Backbone Of Transport Research Articles

Open E-Bus Blueprint

Buses form the backbone of public transportation in India, catering to 39.9 crore (399 million) passengers daily and accounting for over 90% of all public transport trips. As part of a broader goal to reduce transport emissions, India is looking to electrify up to 800,000 buses in the next seven years, including public, private and institutional fleet. Given the different dynamics of operating electric buses, a more connected and digital ecosystem can be a potential game changer in this transition.

Tracing Root Causes of Electric Vehicle Fires

As electric vehicles (EVs) emerge as the backbone of modern transportation, the concurrent uptick in battery fire incidents presents a disconcerting challenge. To tackle this issue effectively, it is imperative to pierce beyond the superficial causes of lithium‐ion battery (LIB) failures—such as equipment malfunctions or physical damage—and to excavate the underlying triggers. This nuanced approach is pivotal to refining EV quality, diminishing fire incidents, and bolstering consumer trust. While issues that are readily apparent to consumers, like spontaneous battery degradation, vehicular collisions, or submersion, may seem like the primary culprits, they merely scratch the surface of a more complex problem. The true mechanisms behind these fires involve internal and external short circuits, yet these explanations fall short in providing actionable guidance for manufacturers or end‐users to enhance LIB safety. The heart of the issue is identifying the root causes that bridge failure triggers and resulting fires. A total of 20 root causes are identified, linking them to real‐world scenarios like overcharging causing internal shorts or wire harness issues leading to external shorts. With this insight, stakeholders can more effectively investigate and understand EV LIB fire incidents, bolstering EV safety and reliability, and promoting consumer confidence.

Potassium Phthalimide Doped with Delta‐Site Structures to Construct Ultra‐Long Cycle Life Aqueous Zn‐Polymer Batteries

AbstractAqueous Zn‐polymer batteries hold great promise for environmentally friendly energy storage systems. However, the poor cycling performance caused by irreversible structural deformation and polymer chain entanglement during the embedding and de‐embedding processes of Zn2+ and H+ ions is one of the key challenges facing their development. Here a new polyaniline cathode doped is developed with potassium phthalimide using a secondary doping approach. This polymeric electrode integrates the conjugated backbone for charge transport with an anionic phthalimide dopant for constructing a triangular‐site structure, as illustrated by the density functional theory calculations. This unique molecular structure is favorable for improving conductivity and structural stability by effectively modulating the localized electron cloud density. The Zn‐polymer battery holds an outstanding capacity retention of 76.1% after 25,000 cycles at a current density of 1 A g−1 with the coulombic efficiency maintained above 99.4%. This secondary doped polymer strategy offers a new host alternative for the ultra‐long cycle life of Zn‐polymer batteries. The molecular design strategy and the insight into the relationship between the structure and performance may provide some guidelines for developing polymer cathodes with high stability.

Realistic U.S. Long-Haul Drive Cycle for Vehicle Simulations, Costing, and Emissions Analysis

Although heavy-duty trucks constitute the backbone of freight transportation in the United States, they also contribute significantly to greenhouse gas emissions. Various alternative powertrains to reduce emissions have been assessed, but few specific to U.S. long-haul applications with a consistent basis of assumptions. To enable a more accurate assessment for all stakeholders, a representative drive cycle for long-haul truck operations in the United States is introduced (USLHC8) for modeling and simulation purposes. This was generated from 58,000 mi of real driving data through a unique random microtrip selection algorithm. USLHC8 covers a total driving time of 10 h 47 min, an average vehicle speed of 55.58 mph, and road grade ranging from −6% to +6%. To establish a benchmark for further powertrain comparisons, a vehicle-level simulation of a conventional diesel powertrain was paired with USLHC8. Benchmarks are presented for fuel consumption, well-to-wheel emissions, and total cost to society under different scenarios (present-day, mid-term, and long-term).

