Abstracts | Transport and Vehicle Engineering
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 788

World Academy of Science, Engineering and Technology

[Transport and Vehicle Engineering]

Online ISSN : 1307-6892

638 A Hybrid Traffic Model for Smoothing Traffic Near Merges

Authors: Shiri Elisheva Decktor, Sharon Hornstein

Abstract:

Highway merges and unmarked junctions are key components in any urban road network, which can act as bottlenecks and create traffic disruption. Inefficient highway merges may trigger traffic instabilities such as stop-and-go waves, pose safety conditions and lead to longer journey times. These phenomena occur spontaneously if the average vehicle density exceeds a certain critical value. This study focuses on modeling the traffic using a microscopic traffic flow model. A hybrid traffic model, which combines human-driven and controlled vehicles is assumed. The controlled vehicles obey different driving policies when approaching the merge, or in the vicinity of other vehicles. We developed a co-simulation model in SUMO (Simulation of Urban Mobility), in which the human-driven cars are modeled using the IDM model, and the controlled cars are modeled using a dedicated controller. The scenario chosen for this study is a closed track with one merge and one exit, which could be later implemented using a scaled infrastructure on our lab setup. This will enable us to benchmark the results of this study obtained in simulation, to comparable results in similar conditions in the lab. The metrics chosen for the comparison of the performance of our algorithm on the overall traffic conditions include the average speed, wait time near the merge, and throughput after the merge, measured under different travel demand conditions (low, medium, and heavy traffic).

Keywords: highway merges, traffic modeling, SUMO, driving policy

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637 A Conv-Long Short-term Memory Deep Learning Model for Traffic Flow Prediction

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

Abstract:

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

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

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636 Hearing Conservation Aspects of Soldier’s Exposure to Harmfull Noise within Military Armored Vehicles

Authors: Fink Nir

Abstract:

Soldiers within armored vehicles are exposed to continuous noise reaching levels as high as 120 dB. The use of hearing protection devices (HPD) may attenuate noise by as 25 dB, but attenuated noise reaching the ear is still harmful and may result in hearing loss. Hearing conservation programs in the military suggest methods to manage the harmful effects of noise. These include noise absorption within vehicles, evaluating HPD's performance, limiting time exposure, and providing guidance.

Keywords: armored vehicle noise, hearing loss, hearing protection devices, military noise, noise attenuation

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635 Geographic Information System-Based Identification of Road Traffic Crash Hotspots on Rural Roads in Oman

Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

Abstract:

The use of Geographic Information System (GIS) tools in the analysis of traffic crash data can help to identify locations or hotspots with high instances or risk of traffic crashes. The identification of traffic crash hotspots can effectively improve road safety measures. Mapping of road traffic crash hotspots can help the concerned authorities to give priority and take targeted measures and improvements to the road structure at these locations to reduce traffic crashes and fatalities. In Oman, there are countless rural roads that have more risks for traveling vehicles compared to urban roads. The likelihood of traffic crashes as well as fatality rate may increase with the presence of risks that are associated with the rural type of community. In this paper, the traffic crash hotspots on rural roads in Oman are specified using spatial analysis methods in GIS and traffic crash data. These hotspots are ranked based on the frequency of traffic crash occurrence (i.e., number of traffic crashes) and the rate of fatalities. The result of this study presents a map visualization of locations on rural roads with high traffic crashes and high fatalities rates.

Keywords: road safety, rural roads, traffic crash, GIS tools

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634 Traffic Calming Measures at Rural Roads in Dhofar

Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

Abstract:

Traffic calming measures are different design features or strategies used to reduce the speed of a traveling vehicle on a particular road. These calming measures are common on rural roads of Oman. Some of these measures are road speed limits, vertical deflections, horizontal deflections, and road signs. In general, vertical deflections such as rumble strips, road studs (cat’s eye), speed tables, and speed humps are widely used. In this paper, as vehicle speeding is a major cause of road traffic crashes and high fatalities in Oman, the effectiveness of existing traffic calming measures at current locations on rural roads is assessed. The study was conducted on the rural roads of Dhofar Governorate, which is located in the south of Oman. A special focus is given to the calming measures implemented on the mountain roads of Dhofar. It is shown that vertical deflection calming measures are effective in reducing vehicle speed to 20 to 40 kph, depending on the vertical deflection type and spacing. Calming measures are also proposed at locations with a high probability of traffic crashes based on the number of traffic crashes at these locations, road type, and road geometry.

