Transportation Platform Research Articles

Competitive planning of partnership supply networks focusing on sustainable multi-agent transportation and virtual alliance: A matheuristic approach

The partnership supply of market needs is one of the most regarded orientations in recent years. In this paper, a competitive model is designed in partnership supply networks including parent firms (brands), manufacturing plants, governmental logistics company and franchised stores. In the raised scheme, the involved supply networks seek to develop their upstream and downstream partnerships (respectively with manufacturing plants and franchised stores) in a competitive environment. Besides this cross-network competition, the downstream partners of each network develop some virtual alliances. In such alliances, each of the involved members, further pursuing its own interests, aims to increase the overall share of the parent brand. Even more striking, a multi-agent transportation platform is implemented in the distribution of products to meet the environmental sustainability requirements. The state-owned logistics company, as the market leader of the cited distributed structure, dictates its strategy to the supply networks seeking to gain the most possible partnership interactions. Hence, in this paper, a multi-level competition-oriented problem is considered in the partnership supply networks and formulated upon multiple hierarchical stages. Due to the NP-hardness of the problem and given its structural features, a matheuristic approach based on a combination of the Benders Decomposition method and Particle Swarm Optimization algorithm is developed. The proposed solving approach is compared against a gaming-based heuristic and also a pure Benders Decomposition. The results of the evaluations indicate the superiority of the suggested hybrid approach, especially in large-scale instances.

Vulnerability and Resilience of Urban Traffic to Precipitation in China

The concept of Healthy Cities, introduced by the World Health Organization, demonstrates the value of health for the whole urban system. As one of the most important components of urban systems, transportation plays an important role in Healthy Cities. Many transportation evaluation systems focus on factors such as road networks, parking spaces, transportation speed, accessibility, convenience, and commuting time, while the vulnerability and resilience of urban transportation are rarely evaluated. This study presents the preliminary progress in the evaluation of traffic vulnerability and resilience during precipitation events in 39 Chinese cities. Traffic congestion index data, derived from the Baidu Map Smart Transportation Platform, and rainfall data, derived from NASA’s global precipitation measurement, are utilized. Traffic vulnerability index, traffic resilience index, and the corresponding quantitative methods are proposed, and the analysis results are presented. This study is of value in improving the understanding of urban traffic vulnerability and resilience, and in enabling the quantitative evaluation of them in urban health assessment and the Healthy Cities program.

Selecting Remote Driving Locations for Latency Sensitive Reliable Tele-Operation

These days, autonomous vehicles (AVs) technology has been improved dramatically. However, even though the AVs require no human intervention in most situations, AVs may fail in certain situations. In such cases, it is desirable that humans can operate the vehicle manually to recover from a failure situation through remote driving. Furthermore, we believe that remote driving can enhance the current transportation system in various ways. In this paper, we consider a revolutionary transportation platform, where all the vehicles in an area are controlled by some remote controllers or drivers so that transportation can be performed in a more efficient way. For example, road capacity can be effectively utilized and fuel efficiency can be increased by centralized remote control. However, one of the biggest challenges in such remote driving is the communication latency between the remote driver and the vehicle. Thus, selecting appropriate locations of the remote drivers is very important to avoid any type of safety problem that might happen due to large communication latency. Furthermore, the selection should reflect the traffic situation created by multiple vehicles in an area. To tackle these challenges, in this paper, we propose several algorithms that select remote drivers’ locations for a given transportation schedules of multiple vehicles. We consider two objectives in this system and evaluate the performance of the proposed algorithms through simulations. The results show that the proposed algorithms perform better than some baseline algorithms.

Real-time visibility transportation platform deployment. Evidence from business practice and insights for theory

Real-time visibility transportation platform deployment. Evidence from business practice and insights for theory

