Current Transportation Systems Research Articles

The application of renewable energy in transportation systems in China

The energy consumption level in transportation is projected to continue its current upward trend until the year 2040. Motor gasoline and diesel are the most consumed energy sources in common transportation, followed by jet fuel and natural gas. Regrettably, biofuel and electric energy, which are renewable energy sources, had only a little contribution to overall energy consumption in transportation. This indicates that the use of renewable energy sources in transportation is still in its early stages. The rapid advancement of energy innovation is causing alarm among the general people. In 2020, greenhouse gas emissions from transportation reached a record high. In order to predict the future trajectory of renewable energy, it is crucial to closely monitor the utilization of nonrenewable energy sources in transportation, which is currently at a high level. This study examines the existing energy sources in China and utilizes reliable research papers and data to demonstrate the practicality of several energy advancements in current transportation systems. The study will employ a literature review method to examine the advancements in energy innovation within the domains of internal combustion engines and electric motors in automobiles, waterborne transportation, and aircraft.

Integrating Tehran metropolitan air pollution into the current transport system and sprawl growth: an emphasis on urban performance and accessibility

Air pollution is one of the most challenging issues for urban environment and environmental management. The goal of this study was to determine the impact of Tehran metropolitan's performance and accessibility on urban transportation and air pollution as sprawl grows. Tehran, with a population of 15.98 million people, has many environmental issues, including air pollution. Secondary data were collected from the Tehran Air Quality Control Company as well as Landsat satellite imagery (OLI). The raw data of intra-city and suburban traffic counts for spatial analysis of movements, combined with the raw data of measuring stations, were then used as a sample in the ArcGIS software environment for three selected days in 2013, 2014, and 2016. Following geometric and radiometric correction, programming methods and a multivariate regression algorithm were applied to the images, yielding results in the form of additional stations. According to the results obtained (about 3.29 m) root-mean-square error (RMSE), the Inverse Distance Weighting (IDW) model was used in air pollution maps for better assessment. The findings suggest that Tehran is not the only source of air pollution and that TMA performance and accessibility play a significant role in the amount of air pollution. Furthermore, there is a strong correlation (more than 75%) between air pollution maps and transportation flow maps on specific days (February 23, 2013, February 26, 2015, and December 28, 2016). Finally, the analysis of this situation in three circles showed that the highest volume of traffic was done in the city of Tehran (CBD), suburban area (Suburban), and suburban area (Exurban), respectively, and the pattern of distribution and spatial accumulation of pollution has also been a function of this situation.

TRAFFIC PULSE-ROADWAY CONTROL SYSTEM

Rapid transit and transportation networks are essential to any country's economic progress. Long wait times, lost fuel, and financial losses are the outcomes of poor management and traffic congestion. For the sake of national development, a quick, affordable, and effective traffic control system is thus absolutely essential. In many nations, keeping an eye on and managing urban traffic is turning into a significant issue. The Traffic Monitoring Authority needs to come up with innovative ways to solve this issue because there are more and more cars on the road. Using automation and intelligent control techniques is one option to enhance the current transportation system's traffic flow and safety. Efficient and quick congestion relief is the aim. The project includes sound sensors that can recognize emergency cars as they approach in order to improve emergency vehicle detection. By prioritizing and streamlining emergency vehicle traffic at signalized junctions, this cutting-edge feature seeks to enhance overall traffic management and response times. Additionally, the concept has a novel element for pedestrian safety: when a signal changes from red to orange or orange to green, a dynamically triggered block is deployed. By erecting a barrier that guarantees pedestrians are securely clear of traffic before crossing, this creative solution seeks to improve pedestrian safety. Keywords: Traffic jams, traffic surveillance, automation, and clever control techniques, Changes in signals, sound sensors, emergency vehicle detection, quicker reaction times, barriers, and pedestrian safety.

