990-2020. Moreover, Green Finance (GF), Technology (TECH), and Gross domestic product (GDP) have also been added as explanatory factors which might affect CO2TRANSP emissions. The study employs the Method of Moment Quantile Regression (MMQR), an advance econometric technique to observe the variations along each quantile. Based on the results of the preliminary test, we confirm the presence of cross-sectional dependence and slope heterogeneity. Whereas the result of the panel unit root test report mixed order of variables’ integration. The findings reveal that rise in income level activates CO2TRANSP, confirming the first stage of Environmental Kuznet Hypothesis. Surprisingly, the present TXEN policies of OECD member states are not mature enough to tackle the CO2TRANSP emissions. However, the findings confirm that GF and TECH are solely responsible for the reduction in the CO2TRANSP. The outcomes of Bootstrap Quantile Regression (BSQR) further validate and support the earlier findings of MMQR. Based on the findings of this study, it is revealed that the current TXEN policies are too moderate, and an incremental and progressive rise in TXEN may help in a transition toward a cleaner and sustainable transportation sector in the study region.

Keywords: transport-related CO2 emissions, energy-related tax, green finance, technological development, oecd member states

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Authors: Seyedabdolali Mortazavi Kamalabadi, Faegheh Taheran

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By giving an overview of previous arguments and findings concerned with the concept of competitive advantage, first, we define the overall concept of competitive advantage and discuss nuances of understanding such an important and strategic idea. Finally, by considering the major concerns of marketing academia, including globalization, AI-based technologies, consumer well-being, and internal coopetition between a firm’s units, fruitful avenues to be explored by future studies are presented in the form of research propositions. In the end, relevant gaps mentioned by numerous studies that are worth investigating are demonstrated.

Keywords: artificial intelligence, competitive advantage, consumer well-being, coopetition, globalization, literature review, temporary competitive advantage

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Authors: Tingke Wu, Man Yuan

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“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.

Keywords: driving forces, Hubei, optimizing strategies, spatial pattern, territory

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Authors: Na Zhou, Chun-Lai Zhang, Qing Li, Bingqi Zhu, Xun-Ming Wang

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The understanding of the dynamics of aeolian sand in the Yarlung Zangbo River Valley (YLZBV), southern Qinghai-Tibetan Plateau, including its origins, transportation,and deposition, remains preliminary. In this study, we investigated the extensive origin of aeolian sediments in the YLZBV by analyzing the distribution and composition of sediment’s grain size and geochemical composition in dune sediments collected from the wide river terraces. The major purpose is to characterize the sedimentological and geochemical compositions of these aeolian sediments, trace back to their sources, and understand their influencing factors. As a result, the grain size and geochemistry variations, which showed a significant correlation between grain sizes distribution and element abundances, give a strong evidence that the important part of the aeolian sediments in the downstream areas was firstly derived from the upper reaches by intense fluvial processes. However, the sediments experienced significant mixing process with local inputs and reconstructed by regional wind transportation. The diverse compositions and tight associations in the major and trace element geochemistry between the up- and down-stream aeolian sediments and the local detrital rocks, which were collected from the surrounding mountains, suggest that the upstream aeolian sediments had originated from the various close-range rock types, and experienced intensive mixing processes via aeolian- fluvial dynamics. Sand mass transported by water and wind was roughly estimated to qualify the interplay between the aeolian and fluvial processes controlling the sediment transport, yield, and ultimately shaping the aeolian landforms in the mainstream of the YLZBV.

Keywords: grain size distribution, geochemistry, wind and water load, sand source, Yarlung Zangbo River Valley

