Multi-mode Transport Research Articles

Exploring the association between multi-mode transport and the built environment: A comparative study of metro, bus, taxi, and shared bike use

Urban transportation plays a pivotal role in sustainable city planning, with multiple transportation modes coexisting to achieve sustainable goals. Despite the extensive use of various mobility datasets to analyze mobility behaviors, comparative studies focusing on multiple transportation modes for origin-destination (OD) trips remain scarce. This study, conducted in Shenzhen, presents three in-depth comparative analyses: (1) variations in the utilization of metros, buses, taxis, and shared bikes; (2) the clustering patterns of OD flows across different modes; and (3) the influence of the built environment at origins and destinations on OD flows. The findings reveal that the use of public transportation and taxis mirrors the city's polycentric layout, with each transportation mode fulfilling distinct roles in linking disparate urban areas. The nonlinear effect of the built environment on OD flows exhibits mode-specific variations, particularly in relation to thresholds. Additionally, network topology characteristics are identified as significant factors in explaining OD flows for all modes. Despite observed differences in weekday and weekend OD flow clustering, the built environment consistently correlates with daily OD flows. These findings provide valuable insights to inform mode-specific strategies that enhance sustainable urban development.

Spatial accessibility and equity of community healthcare: unraveling the impact of varying time and transport mode.

Achieving a higher level of accessibility and equity to community healthcare services has become a major concern for health service delivery from the perspectives of health planners and policy makers in China. In this study, we introduced a comprehensive door-to-door (D2D) model, integrating it with the open OD API results for precise computation of accessibility to community hospitals over different transport modes. For the D2D public transit mode, we computed the temporal variation and standard deviation of accessibility at different times of the day. Additionally, accessibility values for D2D riding mode, D2D driving mode, and simple driving mode were also computed for comparison. Moreover, we introduced Lorenz curve and Gini index to assess the differences in equity of community healthcare across different times and transport modes. The D2D public transit mode exhibits noticeable fluctuations in accessibility and equity based on the time of day. Accessibility and equity were notably influenced by traffic flow between 8 AM and 11 AM, while during the period from 12 PM to 10 PM, the open hours of community hospitals became a more significant determinant in Nanjing. The moments with the most equitable and inequitable overall spatial layouts were 10 AM and 10 PM, respectively. Among the four transport modes, the traditional simple driving mode exhibited the smallest equity index, with a Gini value of only 0.243. In contrast, the D2D riding mode, while widely preferred for accessing community healthcare services, had the highest Gini value, reaching 0.472. The proposed method combined the D2D model with the open OD API results is effective for accessibility computation of real transport modes. Spatial accessibility and equity of community healthcare experience significant fluctuations influenced by time variations. The transportation mode is also a significant factor affecting accessibility and equity level. These results are helpful to both planners and scholars that aim to build comprehensive spatial accessibility and equity models and optimize the location of public service facilities from the perspective of different temporal scales and a multi-mode transport system.

Research Progress of the Impacts of Comprehensive Transportation Network on Territorial Spatial Development and Protection

Coordination between the construction of transport infrastructure and the development and protection of territorial space is an important factor in promoting sustainable regional development, but there is still a lack of systematic research on the impact of transport on territorial space worldwide. Following the logic of “development trend revealing—theoretical and technological summary—mechanism analysis”, the research progress on the two aspects of development and protection of territorial space related to transport is systematically and comprehensively sorted from the perspective of multi-scale and multi-mode transport. The results show that: (1) The number of research papers on the effect of transport on territorial space is on the rise, and there is an obvious trend of cross-disciplinary research. (2) Transport infrastructure will promote the development of territorial space in terms of land use change, spatial-temporal compression, and economic development, and will affect the protection of territorial space in terms of ecological impacts, energy consumption and carbon emissions, and the crossing of protection zones. (3) In the existing research, the lack of multi-dimensional indicator system construction and analysis, insufficient research at the mechanism level, and insufficient combination of theoretical research and practical application are the main problems at present, and an important direction is urgently needed for future research.