Reimagining Transportation: Bio-Mobility <sup>TM</sup>

<div class="section abstract"><div class="htmlview paragraph">India has a huge opportunity to fulfil its commitment towards global GHG emissions reduction by 30-35%. This can be achieved by maximizing the share of renewable energy in India’s overall energy mix, currently is dominated by fossil fuels. After industry and transportation sector comprising of air, water and surface modes is the second largest contributor of GHG emissions. Ever since the evolution of mobility, the transportation landscape continues to be occupied mostly by internal combustion engines (ICE) that employs fossil fuels. These fossil fuels are majorly import dependent and cause of huge foreign exchange outflow. Therefore, the need of the hour is to leverage captive alternative energy sources that can help mitigate risk of climate change besides positively impacting economy and society. Biofuel - a renewable transportation fuel, both in gaseous & liquid form, is a very promising, alternate clean energy source. Biofuels are environment friendly and help improve the rural economy. Besides facilitating energy self-reliance, biofuels utilize existing infrastructure and ecosystem of ICE automotive industry. Praj Bio-Mobility<sup>TM</sup> platform envisions the use of bio-based renewable feedstock for the production of low-carbon transportation fuels for all modes of transportation. This unique platform also works in tandem with e-mobility solutions. Bio-Mobility<sup>TM</sup> platform comprises of established solutions such as 1st generation bio-ethanol, Biodiesel and fast emerging advanced biofuel solution such as 2<sup>nd</sup> generation bio-ethanol, sustainable aviation fuel (SAF), compressed bio-gas (CBG), Bio-hydrogen, marine bio-fuels, etc. This paper deals with the adoption of Bio-Mobility<sup>TM</sup> platform for transportation as they can create winners in the social, economic and environmental areas. This includes entrepreneurship and employment opportunities for farming community, boosting rural economy, minimizing air pollution resulting in curbing GHG emissions. It also aligns with the Government of India’s vision of doubling the farmer’s income and contributing towards India’s Aatmanirbhar Bharat Abhiyaan.</div></div>

Safe Transportation of Nuclear Fuel Assemblies by Means of Wheeled Robotic Platforms

Certain engineering problems concerning safety of the technological operations of the horizontal transportation of nuclear fuel within the enterprises’ sites were considered. Taking into account current trends in the introduction of robotic systems to reduce the impact of hazardous nuclear materials on personnel, the issue of automated control of the movement of the wheeled robotic platform, which can be used for horizontal transportation of nuclear fuel was studied. The major attention was paid to minimizing the transportation loads on nuclear fuel by means of decreasing the accelerations under its horizontal movement on the robotic wheeled transportation platform, which is a separate issue of the comprehensive safety problem of nuclear materials management.
 The research of horizontal movement safety of nuclear fuel by means of the robotic wheeled platforms was limited to defining transportation accelerations and was performed by computer simulations using mathematical models of dynamics and electro-mechanics. The mathematical model of the robotic transport wheeled platform loaded with nuclear fuel with the on-board accelerometer ensuring the required measurements necessary for an automated safe movement control system was built in the form of the Lagrange equations of the second kind and the electro-mechanics equations of the direct current electric motors. The issue of ensuring smooth running during the displacement of a wheeled platform loaded with nuclear fuel was investigated, since especially in this mode the maximum accelerations are observed, which can lead to nuclear fuel damage. Computer simulation was performed using free Scilab software with open program code. It was demonstrated that due to the proper choice of the time algorithm of the voltage of electric motors, it is possible to ensure a small acceleration during the displacement of a robotic wheeled transport platform loaded with nuclear fuel. The obtained result substantiated the possibility of safe horizontal transportation of nuclear fuel on robotic wheeled platforms within the territories of enterprises, which will significantly reduce the harmful impact of hazardous nuclear materials on industrial personnel.

Soft Robot Based on Hyperelastic Buckling Controlled by Discontinuous Magnetic Field

Abstract Most untethered magnetic soft robots are controlled by a continuously applied magnetic field. The accuracy of their motion depends completely on the accuracy of external magnetic field, consequently any slight disturbance may cause a dramatic change. Here, we report a new structure and driven method design to achieve a novel magnetic soft robot, denoted as “BUCK”, which can achieve accurate and stable locomotion with weakly dependence on the magnetic field. The robot BUCK consists of functional magnetic composite materials with one central transportation platform and four crawling arms, whose motion is mainly based on hyperelastic buckling and recovering of the arms. BUCK is capable of cargo transportation with multimodal locomotion, such as crawling, climbing, and turning with high adaptability to various surfaces. Due to the applied discontinuous magnetic field, BUCK consumes much less driven energy compared with conventional magnetic robots. Moreover, we develop theoretical and numerical models to rationally design the precisely controlled BUCK. Our study shows applications in terms of transportation functions, such as for optical path adjustments and photographic tasks in complex circumstances. This work also provides new ideas on how to utilize nonlinear deformation more efficiently; one could combine the benefits for both the flexible electronics and actuation applications.