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Authors: Julie Furst-Bowe

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Over the past decade, there has been significant growth in online courses and programs at all levels of education in the United States. This study explores the growth of online and blended (or hybrid) programs offered by the sixteen technical colleges in the Wisconsin Technical College System (WTCS). The WTCS provides education and training programs to more than 300,000 students each year in career clusters including agriculture, business, energy, information technology, healthcare, human services, manufacturing, and transportation. These programs range from short-term training programs that may lead to a certificate to two-year programs that lead to an associate degree. Students vary in age from high school students who are exploring career interests to employees who are seeking to gain additional skills or enter a new career. Because there is currently a shortage of skilled workers in nearly all sectors in the state of Wisconsin, it is critical that the WTCS is providing fully educated and trained graduates to fill workforce needs in a timely manner. For this study, information on online and blended programs for the past five years was collected from the WTCS, including types of programs, course and program enrollments, course completion rates, program completion rates, time to completion and graduate employment rates. The results of this study indicate that the number of online and blended courses and programs is continuing to increase each year. Online and blended programs are most commonly found in the business, human services, and information technology areas, and they are less commonly found in agriculture, healthcare, manufacturing, and transportation programs. Overall, course and program completion rates were higher for blended programs when compared to fully online programs. Students preferred the blended programs over the fully online programs. Overall, graduates were placed into related jobs at a rate of approximately 90 percent, although there was some variation in graduate placement rates by programs and by colleges. Differences in graduate employment rate appeared to be based on geography and sector as employers did not distinguish between graduates who had completed their programs via traditional, blended or fully online instruction. Recommendations include further exploration as to the reasons that blended courses and programs appear to be more effective than fully online courses and programs. It is also recommended that those program areas that are not using blended or online delivery methods, including agriculture, health, manufacturing and transportation, explore the use of these methods to make their courses and programs more accessible to students, particularly working adults. In some instances, colleges were partnering with specific companies to ensure that groups of employees were completing online coursework leading to a certificate or a degree. Those partnerships are to be encouraged in order for the state to continue to improve the skills of its workforce. Finally, it is recommended that specific colleges specialize in the delivery of specific programs using online technology since it is not bound by geographic considerations. This approach would take advantage of the strengths of the individual colleges and avoid unnecessary duplication.

Keywords: career and technical education, online learning, skills shortage, technical colleges

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Authors: Khashayar Kazemzadeh, Mohammad Hanif Dasoomi

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According to the increasing volume of traffic, lane changing plays a crucial role in traffic flow. Lane changing in traffic depends on several factors including road geometrical design, speed, drivers’ behavioral characteristics, etc. A great deal of research has been carried out regarding these fields. Despite of the other significant factors, the drivers’ behavioral characteristics of lane changing has been emphasized in this paper. This paper has predicted the effective equation based on personal characteristics of lane changing by regression models.

Keywords: effective equation, lane changing, drivers’ behavioral characteristics, regression models

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Authors: Arefeh Hesaraki

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The application of photovoltaic-thermal hybrids (PVT), which delivers both electricity and heat simultaneously from the same system, has become more popular during the past few years. This study addresses techno-economic and environmental impacts assessment of photovoltaic/thermal systems combined with a ground-source heat pump (GSHP) for three single-family houses located in Stockholm, Sweden. Three case studies were: (1) A renovated building built in 1936, (2) A renovated building built in 1973, and (3) A new building built-in 2013. Two simulation programs of SimaPro 9.1 and IDA Indoor Climate and Energy 4.8 (IDA ICE) were applied to analyze environmental impacts and energy usage, respectively. The cost-effectiveness of the system was evaluated using net present value (NPV), internal rate of return (IRR), and discounted payback time (DPBT) methods. In addition to cost payback time, the studied PVT system was evaluated using the energy payback time (EPBT) method. EPBT presents the time that is needed for the installed system to generate the same amount of energy which was utilized during the whole lifecycle (fabrication, installation, transportation, and end-of-life) of the system itself. Energy calculation by IDA ICE showed that a 5 m² PVT was sufficient to create a balance between the maximum heat production and the domestic hot water consumption during the summer months for all three case studies. The techno-economic analysis revealed that combining a 5 m² PVT with GSHP in the second case study possess the smallest DPBT and the highest NPV and IRR among the three case studies. It means that DPBTs (IRR) were 10.8 years (6%), 12.6 years (4%), and 13.8 years (3%) for the second, first, and the third case study, respectively. Moreover, environmental assessment of embodied energy during cradle- to- grave life cycle of the studied PVT, including fabrication, delivery of energy and raw materials, manufacture process, installation, transportation, operation phase, and end of life, revealed approximately two years of EPBT in all cases.

Keywords: life-cycle cost, life-cycle assessment, photovoltaic/thermal, IDA ICE, net present value

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Authors: Riccardo Loggia, Francesca Pizzimenti, Francesco Lelli, Luigi Martirano

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Recent air emission regulations point toward the complete electrification of road vehicles. An increasing number of users are beginning to prefer full electric or hybrid, plug-in vehicle solutions, incentivized by government subsidies and the lower cost of electricity compared to gasoline or diesel. However, it is necessary to optimize charging stations so that they can simultaneously satisfy as many users as possible. The purpose of this paper is to present optimization algorithms that enable simultaneous charging of multiple electric vehicles while ensuring maximum performance in relation to the type of charging station.