Keywords: road safety, rural roads, speed, traffic calming measures, traffic crash

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633 Changes in Pain Intensity of Musculoskeletal Disorders in Flight Attendants after Stretching Exercise Program

Authors: Maria Melania Muda, Retno Wibawanti, Retno Asti Werdhani

Abstract:

Background: Flight attendant (FA) is a job that is often exposed to ergonomic stressors; thus, they are very susceptible to symptoms of musculoskeletal disorders (MSDs). One of the ways to overcome musculoskeletal complaints is by stretching. This study aimed to examine the prevalence of MSDs and the effect of a 2-week stretching exercise program using the Indonesian Ministry of Health's stretching video on changes in musculoskeletal pain intensity in FA on commercial aircraft in Indonesia. Methods: A pre-post study was conducted using Nordic Musculoskeletal Questionnaire (NMQ) for MSDs’ identification and Visual Analog Scale (VAS) as pain intensity measurement. Data was collected and then analyzed using SPSS with Wilcoxon test. The change in pain intensity was considered significant if the p value was less than 0.05. Results: The results showed that 92% of the FA (n=75) had MSDs in at least 1 area of the body in the last 12 months. Thirty-four respondents participated as subjects. The complaint level score in 28 body areas before intervention was a median of 34 (29-84), with pain intensity of a median of 6 (2-9) became a median of 32 (28-67) and a median of 3 (0-9) after the intervention, respectively, with p-value <0.001. Conclusion: The stretching exercise program showed significant changes in the complaint level scores in 28 body areas (p < 0.001) and pain intensity before and after the stretching exercise intervention (p < 0.001).

Keywords: flight attendant, MSDs, Nordic Musculoskeletal Questionnaire, stretching exercise program, visual analog scale

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632 Analysis of Traffic Crashes on Rural Roads in Oman

Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

Abstract:

Fatalities of Road Traffic Crashes (RTCs) on rural roads are usually higher than that on urban roads. The likelihood of traffic accidents may increase with the presence of factors that are associated with the rural type of community such as long-distance, road type, road geometry (e.g., curves and steepens), poor lighting, terrain, obstacles (e.g., animals crossing, boulders or tree branches), heavy truck traffic, weather conditions, and road flaws. Most of these factors are present on the rural roads of Oman. As many cities in Oman are surrounded by mountains and connected by rural roads, this is of great concern. In this paper, the causes of traffic crashes on rural roads in Oman are analyzed. The fatality rate of traffic deaths on rural roads is compared with the fatality rate on urban roads for different regions in Oman. Statistical data and police reports show that the leading cause of RTCs and deaths on rural roads is vehicle speeding, especially on long-distance roads. It is shown that crashes on rural roads result in higher fatalities than crashes on urban roads. In comparison to speed, the numbers of RTCs and deaths that resulted from other causes are small.

Keywords: causes of traffic crashes, road safety, road traffic crash, rural roads

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631 Sourcing and Compiling a Maltese Traffic Dataset MalTra

Authors: Gabriele Borg, Alexei De Bono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale.

Keywords: Big Data, vehicular traffic, traffic management, mobile data patterns

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630 Graph Based Traffic Analysis and Delay Prediction Using a Custom Built Dataset

Authors: Gabriele Borg, Alexei Debono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.

Keywords: graph neural networks, traffic management, big data, mobile data patterns

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629 Testing of Electronic Control Unit Communication Interface

Authors: Petr Šimek, Kamil Kostruk

Abstract:

This paper deals with the problem of testing the Electronic Control Unit (ECU) for the specified function validation. Modern ECUs have many functions which need to be tested. This process requires tracking between the test and the specification. The technique discussed in this paper explores the system for automating this process. The paper focuses in its chapter IV on the introduction to the problem in general, then it describes the proposed test system concept and its principle. It looks at how the process of the ECU interface specification file for automated interface testing and test tracking works. In the end, the future possible development of the project is discussed.

Keywords: electronic control unit testing, embedded system, test generate, test automation, process automation, CAN bus, ethernet

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628 Analysis of Accessibility of Tourism Transportation in Banyuwangi

Authors: Lilla Anjani, Ervina Ahyudanari

Abstract:

Tourism is one of the contributors to regional economic income. Banyuwangi has made rapid developments related to the tourism sector, especially since 2010. There are 25 tourist visit locations that can become tourist destinations. Banyuwangi has tourism transportation to support the ease of reaching tourist places. This transportation operates with six routes, namely the final destination of Ijen Crater, Glenmore, Bajangan, Bangsring, Red Island, and Pine Forest. Despite having tourism transportation, tourists tend to choose to use a private car or rent a car because there is no access to tourist places using public transportation. Tourism transportation is also one form of sustainable tourism development in the future, such as the Sustainable Development Goals. The Banyuwangi government has a special program for tourism development that is supported by all sectors in Banyuwangi. To support the development of tourism in Banyuwangi, it is necessary to analyze existing tourism transportation as well as suggestions regarding new routes to reach all tourism locations in Banyuwangi Regency. The analysis reviewed in this study is an analysis of accessibility, distance, and time to the tourism location. There are 30 tourism destination points from 39 ODTW references from the transportation service, and the tourism office of Banyuwangi Regency Banyuwangi tourism objects can be divided into six zones based on travel time and distance. The highest accessibility value for Zone A is 51.96, and the lowest is 11.989. The highest accessibility value for Zone B is 33.4269, and the lowest is 21.737. The highest accessibility value for Zone C is 33,407, and the lowest is 14,848. The highest accessibility value for Zone D is 58,967, and the lowest is 14,742. The highest accessibility value for Zone E is 56,401, and the lowest is 14.1. The highest accessibility value for Zone F is 176.14, and the lowest is 44.1. There are two tourist transportation routes with six sessions every day. The resulting new route is in the form of grouping based on locations that can be reached in one particular area.

Keywords: accessibility, tourism clustering, Banyuwangi tourism, sustainable development goals

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627 Icephobic and Hydrophobic Behaviour of Laser Patterned Transparent Coatings

Authors: Bartłomiej Przybyszewski, Rafał Kozera, Anna Boczkowska, Maciej Traczyk, Paulina Kozera, Malwina Liszewska, Daria Pakuła

Abstract:

The goal of the work was to reduce or completely eliminate the accumulation of dirt, snow and ice build-up on transparent coatings by achieving self-cleaning and icephobic properties. The research involved the use of laser surface texturing technology for chemically modified coatings of the epoxy materials group and their hybrids used to protect glass surfaces. For this purpose, two methods of surface structuring and the preceding volumetric modification of the chemical composition with proprietary organosilicon compounds and/or mineral additives were used. An attractive approach to the topic was the development of efficient and, most importantly, durable coatings with self-cleaning and ice-phobic properties that reduced or avoided dirt build-up and adhesion of water, snow and ice. With a view to the future industrial application of the developed technologies, all methods meet the requirements in terms of their practical use on a large scale.

Keywords: icephobic coatings, hydrophobic coatings, transparent coatings, laser patterning

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626 Intelligent Cooperative Integrated System for Road Safety and Road Infrastructure Maintenance

Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras

Abstract:

This paper presents the architecture of the “Intelligent cooperative integrated system for road safety and road infrastructure maintenance towards 2020” (ODOS2020) advanced infrastructure, which implements a number of cooperative ITS applications based on Internet of Things and Infrastructure-to-Vehicle (V2I) technologies with the purpose to enhance the active road safety level of vehicles through the provision of a fully automated V2I environment. The primary objective of the ODOS2020 project is to contribute to increased road safety but also to the optimization of time for maintenance of road infrastructure. The integrated technological solution presented in this paper addresses all types of vehicles and requires minimum vehicle equipment. Thus, the ODOS2020 comprises a low-cost solution, which is one of its main benefits. The system architecture includes an integrated notification system to transmit personalized information on road, traffic, and environmental conditions, in order for the drivers to receive real-time and reliable alerts concerning upcoming critical situations. The latter include potential dangers on the road, such as obstacles or road works ahead, extreme environmental conditions, etc., but also informative messages, such as information on upcoming tolls and their charging policies. At the core of the system architecture lies an integrated sensorial network embedded in special road infrastructures (strips) that constantly collect and transmit wirelessly information about passing vehicles’ identification, type, speed, moving direction and other traffic information in combination with environmental conditions and road wear monitoring and predictive maintenance data. Data collected from sensors is transmitted by roadside infrastructure, which supports a variety of communication technologies such as ITS-G5 (IEEE-802.11p) wireless network and Internet connectivity through cellular networks (3G, LTE). All information could be forwarded to both vehicles and Traffic Management Centers (TMC) operators, either directly through the ITS-G5 network, or to smart devices with Internet connectivity, through cloud-based services. Therefore, through its functionality, the system could send personalized notifications/information/warnings and recommendations for upcoming events to both road users and TMC operators. In the course of the ODOS2020 project pilot operation has been conducted to allow drivers of both C-ITS equipped and non-equipped vehicles to experience the provided added value services. For non-equipped vehicles, the provided information is transmitted to a smartphone application. Finally, the ODOS2020 system and infrastructure is appropriate for installation on both urban, rural, and highway environments. The paper presents the various parts of the system architecture and concludes by outlining the various challenges that had to be overcome during its design, development, and deployment in a real operational environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).

