Transportation System Improvements Research Articles

Enhancing Urban Mobility: Predicting Traffic Congestion with Optimized ML Model

Abstract Traffic congestion is a critical challenge in urban areas, leading to increased travel times, pollution, and a decreased quality of life. This study addresses this issue by developing a predictive model for traffic congestion using the eXtreme Gradient Boosting (XGBoost) machine learning model, enhanced with hyperparameter optimization and detrending techniques. Key traffic parameters, including waiting times, vehicle angles, latitude, longitude, and speeds, are incorporated to improve the model's accuracy. Compared to ARIMA and LSTM models, the proposed XGBoost model significantly outperforms these approaches. LSTM exhibits much higher prediction errors. The XGBoost model, with its lowest MAE (0.007), MSE (0.008), and an accuracy of 99.5%, demonstrates superior performance and efficiency. Implemented in Python using the SUMO simulator for real-time traffic data, the proposed model showcases robust predictive capabilities, contributing to smarter urban mobility solutions and improved transportation systems. These findings underscore the effectiveness of advanced machine learning techniques in predicting traffic congestion and provide valuable insights for developing smarter urban mobility solutions. The study’s contributions aim to enhance transportation systems and improve the overall quality of urban life.

RESEARCH AND EVALUATION OF LOGISTICS SCHEMES EFFICIENCY FOR THE GRAIN LOADS TRANSPORTATION FOR EXPORT UNDER THE CONDITIONS OF THE MILITARY STATE

Purpose. The aim of the work is to study the effectiveness of various logistics schemes for the delivery of grain cargoes for export from production sites to its transshipment points - to sea ports and to border terminals on the border with the countries of the European Union. Methodology. In the research process analysis and synthesis methods were used to study the content and main provisions of scientific publications on the state of the logistic system of transporting Ukrainian grain for export, the theory of operational work of railways for the development of logistics schemes for the delivery of grain cargoes, methods of mathematical statistics for the analysis of tariffs for road transportation, methods of technical economic calculations and determination of transportation tariffs. Results. In order to evaluate the effectiveness of grain delivery logistics schemes, the routes from one of the areas with the largest concentration of grain loading to a large seaport and to a railway and road border checkpoint were considered. At the same time, the following logistics schemes of grain delivery were chosen: automobile transportation by grain trucks and in containers, railway transportation by wagons and route shipments in grain wagons and in containers on fitting platforms. Calculations showed that transportation costs in the direction of ports are 10...15% lower than for transportation to land checkpoints; rail transportation is generally 30...40% cheaper than road transportation, and transportation in containers allows to save 20...25% of the cost of transportation. Scientific novelty. The obtained results make it possible to provide a scientific and economic basis for the development and improvement of the grain cargo transportation system, as well as for the optimization of the parameters of its individual links. Practical significance. Analysis and improvement of grain transportation logistics schemes will increase the efficiency of grain export logistics, reduce the share of the logistics component in the final cost of Ukrainian grain and, accordingly, increase both its competitiveness on foreign markets and foreign currency revenues to the state budget.

Assessing travel time performance of multimodal transportation systems using fuzzy-analytic hierarchy process: A case study of Bhopal City

Insufficient multimodal transportation infrastructure in Indian cities increases travel time, waiting time, traffic congestion, traffic accidents, travel costs, fast-growing energy consumption, and walking distance. The multimodal transportation system's journey time performance must be analysed to tackle these transportation concerns. Thus, this research provides a fundamental method for assessing multimodal transportation system trip time performance. This study proposes three steps for assessing travel time performance: identifying factors, generating individual indices, and evaluating the Multimodal Transport System Travel-Time Performance Index. The travel-time performance index of Bhopal city was 0.79 after evaluating the results of the individual indices (Access 0.49, In-vehicle 0.39, and Egress 0.38). Consequently, this study will help identify areas for improvement in Bhopal's multimodal transportation system and provide insights for enhancing its efficiency and user satisfaction. The proposed methodology can be applied to other cities facing similar challenges, aiding in the development of more sustainable and user-friendly transportation systems.