Risk Management in the Construction of Intelligent Transportation Platform Based on Artificial Intelligence

The smoothness of a city's traffic is one of the signs that measure the development of a city. With the advent of the era of artificial intelligence and big data, the previously bloated and blocked motor vehicle transportation system is increasingly unable to adapt to this fast-paced society. The use of artificial intelligence technology to build a brand-new intelligent transportation platform is imminent, and reasonable planning of the risks in the construction of the transportation platform can effectively increase the transmission rate and reduce the frequency of accidents. The purpose of this paper is to study the risk management in the construction of intelligent transportation platform based on artificial intelligence. This article first summarizes the basic theory of artificial intelligence, and then extends the core technology of artificial intelligence. And combined with the current situation of my country's contemporary intelligent transportation, analysis of the existing problems and shortcomings, on this basis, combined with artificial intelligence technology to research and analyze the risk management in the construction of intelligent transportation platform. This research systematically expounds the risk construction principles, model construction and risk response measures of the intelligent transportation platform. This paper uses field surveys, interviews and other research methods to research and investigate traffic risk management in a certain place. The experimental research shows that risk management in the construction of intelligent transportation platforms based on artificial intelligence has higher feasibility than traditional traffic management.

Treatment of the complex liquid phase that contains produced water, condensate oil, and floccule from an offshore gas field: A pilot system for the South China Sea

Produced water (PW) of the liquid phase is the largest volume by-product from the process of offshore oil and gas production, and compact and efficient treatment methods are brought into focus. The PW, condensate oil, and floccule in the liquid phase all require treatment to satisfy the requirements of the standards. The liquid phase volume from offshore gas fields is typically not as large as that from offshore oil fields. The presence of the floccule and severity of emulsification, however, cause higher levels of treatment difficulty. Ecological damage to the ocean and some other potential hazards can be caused if PW discharged into the ocean contains oil that exceeds the concentrations of the value, of which ranges from 15 mg/L to 50 mg/L according to different standards. Condensate oil phase pipes may also be corroded if the oil phase is not well treated. This study examines a pilot system with the capacity of 0.5 m3/h, that includes pre-, PW, and condensate oil treatments performed at an industrial offshore gas field platform on the South China Sea. The water and oil phases were transparent in appearance. The concentration of oil in the PW discharged to the ocean was less than 50% of the value of the relative standards. The concentration of water in the condensate oil was lower than 200 mg/L, which satisfied the requirement of this platform for transportation by submarine pipelines. The accumulative floccule in the liquid phase was also gathered using a filter bag that proceeded a virtuous circle due to the avoidance of the accumulation of the floccule. This pilot system provides a novel solution method for the liquid phase from offshore gas fields containing highly emulsified PW, condensate oil, and floccule, which diffuses between the PW and the condensate oil.

Failure Analysis of Tee in Shale Gas Transportation Platform

The mains reasons for internal corrosion failure and cracking of the tee in shale gas transportation platform have been proposed based on macroscopic analysis, physical and chemical property test, metallographic examination, Scanning Electron Microscope analysis, X-ray spectroscopy analysis and service condition analysis. The results show that corrosion occurring in the inner wall of tee was caused by the combined impacts of CO2 corrosion, sulfate-reducing bacteria (SRB) corrosion and erosion corrosion. The crack in the weld of the inner wall was mainly due to the Sulfate-reducing Bacteria Induced cracking.