Beyond the Current State of the Art in Electric Vehicle Technology in Robotics and Automation

The improvement of electric vehicles and their parts is currently the subject of several recent innovations, with an emphasis on advancements in batteries, energy management systems, autonomous features, and charging infrastructure. The current logistics and transportation (L&T) systems comprise heterogeneous fleets made up of both conventional internal combustion engine cars and other vehicle types that use environmentally friendly technology, such as electric and plug-in hybrid vehicles. This helps significantly to the development of the upcoming generations of electric vehicles and promotes a more sustainable and effective ecosystem. This article offers insights into the most recent advancements in the field of electric cars (EVs) as new and innovative EV technologies based on data and statistics from science that may prove to be technically possible by 2030. Potential design and modeling techniques, including digital twins with linked IoT, are discussed in this paper. Additionally, all EV-related topics are covered, including hard-core battery material sciences, power electronics, and powertrain engineering, as well as market and environmental considerations and prospective technological obstacles and research gaps. This investigation is interesting since it offers thorough information on every facet of EVs. In conclusion, we offer to the readers several open issues in the field of EV as well as specific research directions to wrap up our work.

Study on energy capture characteristics of piezoelectric stack energy harvester for railway track

Railway traffic plays a pivotal role within the current transportation system, with ensuring its safety being of paramount importance. Real-time monitoring of train track health through sensor technology has emerged as a significant approach for achieving this objective. However, a persistent challenge lies in providing cost-effective and stable power to sensors in remote areas. This paper proposes the utilization of a novel piezoelectric stack energy harvester in railway systems to address this issue. The substantial and consistent vibration energy produced by railway operations makes it an ideal source for energy harvesting, unaffected by environmental conditions. Through simulation analysis and experimental verification, this study explores the impact of load size, load frequency, and external resistance on the energy harvesting efficiency of the proposed piezoelectric stack energy harvester. The results indicate that the output power of the energy harvester increases with the load size. Furthermore, the frequency significantly influences the energy capture efficiency when below 8 Hz, with minimal impact on frequencies above 8 Hz. Interestingly, the load dramatically affects the energy capture efficiency, even at higher frequencies. With the external resistance set to 250 kΩ, the harvester achieves a maximum output power of 42.76 mW.

STRATEGIES AND PUBLIC PARTICIPATION IN SOLID WASTE MANAGEMENT IN PORT LOKO CITY

To create a framework for long-term, sustainable solid waste management, this paper examines the Port Loko municipalitys solid waste management plan and public involvement. It sets out: to examine the waste management tactics employed by the Port Loko City Council; to evaluate the methods used for solid waste management transportation; to investigate whether dustbins are available for collecting solid waste throughout the city; to determine whether land fill is available; to evaluate the degree of public involvement in the procedures related to solid waste management; to create a framework for long-term, sustainable solid waste management. The primary means of addressing the objectives was by means of semi-structured interviews and discussions with diverse stakeholders and members of the municipalitys community. The current solid waste management system was examined in the study, along with input from the general public, to determine its advantages and disadvantages. It was found that Port Loko Citys current solid waste management system is not sustainable. The separation of waste is not provided for. Waste is not being collected or transported in an appropriate or sufficient manner. Officially, recycling and composting of waste are not permitted. People are not involved in the decision-making process regarding solid waste because the majority of the waste is disposed of in open landfills. Additionally, the study examined the recently suggested solid waste management system. It was discovered that the recently suggested system, which includes a framework for a two-stream waste segregation system, is superior to the current system. The current waste collection and transportation system is not as good as the proposed one. A key component of the plan is the composting of biodegradable waste. But to create a solid waste management system that is sustainable, important issues were left out of the proposed system