Keywords: infrastructure to vehicle, intelligent transportation systems, internet of things, road safety

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625 A Vehicle Detection and Speed Measurement Algorithm Based on Magnetic Sensors

Authors: Panagiotis Gkekas, Christos Sougles, Dionysios Kehagias, Dimitrios Tzovaras

Abstract:

Cooperative intelligent transport systems (C-ITS) can greatly improve safety and efficiency in road transport by enabling communication, not only between vehicles themselves but also between vehicles and infrastructure. For that reason, traffic surveillance systems on the road are of great importance. This paper focuses on the development of an on-road unit comprising several magnetic sensors for real-time vehicle detection, movement direction, and speed measurement calculations. Magnetic sensors can feel and measure changes in the earth’s magnetic field. Vehicles are composed of many parts with ferromagnetic properties. Depending on sensors’ sensitivity, changes in the earth’s magnetic field caused by passing vehicles can be detected and analyzed in order to extract information on the properties of moving vehicles. In this paper, we present a prototype algorithm for real-time, high-accuracy, vehicle detection, and speed measurement, which can be implemented as a portable, low-cost, and non-invasive to existing infrastructure solution with the potential to replace existing high-cost implementations. The paper describes the algorithm and presents results from its preliminary lab testing in a close to real condition environment. Acknowledgments: Work presented in this paper was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation (call RESEARCH–CREATE–INNOVATE) under contract no. Τ1EDK-03081 (project ODOS2020).

Keywords: magnetic sensors, vehicle detection, speed measurement, traffic surveillance system

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624 Assessment of Runway Micro Texture Using Surface Laser Scanners: An Explorative Study

Authors: Gerard Van Es

Abstract:

In this study, the use of a high resolution surface laser scanner to assess the micro texture of runway surfaces was investigated experimentally. Micro texture is one of the important surface components that helps to provide high braking friction between aircraft tires and a wet runway surface. Algorithms to derive different parameters that characterise micro texture was developed. Surface scans with a high resolution laser scanner were conducted on 40 different runway (like) surfaces. For each surface micro texture parameters were calculated from the laser scan data. These results were correlated with results obtained from a British pendulum tester that was used on the same surface. Results obtained with the British pendulum tester are generally considered to be indicative for the micro texture related friction characteristics. The results show that a meaningful correlation can be found between different parameters that characterise micro texture obtained with the laser scanner and the British pendulum tester results. Surface laser scanners are easier to operate and give more consistent results than a British pendulum tester. Therefore for airport operators surface laser scanners can be a useful tool to determine if their runway becomes slippery when wet due to a smooth micro texture.

Keywords: runway friction, micro texture, aircraft braking performance, slippery runways

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623 Worldwide Overview of Homologation for Radio Products

Authors: Nekzad R Doctor, Shubham Bhonde, Shashwat Gawande

Abstract:

The homologation, also known as “type approval,” describes primarily the granting of approval by an official authority. For the use and the import of Keys & ID transmitters as well as Body Control Modules with radio transmission around the globe, homologation is necessary. Depending on country requirements or technical properties (e.g., frequency or transmission power), different approaches need to be fulfilled. The requirements could vary in the form of certifications requirement or exemptions, any technologies forbidden, additional legal requirements and type approval for manufacturing locations. This research will give an overview of all different types of approval and technical requirement for worldwide countries.Information is not available for a lot of countries which is challenging for an entrant in the field of homologation. Also, even if the information is available, there could be a language barrier as different countries sometimes upload their regulations in a local language. Also, there is a lot of unclarity in many countries regarding type approval requirements (Safety, EMC certification,2nd factory certification). To have a clear overview and understanding of type approval requirements, in this document, the Worldwide country will be divided into 4 groups based on technology. After which, a region country-specific type approval requirement will be checked in detail. This document will facilitate in providing global Homologation requirements.

Keywords: homologation, type approval, EMC, body control modules

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622 Implementation of Data Science in Field of Homologation

Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

Abstract:

For the use and the import of Keys and ID Transmitter as well as Body Control Modules with radio transmission in a lot of countries, homologation is required. Final deliverables in homologation of the product are certificates. In considering the world of homologation, there are approximately 200 certificates per product, with most of the certificates in local languages. It is challenging to manually investigate each certificate and extract relevant data from the certificate, such as expiry date, approval date, etc. It is most important to get accurate data from the certificate as inaccuracy may lead to missing re-homologation of certificates that will result in an incompliance situation. There is a scope of automation in reading the certificate data in the field of homologation. We are using deep learning as a tool for automation. We have first trained a model using machine learning by providing all country's basic data. We have trained this model only once. We trained the model by feeding pdf and jpg files using the ETL process. Eventually, that trained model will give more accurate results later. As an outcome, we will get the expiry date and approval date of the certificate with a single click. This will eventually help to implement automation features on a broader level in the database where certificates are stored. This automation will help to minimize human error to almost negligible.