Analyze the Stochastic Solid Fuzzy Transportation Problem with Mixed Constraints through Weibull Distribution

This paper proposed a general formulation of the stochastic solid transportation problem (SSTP) with mixed constraints such as supply, demand and conveyance capacity taken as uncertain under stochastic environment, following the Weibull distribution (WD). The aim of this study is to minimize the transportation cost includes probabilistic constraints have inequalities of stochastic solid transportation problem (SSTP). SSTP with probabilistic constraints is represented as a chance constrained programming problem. Obtain alpha cut representation from cost coefficient of the fuzzy objective function. We have developed four models for stochastic solid transportation problem. The suggested models are demonstrated by taken as numerical example. A sensitivity analysis is performed to understand parameter’s sensitivity in the proposed model. Introduction: In system of transportation, goods are moved from various sources to destinations using different vehicles and organizational systems, involving both technology and human efforts. Efficient resource allocation in transportation system is crucial for industries and imprecision from factors like fluctuating demand, unreliable supply chains and unpredictable traffic. To address these complexities, advanced mathematical models are needed to manage stochasticity, fuzziness and mixed constraints. The study explores the stochastic solid fuzzy transportation problem with mixed constraint by utilizing the Weibull distribution to model uncertainties inherent in transportation systems. This research addresses the complexity introduced by stochastic variables and fuzzy parameters, particularly in situations where demand, supply and cost of transportation are not deterministic. Objectives: The aim of this study is to minimize the cost of transportation includes probabilistic constraints have inequalities of stochastic solid transportation problem (SSTP). Methods: Obtain alpha cut representation form the cost coefficient of the fuzzy objective function and four models are developed for stochastic solid transportation problem. These models are demonstrating by using a numerical example and a sensitivity analysis is conducted to understand the sensitivity of the parameters in the propose model. Results: Obtained optimal solutions for developed four models of SFSTPMC and sensitivity analysis shows that cost of transportation and flow of unit are sensitive to change in probabilities of demand. Improve transportation system by understanding sensitivity patterns that help decision maker choose appropriate supply availability probabilities. Conclusions: This study presented an approach for solving the SFSTPMC using the Weibull distribution for probabilistic constraints and fuzzy objective functions for transportation cost. Developed and optimized four models, focusing on stochastic parameters. Sensitivity analysis demonstrated the impact of these parameters on transportation cost and unit flow. The results validate the model’s effectiveness in practical resource allocation and decision making under uncertainty.

VESecure: Verifiable authentication and efficient key exchange for secure intelligent transport systems deployment

The Intelligent Transportation Systems (ITS) is a leading-edge, developing idea that seeks to revolutionize how people and things move inside and outside cities. Internet of Vehicles (IoV) forms a networked environment that joins infrastructure, pedestrians, fog, cloud, and vehicles to develop ITS. The IoV has the potential to improve transportation systems significantly, but as it is networked and data-driven, it poses several security issues. Numerous solutions to these IoV issues have recently been put forth. However, significant computing overhead and security concerns afflict the majority of them. Moreover, malicious vehicles may be injected into the network to access or use unauthorized services. To improve the security of the IoV network, the Mayfly algorithm is used to optimize the private keys continuously. To address these difficulties, we propose a novel VESecure system that provides secure communication, mutual authentication, and key management between vehicles, roadside units (RSU), and cloud servers. The scheme undergoes extensive scrutiny for security and privacy using the Real-or-Random (ROR) oracle model, Tamarin, and Scyther tools, along with the informal security analysis. An Objective Modular Network Testbed in OMNet++ is used to simulate the scheme. We prove our scheme's efficiency by comparing it with other existing methods regarding communication and computation costs.