Hetero-associative Memory Based New Iraqi License Plate Recognition

As a result of recent developments in highway research as well as the increased use of vehicles, there has been a significant interest paid to the most current, effective, and precise Intelligent Transportation System (ITS). In the field of computer vision or digital image processing, the identification of specific objects in an image plays a crucial role in the creation of a comprehensive image. There is a challenge associated with Vehicle License Plate Recognition (VLPR) because of the variation in viewpoints, multiple formats, and non-uniform lighting conditions at the time of acquisition of the image, shape, and color, in addition, the difficulties like poor image resolution, blurry image, poor lighting, and low contrast, these must be overcome. This paper proposed a model by using Modify Bidirectional Associative Memory (MBAM), which is one type of Hetero-associative memory, MBAM works in two phases (learning and convergence phases) to recognize the number plate, and this proposed model can overcome these difficulties because MBAM's associative memory has a high ability to accept noise and distinguish distorted images, as well as the speed of the calculation process due to the small size of the network. The accuracy of plate region localization is 99.6%, the accuracy for character segmentation is 98%, and the achieved accuracy for character recognition is 100% in various circumstances

Urban-scale estimation model of carbon emissions for ride-hailing electric vehicles during operational phase

Ride-hailing Electric Vehicles (EVs) offer a dual benefit by mitigating carbon emissions and providing convenient transportation solutions. Nevertheless, current emissions estimation models for urban-scale lack consideration of the real-world travel behaviors during operational phase. This study extracted the characteristics of ride-hailing EVs in Shanghai and Shenzhen based on 14.77 million real-world driving records, and established an emission estimation model. The emission estimation model delineates the relationship between speed State of Charge (SOC) and operational efficient of ride-hailing EVs in cities. Compared to traditional methods relying on manufacturer-claimed energy consumption rates, the developed model demonstrates a 38.4% increase in accuracy. It reveals that ride-hailing EVs deviate from the optimal speed in approximately 90% of their trips under the current urban transportation system. A 5 km/h increase in ride-hailing EV speed can improve emission reduction potential, cutting annual emissions by 0.89 ktCO2 in Shanghai and 4.74 ktCO2 in Shenzhen. Additionally, when a ride-hailing EV operates with SOC between 10 and 30%, emissions are 21.4%–36.0% higher compared to SOC between 70 and 90%. At last, the model derives emission factors for ride-hailing EVs during operational phase in Shanghai and Shenzhen are 0.2635 and 0.1535 10−5MtCO2kWh−1km−1

Exploring Sustainable Public Transport System for the Provision of Quality Education Services in Public Universities: A Situational Analysis

This study was conducted to explore the experience of university community regarding the use of available public transport in public universities in Tanzania. The study intended to explore the common transport systems used within the public universities; the risks and challenges of using the available transport systems in execution of day-to-day core functions of the university; and lastly, the effective and efficient transport systems in promoting the teaching and learning process in public universities. A cross-sectional survey design with mixed research approaches was employed. Probability and non-probability sampling techniques were used to get a total sample of 125 respondents from public universities in Tanzania. Data were collected by using self-administered semi-structured questionnaires and in-depth interview. The findings revealed that common transport systems used within the campuses included motorcycle hire, commuter buses, walking, bicycle hire, private bicycle, private motorcycle, university buses, bajaji (rickshaws) hire, and taxi cabs. Moreover, the study revealed that the risks and challenges of using the current transport system within the university campuses included time consuming, costly, and getting late to classes, accident, tiredness, and theft. Furthermore, the study revealed that the effective and efficient transport system within university campuses included the commuter buses, motorcycle hire, private motorcycle, walking, and private cars. The study recommends establishing an internal transportation pool which will be able to offer sustainable, reliable, effective and efficient transportation means within the university. Understanding the campus impediments may help universities design more attractive and useful transport facilities. The current study will inform the university management about the need to promote bicycling and walking which are ecological friendly; improve social interactions; as well as spur physical well-being among the students, staff and university community.