Keywords: homologation, re-homologation, data science, deep learning, machine learning, ETL (extract transform loading)

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621 The Impact of Shifting Trading Pattern from Long-Haul to Short-Sea to the Car Carriers’ Freight Revenues

Authors: Tianyu Wang, Nikita Karandikar

Abstract:

The uncertainty around cost, safety, and feasibility of the decarbonized shipping fuels has made it increasingly complex for the shipping companies to set pricing strategies and forecast their freight revenues going forward. The increase in the green fuel surcharges will ultimately influence the automobile’s consumer prices. The auto shipping demand (ton-miles) has been gradually shifting from long-haul to short-sea trade over the past years following the relocation of the original equipment manufacturer (OEM) manufacturing to regions such as South America and Southeast Asia. The objective of this paper is twofold: 1) to investigate the car-carriers freight revenue development over the years when the trade pattern is gradually shifting towards short-sea exports 2) to empirically identify the quantitative impact of such trade pattern shifting to mainly freight rate, but also vessel size, fleet size as well as Green House Gas (GHG) emission in Roll on-Roll Off (Ro-Ro) shipping. In this paper, a model of analyzing and forecasting ton-miles and freight revenues for the trade routes of AS-NA (Asia to North America), EU-NA (Europe to North America), and SA-NA (South America to North America) is established by deploying Automatic Identification System (AIS) data and the financial results of a selected car carrier company. More specifically, Wallenius Wilhelmsen Logistics (WALWIL), the Norwegian Ro-Ro carrier listed on Oslo Stock Exchange, is selected as the case study company in this paper. AIS-based ton-mile datasets of WALWIL vessels that are sailing into North America region from three different origins (Asia, Europe, and South America), together with WALWIL’s quarterly freight revenues as reported in trade segments, will be investigated and compared for the past five years (2018-2022). Furthermore, ordinary‐least‐square (OLS) regression is utilized to construct the ton-mile demand and freight revenue forecasting. The determinants of trade pattern shifting, such as import tariffs following the China-US trade war and fuel prices following the 0.1% Emission Control Areas (ECA) zone requirement after IMO2020 will be set as key variable inputs to the machine learning model. The model will be tested on another newly listed Norwegian Car Carrier, Hoegh Autoliner, to forecast its 2022 financial results and to validate the accuracy based on its actual results. GHG emissions on the three routes will be compared and discussed based on a constant emission per mile assumption and voyage distances. Our findings will provide important insights about 1) the trade-off evaluation between revenue reduction and energy saving with the new ton-mile pattern and 2) how the trade flow shifting would influence the future need for the vessel and fleet size.

Keywords: AIS, automobile exports, maritime big data, trade flows

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620 Exploring the Relationship between Building Construction Activity and Road-Related Expenditure in Victoria

Authors: Md. Aftabuzzaman, Md. Kamruzzaman

Abstract:

Road-related expenditure and building construction activity are two significant drivers of the Victorian economy. This paper investigates the relationship between building construction activity and road-related expenditure. Data for construction activities were collected from Victorian Building Authority, and road-related expenditure data were explored by the Bureau of Infrastructure and Transport Research Economics. The trend between these two sectors was compared. The analysis found a strong relationship between road-related expenditure and the volume of construction activity, i.e., the more construction activities, the greater the requirement of road-related expenditure, or vice-versa. The road-related expenditure has a two-year lag period, suggesting that the road sector requires two years to respond to the growth in the building sector.

Keywords: building construction activity, infrastructure, road expenditure, Victorian Building Authority

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619 Statistical Analysis and Impact Forecasting of Connected and Autonomous Vehicles on the Environment: Case Study in the State of Maryland

Authors: Alireza Ansariyar, Safieh Laaly

Abstract:

Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models

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618 Municipal Asset Management Planning 2.0 – A New Framework For Policy And Program Design In Ontario

Authors: Scott R. Butler

Abstract:

Ontario, Canada’s largest province, is in the midst of an interesting experiment in mandated asset management planning for local governments. At the beginning of 2021, Ontario’s 444 municipalities were responsible for the management of 302,864 lane kilometers of roads that have a replacement cost of $97.545 billion CDN. Roadways are by far the most complex, expensive, and extensive assets that a municipality is responsible for overseeing. Since adopting Ontario Regulation 588/47: Asset Management Planning for Municipal Infrastructure in 2017, the provincial government has established prescriptions for local road authorities regarding asset category and levels of service being provided. This provincial regulation further stipulates that asset data such as extent, condition, and life cycle costing are to be captured in manner compliant with qualitative descriptions and technical metrics. The Ontario Good Roads Association undertook an exercise to aggregate the road-related data contained within the 444 asset management plans that municipalities have filed with the provincial government. This analysis concluded that collectively Ontario municipal roadways have a $34.7 billion CDN in deferred maintenance. The ill-state of repair of Ontario municipal roads has lasting implications for province’s economic competitiveness and has garnered considerable political attention. Municipal efforts to address the maintenance backlog are stymied by the extremely limited fiscal parameters municipalities must operate within in Ontario. Further exacerbating the program are provincially designed programs that are ineffective, administratively burdensome, and not necessarily aligned with local priorities or strategies. This paper addresses how municipal asset management plans – and more specifically, the data contained in these plans – can be used to design innovative policy frameworks, flexible funding programs, and new levels of service that respond to these funding challenges, as well as emerging issues such as local economic development and climate change. To fully unlock the potential that Ontario Regulation 588/17 has imposed will require a resolute commitment to data standardization and horizontal collaboration between municipalities within regions.

Keywords: transportation, municipal asset management, subnational policy design, subnational funding program design

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617 Understanding Factor Influence in Mask-Wearing Intention Onboard Airplanes during COVID-19: Attitude as a Mediator

Authors: Jing Yu Pan, Dahai Liu

Abstract:

Airlines in the US have taken protective measures to battle the COVID-19 pandemic, with a mask mandate being the most important one, especially in the aircraft cabin. As the industry is recovering from the pandemic, mask-wearing will eventually become a personal choice during flight. Nevertheless, COVID-19 will continue to create uncertainty for a long time into the future, making it necessary to understand the attitude and voluntary use of masks by air travelers on airplanes even after masks are no longer mandatory. This study aimed to understand the relationship between demographic characteristics and mask-wearing intention in the US. For age, gender, income, educational, and ethnicity groups, this study examined three factors – subjective norms, risk avoidance, and information seeking and their influence on the mask-wearing intention onboard airplanes during COVID-19 and whether or not attitude toward masks was an important mediator. The results show that all demographic factors except gender could help to explain the group variations in factor impact and the mediating effect in mask-wearing intentions. In particular, Asian travelers had mask-wearing intentions that were not affected by attitude either directly or indirectly. These findings provide useful implications to enhance the health and safety of air travelers, especially in the US, where opposing views toward mask-wearing still widely exist.

Keywords: COVID-19, passenger demographics, aircraft cabin, mask-wearing intention, attitude as mediator

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616 Health Economics in the Cost-Benefit Analysis of Transport Schemes

Authors: Henry Kelly, Helena Shaw

Abstract:

This paper will seek how innovative methods from Health Economics and, to a lesser extent, wellbeing analysis can be applied in the Cost-Benefit Analysis (CBA) of transport infrastructure and policy interventions. The context for this will focus on the framework articulated by the UK Treasury (finance department) and the English Department for Transport. Both have well-established methods for undertaking CBA, but there is increased policy interest, particularly at a regional level of exploring broader strategic goals beyond those traditionally associated with transport user benefits, productivity gains, and labour market access. Links to different CBA approaches internationally, such as New Zealand, France, and Wales will be referenced. By exploring a complementary method of accessing the impacts of policies through the quantification of health impacts is a fruitful line to explore. In a previous piece of work, 14 impact pathways were identified, mapping the relationship between transport and health. These are wide-ranging, from improved employment prospects, the stress of unreliable journey times, and air quality to isolation and loneliness. Importantly, we will consider these different measures of health from an intersectional point of view to ensure that the basis that remains in the health industry does not get translated across to this work. The objective is to explore how a CBA based on these pathways may, through quantifying forecast impacts in terms of Quality-Adjusted Life Years may, produce different findings than a standard approach. Of particular interest is how a health-based approach may have different distributional impacts on socio-economic groups and may favour distinct types of interventions. Consideration will be given to the degree this approach may double-count impacts or if it is possible to identify additional benefits to the established CBA approach. The investigation will explore a range of schemes, from a high-speed rail link, highway improvements, rural mobility hubs, and coach services to cycle lanes. The conclusions should aid the progression of methods concerning the assessment of publicly funded infrastructure projects.