Keywords: electric vehicles, charging stations, sharing model, fast charging, car park, power profiles

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Authors: Guannan Ren, Thomas Mazzuchi, Shahram Sarkani

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Electric vehicle battery recycling has emerged as a critical process in the transition toward sustainable transportation. As the demand for electric vehicles continues to rise, so does the need to address the end-of-life management of their batteries. Electric vehicle battery recycling benefits resource recovery and supply chain stability by reclaiming valuable metals like lithium, cobalt, nickel, and graphite. The reclaimed materials can then be reintroduced into the battery manufacturing process, reducing the reliance on raw material extraction and the environmental impacts of waste. Current battery recycling rates are insufficient to meet the growing demands for raw materials. While significant progress has been made in electric vehicle battery recycling, many areas can still improve. Standardization of battery designs, increased collection and recycling infrastructures, and improved efficiency in recycling processes are essential for scaling up recycling efforts and maximizing material recovery. This work delves into key factors, such as regulatory frameworks, economic incentives, and technological processes, that influence the cost-effectiveness and efficiency of battery recycling systems. A system dynamics model that considers variables such as battery production rates, demand and price fluctuations, recycling infrastructure capacity, and the effectiveness of recycling processes is created to study how these variables are interconnected, forming feedback loops that affect the overall supply chain efficiency. Such a model can also help simulate the effects of stricter regulations on battery disposal, incentives for recycling, or investments in research and development for battery designs and advanced recycling technologies. By using the developed model, policymakers, industry stakeholders, and researchers may gain insights into the effects of applying different policies or process updates on electric vehicle battery recycling rates.

Keywords: environmental engineering, modeling and simulation, circular economy, sustainability, transportation science, policy

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Authors: Sivapan Choo-In

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The main objective of this study was investigate particulate matter concentration on main and secondary roadside in urban area. And studied on the concentration of some heavy metal including lead (Pb), zinc (Zn), copper (Cu) and cadmium (Cd) in particulate matter in Bangkok area. The averaged particle concentration for main roadside are higher than secondary roadside. The particulate matter less than 10 micron concentration contribute the majority of the Total Suspended Particulate for main road and zinc concentration were higher than copper and lead for both site.

Keywords: air pollution, air quality, polution, monitoring

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Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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Authors: Varun Joshi, M. S. Rawat

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The Indian Himalayan Region (IHR) is inherently fragile and susceptible to landslide hazard due to its extremely weak geology, highly rugged topography and heavy monsoonal rainfall. One of the most common hazards in the IHR is landslide, and this event is particularly frequent in Himalayan states of India i.e. Jammu & Kashmir, Himachal Pradesh, Uttarakhand, Sikkim, Manipur and Arunachal Pradesh. Landslides are mostly triggered by extreme rainfall events but the incidence increases during monsoon months (June to September). Natural slopes which are otherwise stable but they get destabilized due to anthropogenic activities like construction of various developmental activities and deforestation. These activities are required to fulfill the developmental needs and upliftment of societal status in the region. Landslides also trigger during major earthquakes and reported most observable and damaging phenomena. Studies indicate that the landslide phenomenon has increased many folds due to developmental activities in Himalayan region. Gradually increasing and devastating consequences of landslides turned into one of the most important hydro-geological hazards in Himalayan states especially in Uttarakhand and Sikkim states of India. The recent most catastrophic rainfall in June 2013 in Uttarakhand lead to colossal loss of life and property. The societal damage due to this incident is still to be recovered even after three years. Sikkim earthquake of September 2011 is witnessed for triggering of large number of coseismic landslides. The rescue and relief team faced huge problem in helping the trapped villagers in remote locations of the state due to road side blockade by landslides. The recent past incidences of landslides in Uttarakhand, as well as Sikkim states, created a new domain of research in terms of understanding the phenomena of landslide and management of disaster in such situation. Every year at many locations landslides trigger which force dwellers to either evacuate their dwelling or lose their life and property. The communication and transportation networks are also severely affected by landslides at several locations. Many times the drinking water supply disturbed and shortage of daily need household items reported during monsoon months. To minimize the severity of landslide in IHR requires in-depth research and developmental planning. For most of the areas in the present study, landslide hazard zonation is done on 1:50,000 scale. The land use planning maps on extensive basis are not available. Therefore, there is a need of large-scale landslide hazard zonation and land use planning maps. If the scientist conduct research on desired aspects and their outcome of research is utilized by the government in developmental planning then the incidents of landslide could be minimized, subsequent impact on society, life and property would be reduced. Along with the scientific research, there is another need of awareness generation in the region for stake holders and local dwellers to combat with the landslide hazard, if triggered in their location.