An exact second order cone programming approach for traffic assignment problems

Demographic changes, urbanization and increasing vehicle ownership at unprecedented rates put a lot of strain on cities particularly on urban mobility and transportation and overwhelm transportation network infrastructures and current transportation systems, which are not built to cope with such a fast increasing demand. Traffic congestion is considered as the most difficult challenge to tackle for sustainable urban mobility and is aggravated by the increased freight activity due to e-commerce and on-demand delivery and the explosive growth in transportation network companies and ride-hailing services. There is a need to implement a combination of policies to ensure that increased urban traffic congestion does not lower the quality of life and threaten global climate and human health and to prevent further economic losses. This study aims to contribute to the United Nations (UN) climate action and sustainable development goals in tackling recurring traffic congestion problem in urban areas to achieve a sustainable urban mobility in that it offers a solution methodology for traffic assignment problem. We introduce an exact generalized solution methodology based on reformulation of existing traffic assignment problems as a second order cone programming (SOCP) problem and propose column generation (CG) and cutting plane (CP) algorithms to solve the problem effectively for large scale road network instances. We conduct numerical experiments to test the performance of the proposed algorithms on realistic road networks.

TRANSIENT ANALYSIS OF LIQUID-HYDROGEN TRANSFER IN CRYOGENIC STORAGE TANKS

Efficient transfer of liquid hydrogen is critical for a myriad of processes in terrestrial and extraterrestrial applications. The objective of this study is to model and quantify the amount of liquid parahydrogen vaporized during a discharging/charging process in a cryogenic storage system. The effects that are included include geometrical effects (storage tank volume), two-phase compressible flow, choking/unchoking, and wall-fluid heat transfer. A brief description of other physical boil-off mechanisms is also presented. This study provides a foundation for applicationspecific optimization. The storage system studied comprises two interconnected tanks whose transfer line has a variation in the flow area. This simulates current liquid-hydrogen storage and transportation systems. The model tracks the temperature- and pressure-time histories of liquid hydrogen as it flows between storage tanks, in both the choked and unchoked flow regimes. The transfer of liquid is induced solely by the pressure differential that exists between the two storage tanks. An iterative technique helps account for choking, which is likely to exist at the throat in two-phase flow. Cases of zero and infinite tank-wall thermal mass are also discussed. By analyzing the behavior of fundamental variables during the transient transfer of liquid hydrogen, boil-off losses may be minimized if the variables with the greatest effect on boil-off losses are controlled.

Enhancing passenger comfort and operator efficiency through multi-objective bus timetable optimization

<abstract> <p>The current public transportation systems predominantly rely on rigid schedules and service patterns, leading to suboptimal resource allocation that impacts both passengers and transit operators. This inefficiency results in the wastage of resources and dissatisfaction among users. The unsatisfactory passenger experience significantly contributes to the declining ridership, thereby diminishing revenue for transit operators. To specifically address these challenges encountered by Lhasa's public transportation system, we propose a multi-objective model for bus departure timetables. The model aims to synchronize the costs of passenger waiting time and bus operation costs concurrently, accounting for diverse constraints such as actual travel times, operational bus numbers, bus capacity limits, and arrival time distributions. In this research, we establish a multi-objective optimization model with the primary goal of maximizing passenger satisfaction while concurrently optimizing the revenue of the transit company. Implemented in Lhasa, China, we use the Non-Dominated Sorting Genetic Algorithm-Ⅱ to derive Pareto fronts relevant for analysis. The research findings demonstrate a reduction in the frequency of departures by one bus within a one-hour timeframe. Additionally, a substantial 37% decrease is observed in both the count of buses not arriving at stations and the number of passengers waiting at these stations compared to previous timetables. These results suggest promising potential for significant benefits to both the transit company and passengers within the public transportation system.</p> </abstract>

Analysis of trip frequency choice of commute trips in the context of COVID-19 in India: A hybrid choice modelling approach with generalized ordered logit kernel

The paradigm shift in mobility and travel behaviour caused by the successive waves of the COVID-19 pandemic has been unreal. The long-term effects of the pandemic resulting from the fear of the spread of the virus against the belief in the remedial measures are to be understood from a behavioural perspective to strengthen the current transportation system against such impediments. The current study adds to the literature on COVID-19 pandemic by unravelling the long-term impacts of the pandemic on the trip frequency of commute trips. A dataset of 467 individuals from all over India is analysed to understand the factors impacting the willingness of the respondents to reduce their commute trips in a post-vaccinated scenario. An integrated choice and latent variable structure, with a generalized ordered logit kernel, was considered to incorporate the influence of psycho-attitudinal variables and socio-demographics on the willingness to reduce trip frequency among individuals. The results indicate a significant impact for variables including fear of the virus spread, age of individuals, and job satisfaction of working from home on the stated willingness towards trip reduction. The study concludes by presenting policy measures that target to overcome the effects of the pandemic and restore normalcy.