A composite index for the evaluation of sustainability in Latin American public transport systems

Latin American public transport (PT) systems are the backbone of urban transport with high ridership levels but at the same time, they face substantial deficits in terms of their sustainability. No comprehensive framework for PT sustainability assessment exists so far that is tailored to the specific local situation in this region. Therefore, this study develops for the first time a theoretically sound and feasible index for assessing the sustainability of PT systems in Latin America, the Sustainable Public Transport Index for Latin America (SPTI-LATAM). The index is based on an Assessment Indicator Model (AIM) with overall 49 indicators in the five dimensions system effectiveness, social, environmental, economic, governance and integrated transport planning. The SPTI-LATAM is designed with three levels: 1) the basic index (BSPTI) containing 32 indicators; 2) the extended index (ESPTI) including 11 additional indicators; and 3) the global index (GSPTI) with 6 additional indicators. The BSPTI is computed for eleven case study cities to demonstrate its feasibility and to analyze the sustainability of PT systems in the region. The framework uses the Equal Weighting Aggregation (EWA) method for assigning weights to each indicator, the Weighted Sum Model (WSM) for aggregating the indicators to the overall index and international standards and benchmarks for normalization. The final scores of the BSPTI show that the case study cities have still challenges to reach sustainability since only two cities had scores slightly higher than the half of achievable points (55 and 51), while eight cities had scores between 40 and 50 points, and one city achieved 39 points. Deficits are identified mainly for PT service quality, for the environmental performance, for the governance dimension and less for PT system coverage. Overall, the analysis of the BSPTI-LATAM for the 11 case study cities shows that the index is suitable for benchmarking sustainability of local PT systems and ready to be used in research and practice.

Beam management optimization for V2V communications based on deep reinforcement learning

Intelligent connected vehicles have garnered significant attention from both academia and industry in recent years as they form the backbone of intelligent transportation and smart cities. Vehicular networks now exchange a range of mixed information types, including safety, sensing, and multimedia, due to advancements in communication and vehicle technology. Accordingly, performance requirements have also evolved, prioritizing higher spectral efficiencies while maintaining low latency and high communication reliability. To address the trade-off between communication spectral efficiency, delay, and reliability, the 3rd Generation Partnership Project (3GPP) recommends the 5G NR FR2 frequency band (24 GHz to 71 GHz) for vehicle-to-everything communications (V2X) in the Release 17 standard. However, wireless transmissions at such high frequencies pose challenges such as high path loss, signal processing complexity, long pre-access phase, unstable network structure, and fluctuating channel conditions. To overcome these issues, this paper proposes a deep reinforcement learning (DRL)-assisted intelligent beam management method for vehicle-to-vehicle (V2V) communication. By utilizing DRL, the optimal control of beam management (i.e., beam alignment and tracking) is achieved, enabling a trade-off among spectral efficiency, delay, and reliability in complex and fluctuating communication scenarios at the 5G NR FR2 band. Simulation results demonstrate the superiority of our method over the 5G standard-based beam management method in communication delay, and the extended Kalman Filter (EKF)-based beam management method in reliability and spectral efficiency.

Vision Zero application on Czech railways

The railway is perceived as a modern, safe and environmentally sustainable way of transporting people and goods. In the past, appropriate innovations in the field of infrastructure and vehicles, combined with an attractive operational concept, have gradually become the backbone of public transport in the country. Even in this system, similar to other transport systems, there are accidents (events of emergency) or potentially risky situations. The paper places the issue of railway safety in the legislative context and uncovers the points of view from which the safety of railway traffic can be viewed.

Understanding the Spatiotemporal Impacts of the Built Environment on Different Types of Metro Ridership: A Case Study in Wuhan, China

As the backbone of passenger transportation in many large cities around the world, it is particularly important to explore the association between the built environment and metro ridership to promote the construction of smart cities. Although a large number of studies have explored the association between the built environment and metro ridership, they have rarely considered the spatial and temporal heterogeneity between metro ridership and the built environment. Based on metro smartcard data, this study used EM clustering to classify metro stations into five clusters based on the spatiotemporal travel characteristics of the ridership at metro stations. And the GBDT model in machine learning was used to explore the nonlinear association between the built environment and the ridership of different types of stations during four periods in a day (morning peak, noon, evening peak, and night). The results confirm the obvious spatial heterogeneity of the built environment’s impact on the ridership of different types of stations, as well as the obvious temporal heterogeneity of the impact on stations of the same type. In addition, almost all built environment factors have complex nonlinear effects on metro ridership and exhibit obvious threshold effects. It is worth noting that these findings will help the correct decisions be made in constructing land use measures that are compatible with metro functions in smart cities.