Keywords: cost-benefit analysis, health, QALYs transport

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615 Efficient Utilization of Negative Half Wave of Regulator Rectifier Output to Drive Class D LED Headlamp

Authors: Lalit Ahuja, Nancy Das, Yashas Shetty

Abstract:

LED lighting has been increasingly adopted for vehicles in both domestic and foreign automotive markets. Although this miniaturized technology gives the best light output, low energy consumption, and cost-efficient solutions for driving, the same is the need of the hour. In this paper, we present a methodology for driving the highest class two-wheeler headlamp with regulator and rectifier (RR) output. Unlike usual LED headlamps, which are driven by a battery, regulator, and rectifier (RR) driven, a low-cost and highly efficient LED Driver Module (LDM) is proposed. The positive half of magneto output is regulated and used to charge batteries used for various peripherals. While conventionally, the negative half was used for operating bulb-based exterior lamps. But with advancements in LED-based headlamps, which are driven by a battery, this negative half pulse remained unused in most of the vehicles. Our system uses negative half-wave rectified DC output from RR to provide constant light output at all RPMs of the vehicle. With the negative rectified DC output of RR, we have the advantage of pulsating DC input which periodically goes to zero, thus helping us to generate a constant DC output equivalent to the required LED load, and with a change in RPM, additional active thermal bypass circuit help us to maintain the efficiency and thermal rise. The methodology uses the negative half wave output of the RR along with a linear constant current driver with significantly higher efficiency. Although RR output has varied frequency and duty cycles at different engine RPMs, the driver is designed such that it provides constant current to LEDs with minimal ripple. In LED Headlamps, a DC-DC switching regulator is usually used, which is usually bulky. But with linear regulators, we’re eliminating bulky components and improving the form factor. Hence, this is both cost-efficient and compact. Presently, output ripple-free amplitude drivers with fewer components and less complexity are limited to lower-power LED Lamps. The focus of current high-efficiency research is often on high LED power applications. This paper presents a method of driving LED load at both High Beam and Low Beam using the negative half wave rectified pulsating DC from RR with minimum components, maintaining high efficiency within the thermal limitations. Linear regulators are significantly inefficient, with efficiencies typically about 40% and reaching as low as 14%. This leads to poor thermal performance. Although they don’t require complex and bulky circuitry, powering high-power devices is difficult to realise with the same. But with the input being negative half wave rectified pulsating DC, this efficiency can be improved as this helps us to generate constant DC output equivalent to LED load minimising the voltage drop on the linear regulator. Hence, losses are significantly reduced, and efficiency as high as 75% is achieved. With a change in RPM, DC voltage increases, which can be managed by active thermal bypass circuitry, thus resulting in better thermal performance. Hence, the use of bulky and expensive heat sinks can be avoided. Hence, the methodology to utilize the unused negative pulsating DC output of RR to optimize the utilization of RR output power and provide a cost-efficient solution as compared to costly DC-DC drivers.

Keywords: class D LED headlamp, regulator and rectifier, pulsating DC, low cost and highly efficient, LED driver module

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614 Numerical Investigation of 3D Printed Pin Fin Heat Sinks for Automotive Inverter Cooling Application

Authors: Alexander Kospach, Fabian Benezeder, Jürgen Abraham

Abstract:

E-mobility poses new challenges for inverters (e.g., higher switching frequencies) in terms of thermal behavior and thermal management. Due to even higher switching frequencies, thermal losses become greater, and the cooling of critical components (like insulated gate bipolar transistor and diodes) comes into focus. New manufacturing methods, such as 3D printing, enable completely new pin-fin structures that can handle higher waste heat to meet the new thermal requirements. Based on the geometrical specifications of the industrial partner regarding the manufacturing possibilities for 3D printing, different and completely new pin-fin structures were numerically investigated for their hydraulic and thermal behavior in fundamental studies assuming an indirect liquid cooling. For the 3D computational fluid dynamics (CFD) thermal simulations OpenFOAM was used, which has as numerical method the finite volume method for solving the conjugate heat transfer problem. A steady-state solver for turbulent fluid flow and solid heat conduction with conjugate heat transfer between solid and fluid regions was used for the simulations. In total, up to fifty pinfin structures and arrangements, some of them completely new, were numerically investigated. On the basis of the results of the principal investigations, the best two pin-fin structures and arrangements for the complete module cooling of an automotive inverter were numerically investigated and compared. There are clear differences in the maximum temperatures for the critical components, such as IGTBs and diodes. In summary, it was shown that 3D pin fin structures can significantly contribute to the improvement of heat transfer and cooling of an automotive inverter. This enables in the future smaller cooling designs and a better lifetime of automotive inverter modules. The new pin fin structures and arrangements can also be applied to other cooling applications where 3D printing can be used.