Intelligent Traffic System (ITS)

Abstract: One of the main issues of the modern day is effectively monitoring traffic. The influence on automobiles has increased in step with the population's exponential growth during the past century. The current transportation systems are under a great deal of strain as a result of this. Several traffic systems still operate today, ignoring the amount of traffic at that intersection, by assigning set timeslots to each traffic light. Millions of people lose valuable time in traffic as a result, while noise and air pollution also negatively impact the environment. In order to address these issues, we provide a system that controls traffic by using the main element of taking into account traffic density in real time. In order to accomplish its objective, this system makes use of cameras in addition to image processing.

Enhancing The Service Quality of The Tour and Travel SME By Integrating Servqual Dimensions, Kano Model, and Fishbone Diagram

Transportation services are one of the prominent sectors in the movement of the economy. The current transportation system should be arranged in an integrated manner in a single national-scale system to balance the readiness of transportation services and public needs. A proper transportation system can lead to the realization of the goal of building a firm infrastructure and sustainable-inclusive industrialization in the future. Qualitative case study of an SME in Indonesia using the Servqual, Kano, and Fishbone diagram. These three methods can analyze the relationship between quality attributes and determine the factors that influence the quality of a product or service. This study obtained analysis results using the Servqual method that six attributes have the highest gap between reality and expectations. Based on the results using the Kano Model, three classification categories include ten attributes, namely (1) Category O (One Dimensional), (2) Category R (Reverse), and (3) Category Q (Questionable). In addition, analysis of 10 service attributes that are priorities for improvement using the Fishbone diagram produces four main factors (Man, Machine, Environment, and Method) that influence the quality of SME services. This study enriches reference material for considerations in improvement efforts of service attribute weaknesses for transportation service SMEs.

Vehicle Trajectory Data Mining for Artificial Intelligence and Real-Time Traffic Information Extraction

It aims to improve the efficiency of information collection and extraction in the current intelligent transportation system, and accurately mine the vehicle trajectory data By using Artificial Intelligence (AI) and Deep Learning methods, the trajectory data generated during vehicle driving are deeply mined and analyzed, and the characteristics of driving behavior of vehicle drivers are modeled and analyzed in detail. Then, a method of mining driving behavior characteristics based on Convolutional Neural Network (CNN) and vehicle trajectory is proposed. Based on the mathematical principle of wavelet packet and Least Square Support Vector Machine (LSSVM), a combined model of trajectory mining is constructed and applied to the short-term prediction of traffic flow. The traffic flow of Binjiang Road and Renmin Road in Guangzhou, Guangdong Province from August 19 to August 21, 2021 is predicted to verify the accuracy of the trajectory mining combined model. The results show that the combination model of data mining has good fitting effect, and the average accuracy is above 0.8. Besides, the effectiveness of the Deep Learning model in driver behavior classification is verified. The accuracy of the classification model is 75.2% for trajectory, and that is 76.8% for driver behavior characteristics. It is of great significance to effectively utilize the knowledge data in Intelligent Transportation System (ITS) and extract valuable information from it, which has certain reference value for the subsequent refined prediction of vehicle behavior.