Fabrication of S-scheme CdS-g-C3N4-graphene aerogel heterojunction for enhanced visible light driven photocatalysis

Constructing S-scheme heterojunction photocatalysts reveals a greatly improved separation efficiency of photogenerated carriers and enhanced harvesting ability of solar energy in photocatalytic field. Herein, a ternary CdS-g-C3N4-GA heterojunction has been fabricated by a facile ultrasound strategy, which behaved as a S-scheme heterojunction with an intimate interface formed, and GA played as an electronic transportation platform to promote the separation of photo-induced charge carriers, which was certified through photoelectrochemical techniques. Density functional theory calculations revealed that the different component in ternary CdS-g-C3N4-GA heterojunction demonstrated an obvious difference of work function, resulting in the charge transfer from CdS to g-C3N4 through GA with S-scheme principle. In the optimized conditions, the S-scheme CdS-g-C3N4-GA heterojunction not only displayed greatly enhanced photocatalytic performances for degradation of dye and antibiotic wastewater, but also improved photocatalytic H2 production activity. In addition, the photocatalytic mechanism and driving force of charge transfer and separation in S-scheme CdS-g-C3N4-GA heterojunction were studied. This study offers a feasible strategy to construct a ternary S-scheme heterojunction for environmental and energy photocatalysis.

Model predictive control for slurry pipeline transportation of a cutter suction dredger

Cutter Suction Dredgers (CSDs) are a special type of ships designed for construction and maintenance projects of ocean and offshore engineering. During the dredging operation, CSDs can excavate nearly all kinds of soil on the sea bed, and then the dredged materials with coarse particles need to be sucked up by a slurry pump and transported to a disposal area through a long-distance pipeline. In order to avoid sedimentation of slurry in pipeline transportation, the flow rate must be maintained within a reasonable range. Otherwise, the pipeline can be blocked when the slurry density is too high. In this paper, we present a Model Predictive Control (MPC) approach to manipulate the flow rate of slurry in pipeline transportation for a CSD. To demonstrate the advantages of our proposed approach, we also implement three Proportional–Integral–Derivative (PID) controllers (i.e., conventional PID, Fuzzy-PID, and LQR-PID) to make a direct comparison. Moreover, in order to evaluate the effectiveness of our proposed approach in real scenarios, we have, in particular, built a slurry pipeline transportation platform. Both the simulation and experimental results show that our proposed MPC approach is more effective than other PID controllers in controlling the flow rate in the slurry pipeline transportation problem. The proposed approach can provide a guideline for the automated control of the slurry pump for a CSD.

Dynamic evolution of ride-hailing platforms from a systemic perspective: Forecasting financial sustainability

Transportation platforms are often thought to be poised for a bright future, yet issues about the profitability of this industry surface frequently. This study uses the system dynamics modeling framework to forecast ride-hailing platforms' growth on a series of key performance indicators, including profit and the influence of various micro and macro, internal and external factors on growth. More specifically, taking ride-hailing platforms as a focal case, this study explores the internal structure and growth mechanism of a simulated transportation platform from a systematic perspective. The results provide a better understanding of the sustainable growth paths and mechanisms about ride-hailing platforms while further constituting an analytical tool for the operation and management of the emerging platform business model. By so doing, the paper presents useful conclusions for researchers, managers, and policy-makers alike, since it further advances theoretical and practical understanding of the digital transportation economy.

A Post-COVID-19 Economic Recovery Model: The national domestic economic auto-sustainability Model (NDEAS-Model)

The significant damage of COVID-19 on the world economy forces us to reconsider a deep restructuration domestically and internationally in the next few years. This paper suggests a Post-COVID-19 reconstruction model is called “The National Domestic Economic Auto-Sustainability Model (NDEAS-Model).” The NDEAS-Model proposes four economic platforms: (i) the domestic education and technical training standardization platform (P1); (ii) the domestic productive infrastructure and transportation platform (P2); (iii) the selective strategic trade, investment, and tourism protection platform (P3); (iv) the environmental and natural resources management platform (P4). The main objective of NDEAS-Model is to avoid imported massive pandemic diseases, non-sustainable and weak food security platforms, and job diversion, respectively.

Photo-switchable smart superhydrophobic surface with controllable superwettability

An azobenzene-based smart superhydrophobic surface undergoes reversible transformations among multiple bioinspired superwetting states through photo-manipulation, demonstrating promising potential on a rewritable platform for droplet transportation.