Transfer payments and carbon reduction in China: The effect of the national comprehensive demonstration city of energy saving and emission reduction fiscal policy

To address climate change and achieve high-quality economic development, China began implementing the Comprehensive Demonstration City of Energy Saving and Emission Reduction Fiscal Policy (ESERFP) in 2011. This policy relies on special transfer payments to increase the integration of various energy conservation and emission reduction fiscal policies, thereby accelerating institutional and mechanism innovation, actively promoting economic structure adjustment and development mode transformation, and achieving energy conservation and emission reduction goals in various regions. This study uses a multi-period difference-in-difference (DID) model to estimate the ESERFP's CO2 emission reduction effect and paths. The findings demonstrate the following: (1) The ESERFP has lessened the CO2 emission intensity of the demonstration city and effectively played a role in reducing CO2 emissions. (2) Mechanism analysis demonstrates that the ESERFP has significantly improved the green travel level of residents in pilot cities and can also reduce cities' total energy consumption. Therefore, the ESERFP can effectively suppress CO2 emissions by improving transportation systems and optimizing energy consumption structures. (3) Further analysis shows that the ESERFP can reduce the CO2 emission scale of the demonstration cities and effectively promote the increase of actual per capita gross domestic product in pilot cities, bringing economic dividends and thus achieving a “win-win” situation of environmental protection and economic growth. (4) Heterogeneity analysis demonstrates that the CO2 emission reduction effect is more significant in non-old industrial-based cities, non-resource-based cities, and urban agglomerations. This study not only evaluates the CO2 reduction effect of the demonstration city but also provides reference significance for the improvement of subsequent environmental regulations. In addition, clarifying the implementation effect of the ESERFP can help alleviate ecological and environmental problems in the process of urban economic development in China and achieve the sustainable development goal of green transformation.

Analyzing the Evolution of Nepal's Tourism in 2022: Insights and Future Perspectives

This paper focuses into Nepal's internal aviation and tourism industries, underlining the essentiality of strategic planning. It investigates how Nepal's tourism sector has adapted to the global repercussions of COVID-19 and identifies successful strategies to increase tourism revenue following the pandemic. Through the application of both descriptive and inferential statistics, this research analyses data and visually conveys its conclusions. It emphasizes the importance of tailor-made marketing and promotional approaches designed for particular market segments and to exploit local strengths. The document evaluates recovery tactics post-COVID-19, the role of domestic tourism, and the need for upgrades in infrastructure and policies to foster the sustainable development of tourism in Nepal. The necessity for a cohesive approach among federal, provincial, and local governments to facilitate the proper allocation of resources and the execution of tourism initiatives is strongly advocated. The expansion of tourism-related infrastructure, including hotels with high star ratings and improved transport systems, is highlighted as a fundamental factor in supporting the surge of tourists to Nepal. The paper postulates that reinforcing economic development through policies favorable to the tourism industry will have a beneficial impact on international tourism. It urges a policy shift towards the improvement of tourism infrastructure and the adoption of technological innovations in its management.

Causal Loop Diagram of Banyumas Tourism Projection with Transportation System Improvement

Causal Loop Diagram of Banyumas Tourism Projection with Transportation System Improvement

Cybersecurity vulnerability and resilience of cooperative driving automation for energy efficiency and flow stability in smart cities

Increasing levels of communication and automation has led to the development of cyber physical systems applications known as cooperative driving automation. While such applications provide enormous benefits in improving transportation systems operation and environmental sustainability, they also introduce new risks to smart cities. These systems provide wider access to adversaries and increase the attack surface to compromise the operation of smart cities. This study develops a vehicle to infrastructure (V2I) based cooperative driving automation platform to understand and analyze the cyber risks in these systems from a V2I perspective in a representative traffic environment. Three cyberattacks (Fake BSMs, replay and denial of service) were emulated as a cooperative game to assess the impact on volatility, energy efficiency and traffic flow stability. The critical nature of cooperative driving automation is revealed by this research and flow stability, and energy efficiency of cooperative driving automation are severely impacted by the three categories of cyberattacks. Further, a 35 %-40 % increase in volatility in acceleration-deceleration regimes along with 20 % increase in emission is observed as opposed to the baseline case with no cyberattacks. The proposed long-short term memory neural networks (LSTM) showed an average detection accuracy of around 98 % for the analyzed cyberattacks. The research findings would foster the development of algorithms to continuously monitor the state of cooperative automated driving environment for anomalous behavior and promote resilient and environmentally sustainable cities in the future.