Methods to Assess the Locations of Transport and Logistics Centers in the Backbone Network

The existing «gaps» in the evaluation tools of the transport and logistics infrastructure locations lead to low spatial efficiency of the transport and logistics centres (TLC) backbone network. There is a need to supplement the existing system with new methods of assessment, which integrate sectoral and territorial aspects of the efficiency of TLC deployment, increase the validity of strategies for the development of transport industries, the spatial development strategy of the Russian Federation, which was the main purpose of the study. The proposed methods of assessing TLC locations on the basis of partial indicators, integral rank indicator eliminate randomness in the choice of parameters of estimation. The scientific novelty of the study results is achieved by the principle of the criteria uniformity of territorial and sectoral efficiency of TLC locations. The practical relevance of the research consists in the proposed tools and methodological capabilities of assessment methods.

Sustainability evaluation methods for public transport with a focus on Latin American cities: A literature review

Stakeholders worldwide commit to the goal of sustainable development and transport, and to the promotion of public transport (PT) as one backbone of sustainable transport. Evaluation frameworks have been developed to aid municipalities and operators in purposefully shaping their PT systems. These frameworks differ greatly in their scope and consideration of the different sustainability dimensions, and in addition, they focus on industrialized countries. The goal of this study is to provide a systematic overview of existing frameworks for evaluating the sustainability of PT systems with a particular focus on Latin America for the first time, to identify possible gaps that result from the specific characteristics of Latin American PT systems and finally to derive research needs and recommendations for this region. The analysis includes three types of articles: scientific papers, international guidelines published by NGOs, and local as well as national Latin American guidelines for PT evaluation. The 69 identified relevant references reveal that Multi-Criteria Decision-Making (MCDM), followed by Assessment Indicator Models (AIM) are the preferred evaluation frameworks. Among the MCDM methods, the Analytical Hierarchy Process was the most frequently approach. We found a high prevalence of studies taking society and municipalities’ perspective (both 46%), followed by combinations (users, operators, municipalities − 37%), and the users’ perspective (14%). The review further shows that the Latin American context is not sufficiently considered in the existing frameworks and that further research is needed to develop frameworks that comprehensively and systematically consider all sustainability dimensions for this specific spatial context.

CO2 emissions reduction performance of China's HSR based on substitution effect and demand effect

Abstract As an important transportation infrastructure and transportation backbone in China, high-speed rail (HSR) plays a critical role in promoting the development of green and low-carbon transportation. Calculating the CO2 emissions reduction performance of HSR will be conducive to promote the CO2 emissions reduction work of the railway. Based on the Dalkic HSR CO2 emissions reduction performance model, by adjusting the HSR CO2 emission factor (CEFHSR), the annual times of departures (T) and other parameters, this study develops a Chinese HSR CO2 emissions reduction performance model. Taking the Beijing-Shanghai HSR as the research object, this study conducts a questionnaire survey to explore the substitution effect and demand effect of HSR on different transportation modes; collects data such as passenger volume, average electricity use and annual times of departures of the Beijing-Shanghai HSR in 2019; and calculates the CO2 emissions reduction performance of the Beijing-Shanghai HSR. This study has two main results: (1) It builds a Chinese HSR CO2 emissions reduction performance model based on substitution effect and demand effect. (2) In 2019, the CO2 emissions of the Beijing-Shanghai HSR are 2 898 233.62 t, the CO2 emissions reduction performance of the Beijing-Shanghai HSR is 17 999 482.8 t, the annual CO2 emissions of the Beijing-Shanghai line in ‘No HSR’ case are 7.2 times as in the 'HSR' case and the PKT of the HSR is 10.2 g/pkm. Based on the research results, this study proposes three CO2 emissions reduction policy suggestions. This study would be helpful for further HSR CO2 emissions reduction research and departments related to railway transportation management to make CO2 emissions reduction policies.

Hydrogen Internal Combustion Engine Vehicles: A Review

Motor vehicles are the backbone of global transport. In recent years, due to the rising costs of fossil fuels and increasing concerns about their negative impact on the natural environment, the development of low-emission power supply systems for vehicles has been observed. In order to create a stable and safe global transport system, an important issue seems to be the diversification of propulsion systems for vehicles, which can be achieved through the simultaneous development of conventional internal combustion vehicles, electric vehicles (both battery and fuel cell powered) as well as combustion hydrogen-powered vehicles. This publication presents an overview of commercial vehicles (available on the market) powered by internal combustion hydrogen engines. The work focuses on presenting the development of technology from the point of view of introducing ready-made hydrogen-powered vehicles to the market or technical solutions enabling the use of hydrogen mixtures in internal combustion engines. The study covers the history of the technology, dedicated hydrogen and bi-fuel vehicles, and vehicles with an engine powered by a mixture of conventional fuels and hydrogen. It presents basic technology parameters and solutions introduced by leading vehicle manufacturers in the vehicle market.