Keywords: coseismic, Indian Himalayan Region, landslide hazard zonation, Sikkim, societal, Uttarakhand

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Authors: Csaba I. Hencz, István Á. Harmati

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Nowadays the significance of road transport is gradually increasing. All transport companies are working in the same external environment where the speed of transport is defined by traffic rules. The main objective is to accelerate the speed of service and it is only dependent on the individual abilities of the managing members. These operational control units make decisions quickly (in a typically experiential and/or intuitive way). For this reason, support for these decisions is an important task. Our goal is to create a decision support model based on fuzzy signatures that can assist the work of operational management automatically. If the model sets parameters properly, the management of transport could be more economical and efficient.

Keywords: freight transport, decision support, information handling, fuzzy methods

Procedia PDF Downloads 241

Authors: Hanwei Gao, Louis Jezequel, Eric Cabrol, Bernard Vitry

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The chassis system is composed of complex elements that take up all the loads from the tire-ground contact area and thus it plays an important role in numerous specifications such as durability, comfort, crash, etc. During the development of new vehicle projects in Renault, durability validation is always the main focus while deployment of comfort comes later in the project. Therefore, sometimes design choices have to be reconsidered because of the natural incompatibility between these two specifications. Besides, robustness is also an important point of concern as it is related to manufacturing costs as well as the performance after the ageing of components like shock absorbers. In this paper an approach is proposed aiming to realize a multi-objective optimization between chassis endurance and comfort while taking the random factors into consideration. The adaptive-sparse polynomial chaos expansion method (PCE) with Chebyshev polynomial series has been applied to predict responses’ uncertainty intervals of a system according to its uncertain-but-bounded parameters. The approach can be divided into three steps. First an initial design of experiments is realized to build the response surfaces which represent statistically a black-box system. Secondly within several iterations an optimum set is proposed and validated which will form a Pareto front. At the same time the robustness of each response, served as additional objectives, is calculated from the pre-defined parameter intervals and the response surfaces obtained in the first step. Finally an inverse strategy is carried out to determine the parameters’ tolerance combination with a maximally acceptable degradation of the responses in terms of manufacturing costs. A quarter car model has been tested as an example by applying the road excitations from the actual road measurements for both endurance and comfort calculations. One indicator based on the Basquin’s law is defined to compare the global chassis durability of different parameter settings. Another indicator related to comfort is obtained from the vertical acceleration of the sprung mass. An optimum set with best robustness has been finally obtained and the reference tests prove a good robustness prediction of Chebyshev PCE method. This example demonstrates the effectiveness and reliability of the approach, in particular its ability to save computational costs for a complex system.

Keywords: chassis durability, Chebyshev polynomials, multi-objective optimization, polynomial chaos expansion, ride comfort, robust design

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Authors: Ruxandra Aursulesei, David O’Callaghan, Cian Ryan, Diarmaid O’Cualain, Viktor Varkarakis, Alina Sultana, Joseph Lemley

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Human errors caused by drowsiness are among the leading causes of road accidents. Neurobiological research gives information about the electrical signals emitted by neurons firing within the brain. Electrical signal frequencies can be determined by attaching bio-sensors to the head surface. By observing the electrical impulses and the rhythmic interaction of neurons with each other, we can predict the mental state of a person. In this paper, we aim to better understand intersubject and intrasubject variability in terms of electrophysiological patterns that occur at the onset of drowsiness and their evolution with the decreasing of vigilance. The purpose is to lay the foundations for an algorithm that detects the onset of drowsiness before the physical signs become apparent.

Keywords: electroencephalography, drowsiness, ADAS, annotations, clinician

Procedia PDF Downloads 92