Adaptive Sustainable Mobility Solutions by Using Vehicle-Integrated Photovoltaic in Kigali City

In a fast-paced urbanized culture, sustainable transportation remains a significant challenge. Quick and smooth mobility of people and goods with the possibility of regulating traffic congestion and preventing climate change is essential for every public transportation user. Urban population in developing nations like Rwanda is expected to double by the year 2050, and balancing the supply and demand of the urban transport system will be a significant issue. Information technology enables elements within the transportation system, including vehicles, roads, traffic lights, and message signs, to become intelligent by embedding them with sensors, processors, algorithms, and actuators, thus empowering them to communicate through various technologies. These technologies improve transportation system performance by reducing congestion, increasing safety and traveler convenience, and protecting the climate against some greenhouse gases. Different mobility solutions are stated in this document. The use of electric vehicles, Passenger Information Systems, Car-sharing and ride-sharing services, electronic payment, Bus Signal Priority, and Vehicle-Integrated Photovoltaics. Using photovoltaics in Rwanda is adequate because of the electricity problem. This is the best solution for fighting against climate change due to fuel from motorized traffic.

Alternative prioritization for mitigating urban transportation challenges using a Fermatean fuzzy-based intelligent decision support model

Practitioners and decision-makers often face difficulties in selecting and prioritizing effective strategies to address challenges to sustainable urban transportation development. Although there has been considerable research conducted on the subject, the Tanzanian context, which is greatly affected by social and environmental problems, has received inadequate attention. Therefore, this study intends to bridge this gap by pinpointing the obstacles to sustainable urban transportation and proposing the most appropriate strategies to tackle them. The study proposes seven strategies and determines five criteria to prioritize them. To accomplish this, the study proposes a novel Fermatean fuzzy-based intelligent decision support model to assess the criteria weights and prioritizes strategies based on the weighted criteria. The study validates the proposed methodology by conducting a sensitivity analysis, which indicates that restricting car use (A5), improving sector coordination (A1), and conducting extensive research on transportation issues (A7) are the top three strategies for promoting sustainable urban transportation. The study’s findings hold significant value in providing urban transportation planners with helpful guidance to develop optimization techniques that can improve transportation systems.

Review of the Lifestyle Issues of the Khumi Community

The Khumi community is primarily patriarchal and is a notable ethnic group in Bangladesh, India, and Myanmar. They reside in the western part of Myanmar, specifically in the Arakan hill region. Their settlements are found in the hilly areas adjacent to the India-Bangladesh border. The data analysis reveals the comprehensive insights into the socio-demographic, health-related, education-related, income, and livelihood characteristics of the Khumi community in remote hilly regions of Bangladesh. Most of the participants are male, farmers, and Christian. Health issues, such as their eye problems and ankle pain, vary between the genders, with a notable reliance on local pharmacies for their healthcare services. Education-wise, illiteracy is prevalent, and economic and teacher-related obstacles hinder their education accessibility. Monthly and yearly income distributions highlight their economic disparities, with a significant proportion earning between the ranges of 3,001 to 5,500 Taka monthly. Livelihood-related characteristics showcase a heavily reliance on solar power, diverse agricultural practices, and predominantly nuclear family structures. The various challenges in livelihood, including economic, cultural, healthcare, education, communication, and linguistic issues, are addressed through the community-driven solutions. There are various notable efforts focus on water drainage, transportation system improvement, electricity infrastructure enhancement, primary school education, and agricultural training. Therefore, the study concludes that the Khumi community faces various economic vulnerability, educational disparities, and cultural erosion while the recommendations include community-centric development programs, education enhancement, healthcare access improvement, agricultural support, infrastructure development, preservation of culture, social welfare programs, government-community collaboration, research and data collection, and awareness and advocacy efforts. Implementing these numerous recommendations can contribute to the overall development of the Khumi community with addressing their various unique challenges and fostering the sustainable progress.