Parking Prediction in Smart Cities: A Survey

With the growing number of cars in cities, smart parking is gradually becoming a strategic issue in building a smart city. As the precondition in smart parking, accurate parking prediction can reduce the time drivers spend searching for parking spaces and relieve traffic congestion. Meanwhile, VANET and the Internet-of-things (IoT) are the key elements of the current intelligent transportation system. With the IoT devices based on VANET becoming more extensively employed, a large amount of parking data is generated every day, and various methods are proposed for parking prediction, therefore, it is time to systematically summarize the parking prediction issues and the state-of-the-art prediction methods. In this survey, we first provide a comprehensive review of the existing methods used for parking prediction ranging from conventional statistical methods to the latest graph neural network methods. Then, we classify a variety of parking problems such as parking availability prediction, parking behavior prediction, and parking demand prediction. We also compile all the evaluation metrics, open data, and open-source code of the surveyed literature. Finally, we present the challenges and future directions of the parking prediction technique. As far as we know, this is the first survey exploring parking prediction methods, which will be of interest to both researchers and practitioners engaging in intelligent transportation systems (ITS) and smart cities.

The role of hydrogen in a decarbonised future transport sector: A case study of Mexico

In recent years, several approaches and pathways have been discussed to decarbonise the transport sector; however, any effort to reduce emissions might be complex due to specific socio-economic and technical characteristics of different regions. In Mexico, the transport sector is the highest energy consumer, representing 38.9% of the national final energy demand, with gasoline and diesel representing 90% of the sector´s total fuel consumption. Energy systems models are powerful tools to obtain insights into decarbonisation pathways to understand costs, emissions and rate of deployment that could serve for energy policy development. This paper focuses on the modelling of the current Mexican transport system using the MUSE-MX multi-regional model with the aim to project a decarbonisation pathway through two different scenarios. The first approach being business as usual (BAU) which aims to analyse current policies implementation and the second being a goal of net zero carbon emissions by 2050. Under the considered net zero scenario, results show potential deployment of hydrogen-based transport technologies, especially for subsectors such as lorries (100% H2 by 2050) and freight train (25% H2 by 2050), while cars and buses tend to full electrification by 2050.

AMU-LED Cranfield Flight Trials for Demonstrating the Advanced Air Mobility Concept

Advanced Air Mobility (AAM) is a concept that is expected to transform the current air transportation system and provide more flexibility, agility, and accessibility by extending the operations to urban environments. This study focuses on flight test, integration, and analysis considerations for the feasibility of the future AAM concept and showcases the outputs of the Air Mobility Urban-Large Experimental Demonstration (AMU-LED) project demonstrations at Cranfield University. The purpose of the Cranfield demonstrations is to explore the integrated decentralized architecture of the AAM concept with layered airspace structure through various use cases within a co-simulation environment consisting of real and simulated standard-performing vehicle (SPV) and high-performing vehicle (HPV) flights, manned, and general aviation flights. Throughout the real and simulated flights, advanced U-space services are demonstrated and contingency management activities, including emergency operations and landing, are tested within the developed co-simulation environment. Moreover, flight tests are verified and validated through key performance indicator analysis, along with a social acceptance study. Future recommendations on relevant industrial and regulative activities are provided.

Review of Methods for Evaluating the Energy Efficiency of Vehicles with Conventional and Alternative Power Plants

The evaluation of the energy efficiency of vehicles in operating conditions is used to solve management and control tasks in intelligent transport systems. The modern world fleet is characterized by an increase in the share of vehicles with alternative power plants (hybrid, electric, and hydrogen fuel cells). At the same time, vehicles with conventional power plants (internal combustion engines) remain in operation. A wide range of modern power plants determines the relevance of studying the advantages and limitations of existing methods of evaluating the vehicle energy efficiency, delineating the application scope and highlighting promising directions for their further development. The article systematizes the methods of evaluation and management of the energy efficiency of vehicles with conventional and alternative power plants. Special attention is paid to the assessment of energy consumption per unit of transport work at the stage of vehicle operation, taking into account various operational factors. The concept of a 3D morphological model of the transport system for evaluating the energy efficiency of vehicles is presented. An algorithm for the optimization of the current transport system configuration according to the criterion of an increase in the energy efficiency indicator is given.