International North–South Transport Corridor: Boosting Russia’s “pivot to the South” and Trans-Eurasian connectivity

The Russian economy will have to adjust its logistics to face the new reality. The operationali­zation of the multimodal International North–South Transport Corridor (INSTC) is an important strategic part of it. This “pivot to the South” by Russia and other Eurasian Economic Union (EAEU) countries is of particular significance in light of the required reconfiguration of supply chains in Eurasia. Russian exporters, importers and freight forwarding companies’ needs in alternative logistical opportunities have increased dramatically. The INSTC development would promote Eurasian intra- and transcontinental connectivity, reduce export costs, develop new production niches, and realize the Caspian region’s transit potential. This study estimates that the aggregate potential INSTC freight traffic via all the routes and modes of transport, including containerized and non-containerized cargoes, will reach 15–25 million­ tonnes by 2030. The container traffic could rise 20x and this will require investments in hard infrastructure and also soft infrastructure improvement. The corridor will contribute to the evolving outline of the trans-Eurasian transport backbone and bring significant benefits for the economies of Russia, Central Asia, the Caucasus, Middle East, and South Asia.

A possible mitigation measures for urbanized residential care homes for elderly (RCHE) - acoustic window with natural ventilation

Hong Kong is well known as a densely populated city, which has an explicit usage of road traffic as its transport backbone. Severe road traffic noise problem is resulted from poorly planning in past decades, leads to the development of typical baffle type acoustic window with only one outer and one inner opening to attenuate adverse traffic noise impact. Nevertheless, extensive noise mitigation measures while allowing natural ventilation are essential when designing a RCHE. In view of the concern of the limited accessibility of the elderlies, the equal opportunity at both sides of the room to meet the needs of accessing to openable window was taken into account as far as possible. The proposed outer opening of the specially designed acoustic window is located in the middle, while the respective inner openings are located at the 2 sides. In this paper, mock-up test were carried out to analyze the acoustic performance of the specially designed acoustic window with two inner opening against the special characteristics of road traffic noise. Test results shown that the specially designed acoustic window is effective in mitigating substantial road traffic noise while providing reasonably amount of ventilation.

The last mile connectivity: Experience of passengers and drivers of E-rickshaws and cycle rickshaws in an Indian city

Promoting mobility by public transport, rather than individual automobiles, is a worldwide accepted and promoted sustainable solution. Traditionally, cycle-rickshaws have been the backbone of localised transportation in cities of India, thus a key component of 'Last Mile Connectivity' (LMC) in the urban transport sector. However, in the last few years, there has been an attempt to replace cycle rickshaws with battery-operated 'e-rickshaws' to make cities smarter. This paper examines the feasibility and consequences of such change in Ranchi, the capital city of Jharkhand state in India, its impact on traditional cycle rickshaw pullers; and how they fit in the overall urban transport sector. This paper presents Passengers' and Drivers' overall experience of E-Rickshaws and Cycle Rickshaws in promoting last-mile connectivity. Data collected through in-depth interviews with twenty e-rickshaw drivers, twenty rickshaw pullers, and twenty passengers in Ranchi highlights the user experiences of e-rickshaw and advantages, disadvantages, as well as the effectiveness of e-rickshaw on the streets. The study shows that E-rickshaws and cycle rickshaws may remain a viable Last Mile Connectivity in the urban transport sector.