Perbandingan Sistem Levitasi Magnetik Ems dan Eds Untuk Maglev Indonesia

Maglev trains are considered for urban transport and intercity transport systems. On low-medium speed Maglev trains, the operating routine is shorter than that of high-speed trains. Therefore, EMS and LIM technologies are preferred from the point of view of construction costs. However, in high-speed operation, EDS and NGO technologies are preferred for handling, and reliability. In addition, as the development of high-temperature superconductors and new types of permanent magnets develop, stronger and more cost-effective magnetic energy will be used for Maglev trains. The authors believe this technology can be utilized not only for railway applications but also aircraft launch systems and spacecraft launch systems. The need for a new and improved transportation system prompted many countries to be interested and seek to develop Maglev railways. However, although Maglev trains have been studied and developed for approximately half a century, few countries have the knowledge and expertise to do so. This review paper attempts to describe the current complete system in detail and summarizes the basic core technologies of Maglev trains from an electrical engineering point of view. The research hopes to be useful for people interested in this to assimilate Maglev train technology including magnetic levitation, propulsion, guidance, and power supply systems.

Sustainable Rail/Road Unimodal Transportation of Bulk Cargo in Zambia: A Review of Algorithm-Based Optimization Techniques

Modern rail/road transportation systems are critical to global travel and commercial transportation. The improvement of transport systems that are needed for efficient cargo movements possesses further challenges. For instance, diesel-powered trucks and goods trains are widely used in long-haul unimodal transportation of heavy cargo in most landlocked and developing countries, a situation that leads to concerns of greenhouse gases (GHGs) such as carbon dioxide coming from diesel fuel combustion. In this context, it is critical to understand aspects such as the use of some parameters, variables and constraints in the formulation of mathematical models, optimization techniques and algorithms that directly contribute to sustainable transportation solutions. In seeking sustainable solutions to the bulk cargo long-haul transportation problems in Zambia, we conduct a systematic review of various transportation modes and related mathematical models, and optimization approaches. In this paper, we provide an updated survey of various transport models for bulk cargo and their associated optimized combinations. We identify key research challenges and notable issues to be considered for further studies in transport system optimization, especially when dealing with long-haul unimodal or single-mode heavy cargo movement in countries that are yet to implement intermodal and multimodal systems.

Echinostomes and Other Intestinal Trematode Infections.

Intestinal trematodes are among the most common types of parasitic worms. About 76 species belonging to 14 families have been recorded infecting humans. Infection commonly occurs when humans eat raw or undercooked foods that contain the infective metacercariae. These parasites are diverse in regard to their morphology, geographical distribution and life cycle, which make it difficult to study the parasitic diseases that they cause. Many of these intestinal trematodes have been considered as endemic parasites in the past. However, the geographical limits and the population at risk are currently expanding and changing in relation to factors such as growing international markets, improved transportation systems, new eating habits in developed countries and demographic changes. These factors make it necessary to better understand intestinal trematode infections. This chapter describes the main features of human intestinal trematodes in relation to their biology, epidemiology, host-parasite relationships, pathogenicity, clinical aspects, diagnosis, treatment and control.

IMPROVING MOBILITY IN KEDIRI CITY WITH MKJI ANALYSIS 1997 AND TIME SLICE AT SIMPANG EMPAT DHOHO PLAZA

The city of Kediri, as the third largest city in East Java, has cultural heritage, history and natural beauty that attracts visitors from various regions. However, population growth and motorized vehicles cause traffic jams. Signalized intersections, which are a solution to control intersection conflicts, require knowledge of intersection saturation flows to plan efficient traffic management. Analysis methods such as MKJI 1997 and Time Slice with Vehicle Operating Cost (BOK) calculations help design effective solutions. This research shows that adjusting cycle times, increasing effective width, and optimizing signals can improve transportation system performance and reduce congestion in Kediri City. Cycle time analysis taking into account factors such as vehicle type, traffic volume, and vehicle speed resulted in a cycle time of 90.7 seconds. The impact can be seen in the Degree of Saturation (DS) at various intersection arms, with service variations from E to F. Research also shows a decrease in waiting time/queuing for signal lights from 135 seconds to 118 seconds, which results in a decrease in the degree of saturation (DS) and changes in time cycle. The use of Smart Traffic Lights and traffic engineering, such as immediate left turns on the east arm and additional signs, is required. Evaluation of congestion cost efficiency shows that changing the value of side barriers can save Rp. 22,679,183 in the next five years.