Multi-UAV scalable platform for heavy load transportation

Multi-UAV scalable platform for heavy load transportation

Internet of things assisted public security management platform for urban transportation using hybridised cryptographic‐integrated steganography

In cloud computing, data sharing and security are considered as the significant challenging issues in the present era. Until recently, considering secure data sharing in the cloud, several problems have been taken into consideration, such as data security, privacy, data integrity, confidentiality and resource scheduling. In this study, the hybridised cryptographic-integrated steganography (HCIS) algorithm has been used with auxiliary data inputs for secured data sharing in an internet of things assisted cloud environment for the urban transportation system. Further, the cryptography or cryptology generates code that provides a high level of privacy to the group or individual who can access cloud data. Furthermore, cryptography converts data into a secure format that is readable by an authorised user and steganography helps to transmit secret data to avoid the detection of information. The confidential data is extracted at its destination, and the encryption key has been utilised for hiding or effectively protecting data. The experimental results show that efficient and secure data sharing with multi-owners in cloud computing has been achieved using the HCIS method.

Regulating Flexibility: Uber’s Platform as a Technological Work Arrangement


 
 
 When initiating its Norwegian operations, the transportation platform Uber adjusted its business model to the Norwegian regulation of the taxi market by focusing on its high-end offering, Uber Black, organized through limousine companies who employ the drivers and own the cars. The Uber Black drivers in Oslo are classified as employees and endowed with a substantially flexible work arrangement. Based on a ‘traveling ethnography’ among Uber Black drivers in Oslo, this article conceptualizes Uber’s digital platform as a technological work arrangement. The analysis shows that while the platform is experienced as an opaque form of management that limits the drivers’ formal flexibility, the effects of the technological work arrangement is contingent on the drivers’ formal work arrangement and the characteristics of the Uber Black market in Oslo.
 
 

Controlled Multidirectional Particle Transportation by Magnetic Artificial Cilia.

Manipulation of particles in a controllable manner is highly desirable in many applications. Inspired by biological cilia, this article experimentally and numerically demonstrates a versatile particle transportation platform consisting of arrays of magnetic artificial cilia (MAC) actuated by a rotating magnet. By performing a tilted conical motion, the MAC are capable of transporting particles on their tips, along designated directions that can be fully controlled by the externally applied magnetic field, in both liquid and air, at high resolution (particle precision), with varying speeds and for a range of particle sizes. Moreover, the underlying mechanism of the controlled particle transportation is studied in depth by combining experiments with numerical simulations. The results show that the adhesion and friction between the particle and the cilia are essential ingredients of the mechanism underlying the multidirectional transportation. This work offers an advanced solution to controllably transport particles along designated paths in any direction over a surface, which has potential applications in diverse fields including lab-on-a-chip devices, in vitro biomedical sciences, and self-cleaning and antifouling.

Perfluoroalkyl-Functionalized Covalent Organic Frameworks with Superhydrophobicity for Anhydrous Proton Conduction.

The development of anhydrous proton-conducting materials is critical for the fabrication of high-temperature (>100 °C) polymer electrolyte membrane fuel cells (HT-PEMFCs) and remains a significant challenge. Covalent organic frameworks (COFs) are an emerging class of porous crystalline materials with tailor-made nanochannels and hold great potential for ion and molecule transport, but their poor chemical stability poses great challenges in this respect. In this contribution, we present a bottom-up self-assembly strategy to construct perfluoroalkyl-functionalized hydrazone-linked 2D COFs and systematically investigate the effect of different lengths of fluorine chains on their acid stability and proton conductivity. Compared with their nonfluorous parent COFs, fluorinated COFs possess structural ultrastability toward strong acids as a result of enhanced hydrophobicity (water contact angle of 144°). Furthermore, the superhydrophobic 1D nanochannels can serve as robust hosts to accommodate large amounts of phosphonic acid for fast and long-term proton conduction under anhydrous conditions and a wide temperature range. The anhydrous proton conductivity of fluorinated COFs is 4.2 × 10-2 S cm-1 at 140 °C after H3PO4 doping, which is 4 orders of magnitude higher than their nonfluorous counterparts and among the highest values of doped porous organic frameworks so far. Solid-state NMR studies revealed that H3PO4 forms hydrogen-boding networks with the frameworks and perfluoroalkyl chains of COFs, and most of the H3PO4 molecules are highly dynamic and mobile while the frameworks are rigid, which affords rapid proton transport. This work paves the way for the realization of the target properties of COFs through predesign and functionalization of the pore surface and highlights the great potential of COF nanochannels as a rigid platform for fast ion transportation.