Keywords: pin fin heat sink optimization, 3D printed pin fins, CFD simulation, power electronic cooling, thermal management

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613 Optimization of Transmission Loss on a Series-Coupled Muffler by Taguchi Method

Authors: Jing-Fung Lin, Jer-Jia Sheu

Abstract:

In this study, an approach has been developed for the noise reduction of a muffler. The transmission loss (TL) in the muffler is maximized by the use of a double-chamber muffler, and a baffle with a hole is inserted between chambers. Taguchi method is used to optimize the design for the acoustical performance of the muffler. The TL performance is evaluated by COMSOL software. The excellent parameter combination for the maximum TL is attained as high as 35.30 dB in a wide frequency range from 10 Hz to 1400 Hz. The influence sequence of four parameters on TL is determined by the range analysis. The effects of length and expansion ratio of the first chamber on TL performance for the excellent program were discussed. Comparisons of the TL results from different designs are made.

Keywords: acoustics, baffle, chamber, muffler, Taguchi method, transmission loss

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612 Strategies for Building Resilience of 15-Minute Community Life Circles From the Perspective of Infectious Diseases

Authors: Siyuan Cai

Abstract:

COVID-19 has triggered the planning circles to think about how to improve the city's ability to respond to public health emergencies. From the perspective of the community, this article reviews the risk cases in Wuhan Chenjiadun Community and other communities under the epidemic, and analyzes the response to public health emergencies such as infectious disease outbreaks in the excellent cases of resilient epidemic prevention communities. Then, combined with the planning of the living circle, it demonstrates the necessity of integrating the concept of resilience into the 15-minute community living circle to make up for the shortcomings of infectious disease prevention. Finally, it is proposed to strictly control the source and tail of the epidemic in the layout of the living circle, daily health and epidemic emergency should be taken into account in planning, community medical resources should be decentralized in management, and the application of smart technologies in the planning of living circle should be fully emphasized, so as to improve the community's ability to respond to public health emergencies.

Keywords: pandemic, resilient cities, resilient community, 15-minute community life circle

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611 Investigate the Rural Mobility and Accessibility Challenges of Seniors

Authors: Tom Ryan

Abstract:

This paper investigates the rural mobility and accessibility challenges of a specific target group - Seniors. The target group is those over 66 years of age who are entitled to use the Public Transport (PT) Free Travel Scheme in rural Ireland. The paper explores at a high level some of the projected rural PT challenges and requirements over the next 10-15 years, noting that statistical predictions show that there will be a significant population demographic shift within the Senior's age profile. Using the PESTEL framework, the literature review explored existing research concerning mobility, accessibility challenges, and the opportunities Seniors face. Twenty-seven qualitative in-depth interviews with stakeholders within the ecosystem were undertaken. The stakeholders included: rural PT customers, Local-Link managers, NTA senior management, a Minister of State, and a European parliament policymaker. Tier 1 interviewee feedback spotlights that the PT network system does not exist for rural patients to access hospital facilities. There was no evidence from the Tier 2 research findings to show that health policymakers and transport planners are working to deliver a national solution to support patients getting access to hospital appointments. Several research interviewees discussed the theme of isolation and the perceived stigma of senior males utilising PT. The findings indicated that MaaS is potentially revolutionary in the PT arena. Finally, this paper suggests several short-, medium- and long-term recommendations based on the research findings. These recommendations are a potential springboard to ensure that rural PT is suitable for future Irish generations.

Keywords: accessibility, active ageing, car dependence, isolation, seniors health issues, behavioural changes, environmental challenges, internet of things, demand responsive, mobility as a service

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610 Optimum Tuning Capacitors for Wireless Charging of Electric Vehicles Considering Variation in Coil Distances

Authors: Muhammad Abdullah Arafat, Nahrin Nowrose

Abstract:

Wireless charging of electric vehicles is becoming more and more attractive as large amount of power can now be transferred to a reasonable distance using magnetic resonance coupling method. However, proper tuning of the compensation network is required to achieve maximum power transmission. Due to the variation of coil distance from the nominal value as a result of change in tire condition, change in weight or uneven road condition, the tuning of the compensation network has become challenging. In this paper, a tuning method has been described to determine the optimum values of the compensation network in order to maximize the average output power. The simulation results show that 5.2 percent increase in average output power is obtained for 10 percent variation in coupling coefficient using the optimum values without the need of additional space and electro-mechanical components. The proposed method is applicable to both static and dynamic charging of electric vehicles.

Keywords: coupling coefficient, electric vehicles, magnetic resonance coupling, tuning capacitor, wireless power transfer

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609 Improving the Run Times of Existing and Historical Demand Models Using Simple Python Scripting

Authors: Abhijeet Ostawal, Parmjit Lall

Abstract:

The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

Procedia PDF Downloads 99