Mitigating the Vulnerability of a High-Speed Railway–Air Network by Optimizing the Location of Integrated Transportation Hubs

High-speed trains and flights are the backbone of interregional transportation. A coupled high-speed railway–air transportation network (HRATN) allows these two modes of transportation to substitute for each other when the HRATN is threatened by extreme events. During train and flight operations, the area of influence and occurrence of extreme events are difficult to predict. Reasonably selected integrated transportation hubs can mitigate the vulnerability of HRATNs to extreme events. Optimizing the locations of integrated transportation hubs makes full use of the transport resources of both modes and facilitates the transfer of passengers, thereby decreasing the losses caused by extreme events. In this research, a tri-level model is established to reduce the potential worst loss by optimizing the location of the integrated transportation hub. The column-and-constraint generation algorithm based on duality is used to solve the model. For an illustrative example case, the enumeration method and sensitivity analysis show that building more integrated hubs can mitigate HRATN vulnerability but decreases unit investment income. This trivial conclusion verifies the validity of the model constructed in this paper. For a real-world case, comparing the corresponding models that do not consider extreme events reveals that the proposed strategy does not conflict with the decision-making in the normalized situation, thus verifying the usability of the present research.

Analisa Performa K-Means dan DBSCAN dalam Clustering Minat Penggunaan Transportasi Umum

Public transportation is one of the important modes of transportation and is the backbone of transportation in Indonesia. The development of public transportation is also supported by the government, this government support is evident in the national policy, namely the National Medium Term Development Plan (RPJMN). Although public transportation is an effective mode of transportation, it also has obstacles in its development, namely how to meet customer desires in choosing a mode of transportation. There are several variables that are the focus of this research, namely age, gender, income, cost, speed, comfort, safety, efficiency and flexibility. The search for influential variables will use the K-Means and DBSCAN clustering algorithms, these two algorithms are also compared to their performance to find a better algorithm. The results of the Silhouette Coefficient show that DBSCAN has a better performance with a value of 0.99 than K-Means with a value of 0.86. The variables that affect the interest in using public transportation are the most important ones related to cost, speed, comfort, safety, efficiency and flexibility.

Exploratory Data Analysis terhadap Kepadatan Penumpang Kereta Rel Listrik

The existence of the Kereta Rel Listrik Commuter Line as the backbone of transportation in the Jakarta - Bogor - Depok - Tangerang - Bekasi - Banten area has a very important role for commuter mobility around Daerah Khusus Ibukota Jakarta. With an average number of 1.1 million passengers per day, Kereta Rel Listrik is one of the factors supporting Indonesia's economy and growth in various sectors. On the other hand, the Covid-19 pandemic that hit the world caused restrictions on human movement which resulted in a decline in all economic sectors. The purpose of this research is to obtain optimal train schedule recommendations for the operation of the Kereta Rel Listrik Commuter Line in the Rangkasbitung - Tanah Abang service to carry passengers optimally while adhering to the physical distancing protocol set by the Minister of Transportation to prevent the wider spread of Covid-19. With such a large amount of data that must be processed, Exploratory Data Analysis is one of the choices we take to process the above data to get satisfactory results.

Analysis of Port Container Sea-Rail Intermodal Transportation System

With the continuous deepening of the China-Europe freight train, the interconnection of countries and regions along the “Belt and Road” has been accelerated, and railway transportation has become an important carrier and transportation backbone linking China-Europe road logistics, effectively promoting the new development of the geo-economics of China and Europe. The container sea-rail intermodal transportation system has developed rapidly. Based on the composition of the existing port container sea-rail intermodal transportation system, this paper use system analysis to describe its various subsystems, and analyzes the port container sea-rail intermodal transportation system composed of the external structure and the internal structure.

On-Board Data Management Layer: Connected Vehicle as Data Platform

For connected vehicles, as well as generally for the transportation sector, data are now seen as a precious resource. They can be used to make right decisions, improve road safety, reduce CO2 emissions, or optimize processes. However, analyzing these data is not so much a question of which technologies to use, but rather about where these data are analyzed. Thereby, the emerging vehicle architecture has to become a data-oriented architecture based on embedded computing platforms and take into account new applications, artificial intelligence elements, advanced analytics, and operating systems. Accordingly, in this paper, we introduce the concept of data management to the vehicle by proposing an on-board data management layer, so that the vehicle can play the role of data platform capable of storing, processing, and diffusing data. Our proposed layer supports analytics and data science to deliver additional value from the connected vehicle data and stimulate the development of new services. In addition, our data platform can also form or contribute to shaping the backbone of data-driven transport. An on-board platform was built where the dataset size was reduced 80% and a rate of 99% accuracy was achieved in a 5 min traffic flow prediction using artificial neural networks (ANNs).