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As technology continues to evolve, our society is becoming enriched with more intelligent devices that help us perform our daily activities more efficiently and effectively. One of the most significant technological advancements of our time is the Internet of Things (IoT), which interconnects various smart devices (such as smart mobiles, intelligent refrigerators, smartwatches, smart fire alarms, smart door locks, and many more) allowing them to communicate with each other and exchange data seamlessly. We now use IoT technology to carry out our daily activities, for example, transportation. In particular, the field of smart transportation has intrigued researchers due to its potential to revolutionize the way we move people and goods. IoT provides drivers in a smart city with many benefits, including traffic management, improved logistics, efficient parking systems, and enhanced safety measures. Smart transportation is the integration of all these benefits into applications for transportation systems. However, as a way of further improving the benefits provided by smart transportation, other technologies have been explored, such as machine learning, big data, and distributed ledgers. Some examples of their application are the optimization of routes, parking, street lighting, accident prevention, detection of abnormal traffic conditions, and maintenance of roads. In this paper, we aim to provide a detailed understanding of the developments in the applications mentioned earlier and examine current researches that base their applications on these sectors. We aim to conduct a self-contained review of the different technologies used in smart transportation today and their respective challenges. Our methodology encompassed identifying and screening articles on smart transportation technologies and its applications. To identify articles addressing our topic of review, we searched for articles in the four significant databases: IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Consequently, we examined the communication mechanisms, architectures, and frameworks that enable these smart transportation applications and systems. We also explored the communication protocols enabling smart transportation, including Wi-Fi, Bluetooth, and cellular networks, and how they contribute to seamless data exchange. We delved into the different architectures and frameworks used in smart transportation, including cloud computing, edge computing, and fog computing. Lastly, we outlined current challenges in the smart transportation field and suggested potential future research directions. We will examine data privacy and security issues, network scalability, and interoperability between different IoT devices.

Although the improvement of well-being is often an implicitly-assumed goal of many, if not most, public policies, the study of subjective well-being (SWB) and travel has so far been confined to a relatively small segment of the travel behavior community. Accordingly, one main purpose of this paper is to introduce a larger share of the community to some fundamental SWB-related concepts and their application in transportation research, with the goal of attracting others to this rewarding area of study. At the same time, however, I also hope to offer some useful reflections to those already working in this field. After discussing some basic issues of terminology and measurement of SWB, I present from the literature four conceptual models relating travel and subjective well-being. Following one of those models, I review five ways in which travel can influence well-being. I conclude by examining some challenges associated with assessing the impacts of travel on well-being, as well as challenges associated with applying what we learn to policy.

Sophisticated composite materials have a range of outstanding broad merits such as high particular strength, high specific stiffness, powerful designability, excellent tiredness resistance, excellent durability, are widely used in transportation, medical, electronics and other area. The assembly process of the composite surface components has large assembly stress, which affects the assembly accuracy. At the same time, the manual assembly cycle is elongated, the efficiency is low, and the quality stability is impoverished, which constraints the assembly mass and assembly power of the complex curved composite components. To improve the assembly power and carry out automatic assembly, this paper designs the automatic assembly technology scheme of the complex curved composite components, designs the automatic assembly scheme verification device, and conducts the automatic assembly test to verify the feasibility of the scheme.

Lithium-ion power batteries have been widely used in transportation due to their advantages of long life, high specific power, and energy. However, the safety problems caused by the inaccurate estimation and prediction of battery health state have attracted wide attention in academic circles. In this paper, the degradation mechanism and main definitions of state of health (SOH) were described by summarizing domestic and foreign literatures. The estimation and prediction methods of lithium-ion power battery SOH were discussed from three aspects: model-based methods, data-driven methods, and fusion technology methods. This review summarizes the advantages and disadvantages of the current mainstream SOH estimation and prediction methods. This paper believes that more innovative feature parameter extraction methods, multi-algorithm coupling, combined with cloud platform and other technologies will be the development trend of SOH estimation and prediction in the future, which provides a reference for health state estimation and prediction of lithium-ion power battery.

A lithium–oxygen battery, comprising a lithium carbonate-based protected anode, a molybdenum disulfide cathode and an ionic liquid/dimethyl sulfoxide electrolyte, operates in a simulated air atmosphere with a long cycle life of up to 700 cycles. Breathing long life into lithium batteries Lithium–air batteries could have extremely high energy densities and are therefore attractive successors to the lithium-ion batteries that are currently used in electric vehicles. However, the chemistry involved is complex, with multiple potential (and parasitic) side reactions. These are exacerbated by the relatively low proportion of the 'active' component (oxygen) in a real air mixture as opposed to a pure oxygen feed. This can lead to poor performance relative to the theoretical energy density, as well as degradation with time. Now, Larry Curtiss and colleagues combine appropriate cathodes and electrolytes and protect the lithium anode to create a lithium–air battery that can operate for hundreds of cycles in a realistic air-like atmosphere. This suggests that future development of these batteries may not be restricted to using purified air streams. Lithium–air batteries are considered to be a potential alternative to lithium-ion batteries for transportation applications, owing to their high theoretical specific energy 1 . So far, however, such systems have been largely restricted to pure oxygen environments (lithium–oxygen batteries) and have a limited cycle life owing to side reactions involving the cathode, anode and electrolyte 2 , 3 , 4 , 5 . In the presence of nitrogen, carbon dioxide and water vapour, these side reactions can become even more complex 6 , 7 , 8 , 9 , 10 , 11 . Moreover, because of the need to store oxygen, the volumetric energy densities of lithium–oxygen systems may be too small for practical applications 12 . Here we report a system comprising a lithium carbonate-based protected anode, a molybdenum disulfide cathode 2 and an ionic liquid/dimethyl sulfoxide electrolyte that operates as a lithium–air battery in a simulated air atmosphere with a long cycle life of up to 700 cycles. We perform computational studies to provide insight into the operation of the system in this environment. This demonstration of a lithium–oxygen battery with a long cycle life in an air-like atmosphere is an important step towards the development of this field beyond lithium-ion technology, with a possibility to obtain much higher specific energy densities than for conventional lithium-ion batteries.