Evaluating the Performance of a Visual Support System for Driving Assistance using a Deep Learning Algorithm

The issue of road accidents endangering human life has become a global concern due to the rise in traffic volumes. This article presents the evaluation of an object detection model for University of Malaysia Pahang (UMP) roadside conditions, focusing on the detection of vehicles, motorcycles, and traffic lamps. The dataset consists of the driving distance from Hospital Pekan to the University of Malaysia Pahang. Around one thousand images were selected in Roboflow for the train dataset. The model utilises the YOLO V8 deep learning algorithm in the Google Colab environment and is trained using a custom dataset managed by the Roboflow dataset manager. The dataset comprises a diverse set of training and validation images, capturing the unique characteristics of Malaysian roads. The train model's performance was assessed using the F1 score, precision, and recall, with results of 71%, 88.2%, and 84%, respectively. A comprehensive comparison with validation results has shown the efficacy of the proposed model in accurately detecting vehicles, motorcycles, and traffic lamps in real-world Malaysian road scenarios. This study contributes to the improvement of intelligent transportation systems and road safety in Malaysia.

Data Quality Analysis and Improvement: A Case Study of a Bus Transportation System

Due to the rapid development of the mobile Internet and the Internet of Things, the volume of generated data keeps growing. The topic of data quality has gained increasing attention recently. Numerous studies have explored various data quality (DQ) problems across several fields, with corresponding effective data-cleaning strategies being researched. This paper begins with a comprehensive and systematic review of studies related to DQ. On the one hand, we classify these DQ-related studies into six types: redundant data, missing data, noisy data, erroneous data, conflicting data, and sparse data. On the other hand, we discuss the corresponding data-cleaning strategies for each DQ type. Secondly, we examine DQ issues and potential solutions for a public bus transportation system, utilizing a real-world traffic big data platform. Finally, we provide two representative examples, noise filtering and filling missing values, to demonstrate the DQ improvement practice. The experimental results show that: (1) The GPS noise filtering solution we proposed surpasses the baseline and achieves an accuracy of 97%; (2) The multi-source data fusion method can achieve a 100% missing repair rate (MRR) for bus arrival and departure. The average relative error (ARE) of bus arrival and departure times at stations is less than 1%, and the correlation coefficient (R) is also close to 1. Our research can offer guidance and lessons for enhancing data governance and quality improvement in the bus transportation system.

Russia and China: Prospects for the Development of Urban Agglomerations

This research is aimed at studying the development of cities and agglomerations, which is an urgent problem equally for the People’s Republic of China and the Russian Federation. The level of urbanization increases with the development of territories, which makes it necessary to comprehend the processes taking place in urbanized regions and make management decisions to improve the quality of life and equalize it throughout the territory. Within the framework of these processes, the role of core cities remains, which are the centres of preferential development for the entire urban system as a whole.Aim. Comparative analysis of development trends in urbanized regions of China and Russia.Tasks. To analyse the main parameters of the quality of life in large cities of Russia and China. To consider the main trends in the development of urban agglomerations in the direction of its alignment. To determine the development and possibilities of mutual use of the experience of both countries in this process.Methods. The study uses a systematic approach with elements of a structural and functional approach and a comparative research method.Results and conclusion. As the main trends in the development of urbanized regions of Russia and China, the following are highlighted: the growth of the scale of territories and the concentration of a significant population on them, the associated aggravation of a number of problems, such as increasing competition in the integrated labour market, standardization and unification of the p rovision of basic services, increasing burden on local budgets and often limiting the autonomy of municipalities, the need to improve transport systems to increase the mobility of the population throughout the territory of the agglomeration.

The Development of the Transport System in Surkhandarya Province

Research of the transport system of Surkhandarya region shows that most rural districts have weak transport potential, which does not allow effective use of their mineral raw material potential. For this reason, ensuring the development and expansion of the existing regional transport systems, their modernization, regional improvement of the regional transport system is one of the urgent issues of today.