The global expansion of industry and technology has brought various environmental issues especially in atmospheric pollution and global warming. These resulted in various R&D activities on renewable energy resources and devices. Developing high temperature polymer electrolyte membrane fuel cell (HT-PEMFC) is one of them. Over the past decades, this research has been received the most attention for various stationary and transportation applications. This is due to inherent advantages of operation above 100 °C including improved tolerance toward CO poisoning, enhanced electrode kinetics, easier heat dissipation and water management as well as better thermodynamic quality of the produced heat. Poly (benzimidazoles)-phosphoric acid (PBI/PA) is the well-established membrane for HT-PEMFC applications replacing perfluorinated sulfonic acid (PFSA) membranes, which operate in the temperature range of below 100 °C. Nevertheless, there have been concerns on the durability and stability of such PEMFC, which negatively affected their widespread commercialization. In this paper, problems regarding this acid-base complex membrane system and modifications as well as some techniques used to overcome these issues will be outlined.

The recent release of hydrogen economy roadmaps for several major countries emphasizes the need for accelerated worldwide investment in research and development activities for hydrogen production, storage, infrastructure and utilization in transportation, industry and the electrical grid. Due to the high gravimetric energy density of hydrogen, the focus of technologies that utilize this fuel has recently shifted from light-duty automotive to heavy-duty vehicle applications. Decades of development of cost-effective and durable polymer electrolyte membrane fuel cells must now be leveraged to meet the increased efficiency and durability requirements of the heavy-duty vehicle market. This Review summarizes the latest market outlooks and targets for truck, bus, locomotive and marine applications. Required changes to the fuel-cell system and operating conditions for meeting Class 8 long-haul truck targets are presented. The necessary improvements in fuel-cell materials and integration are also discussed against the benchmark of current passenger fuel-cell electric vehicles. Fuel cells are increasingly being considered for powertrains of heavy-duty transportation. Cullen et al. survey the technical challenges of fuel cells at both the system and materials level for transportation application and outline the roadmap for future development.

Intelligent transportation (e.g., intelligent traffic light) makes our travel more convenient and efficient. With the development of mobile Internet and position technologies, it is reasonable to collect spatio-temporal data and then leverage these data to achieve the goal of intelligent transportation, and here, traffic prediction plays an important role. In this paper, we provide a comprehensive survey on traffic prediction, which is from the spatio-temporal data layer to the intelligent transportation application layer. At first, we split the whole research scope into four parts from bottom to up, where the four parts are, respectively, spatio-temporal data, preprocessing, traffic prediction and traffic application. Later, we review existing work on the four parts. First, we summarize traffic data into five types according to their difference on spatial and temporal dimensions. Second, we focus on four significant data preprocessing techniques: map-matching, data cleaning, data storage and data compression. Third, we focus on three kinds of traffic prediction problems (i.e., classification, generation and estimation/forecasting). In particular, we summarize the challenges and discuss how existing methods address these challenges. Fourth, we list five typical traffic applications. Lastly, we provide emerging research challenges and opportunities. We believe that the survey can help the partitioners to understand existing traffic prediction problems and methods, which can further encourage them to solve their intelligent transportation applications.

This paper presents a comparative study of the implementation of all-to-all pairs shortest path algorithms, specifically Floyd-Warshall, Johnson’s, and Dijkstra’s. It contributes to a better understanding of their strengths and weaknesses in different types of applications (real-world scenarios). The research demonstrates the use of these algorithms in finding the shortest path between multiple locations using a Google Maps plotter and the Google Maps API. Older research papers have shown a comparison that shows that the Floyd-Warshall algorithm is faster than the other two algorithms in certain scenarios; however, none have brought up the real-world application of such an algorithm. The null hypothesis of this study is that the Floyd-Warshall algorithm is not suitable for use in a real-life application for finding the shortest path compared to Johnson’s algorithm. The results of this study have potential applications in transportation and logistics and will provide useful insights for future work in this field.

Garut city is one of the cities that is densely packed with transportation, especially on public transportation. The problem is that there are still many people who do not understand the path that the public transportation passes, both in the city itself, outside the city and even foreign tourists. The purpose of developing this application is to find out where to go. In this study, researchers designed and built public transport transportation applications in the web-based city of Garut with the name Garut Anyar utilizing GIS technology in it. The application is useful for searching city transportation routes (Angkot) in Garut City so that users no longer feel difficulties in finding public transport to get to their destination, especially for migrants in Garut City. In addition, this application can display information about angkot routes so that it can add to the user's insight. The conclusion obtained from this study is the Garut Anyar application was successfully built and useful for every user who has used this Garut Anyar application, which has been tested 100 times a trial from the RSU route to Banyuresmi as evidenced by an application testing questionnaire that gets good grades.