Multiobjective route finding in a multimode transportation network by NSGA-II

Route finding is an everyday challenge for urban residents. While many route planner applications exist, they cannot find suitable routes based on user preferences. According to user preferences, routing in a multimode urban transportation network can be considered a multiobjective optimization problem. Different objectives and modes for transportation, along with many routes as decision elements, give rise to the complexity of the problem. This study uses an elitism multiobjective evolutionary algorithm and the Pareto front concept to solve the problem. The data of a simulated multimode network consisting of 150 vertexes and 2600 edges are used to test and evaluate the proposed method. Four transport modes are considered: the metro, bus, taxi, and walking. Also, three minimization objective functions are considered: expense, discomfort, and time. The results show the competence of the algorithm in solving such a complex problem in a short run time. The optimal setting for the algorithm parameters is found by considering the algorithm run time, diversity of solutions, and convergence trend by running sensitivity analyses. A repeatability test is applied using the optimal setting of the algorithm, which shows a high level of repeatability. While NSGA-II (Non-dominated Sorting Genetic Algorithm II) may be a well-established algorithm in the literature, its application in multiobjective route finding in multimode transport networks is unique and novel. The outcomes of the proposed method are compared with existing methods in the literature, proving the better performance of the NSGA-II algorithm.

Fast Neural-Network Surrogate Model of the Updated Multi-Mode Anomalous Transport Module for NSTX-U

Fast Neural-Network Surrogate Model of the Updated Multi-Mode Anomalous Transport Module for NSTX-U

Methodological aspects of risk mapping in multimode transport systems

Efficient transport solutions are based on multimodal systems, with the dominant role of rail and road transport in land versions of the systems and the connecting and directing part of intermodal terminals, transhipment terminals or warehouse centres. The implementation of transport processes is always associated with the risk of lack of timeliness (quality) or threats to people, equipment and cargo (safety) resulting from human, technical, organizational and global factors like pandemics or war. The article contains a risk mapping method in multimodal transport systems configured to estimate the risk of lowering the quality of logistics services (on-time deliveries, etc.). The method combines factors usually considered separately in studies on individual modes of transport. A formal notation of risk factors as a mathematical model was proposed, and a case study was provided to picture the implementation.

Unprotected edge modes in quantum spin Hall insulator candidate materials

The experiments in quantum spin Hall insulator candidate materials, such as HgTe/CdTe and InAs/GaSb heterostructures, indicate that in addition to the topologically protected helical edge modes, these multilayer heterostructures may also support additional edge states, which can contribute to scattering and transport. We use first-principles calculations to derive an effective tight-binding model for HgTe/CdTe, HgS/CdTe, and InAs/GaSb heterostructures, and we show that all these materials support additional edge states which are sensitive to edge termination. We trace the microscopic origin of these states back to a minimal model supporting flat bands with a nontrivial quantum geometry that gives rise to polarization charges at the edges. We show that the polarization charges transform into additional edge states when the flat bands are coupled to each other and to the other states to form the Hamiltonian describing the full heterostructure. Interestingly, in HgTe/CdTe quantum wells the additional edge states are far away from the Fermi level so that they do not contribute to the transport, but in the HgS/CdTe and InAs/GaSb heterostructures they appear within the bulk energy gap, giving rise to the possibility of multimode edge transport. Finally, we demonstrate that because these additional edge modes are nontopological it is possible to remove them from the bulk energy gap by modifying the edge potential, for example, with the help of a side gate or chemical doping.

Multimodal Fuzzy Downstream Petroleum Supply Chain: A Novel Pentagonal Fuzzy Optimization

The petroleum industry has a complex, inflexible and challenging supply chain (SC) that impacts both the national economy as well as people’s daily lives with a range of services, including transportation, heating, electricity, lubricants, as well as chemicals and petrochemicals. In the petroleum industry, supply chain management presents several challenges, especially in the logistics sector, that are not found in other industries. In addition, logistical challenges contribute significantly to the cost of oil. Uncertainty regarding customer demand and supply significantly affects SC networks. Hence, SC flexibility can be maintained by addressing uncertainty. On the other hand, in the real world, decision-making challenges are often ambiguous or vague. In some cases, measurements are incorrect owing to measurement errors, instrument faults, etc., which lead to a pentagonal fuzzy number (PFN) which is the extension of a fuzzy number. Therefore, it is necessary to develop quantitative models to optimize logistics operations and supply chain networks. This study proposed a linear programming model under an uncertain environment. The model minimizes the cost along the refineries, depots, multimode transport and demand nodes. Further developed pentagonal fuzzy optimization, an alternative approach is developed to solve the downstream supply chain using the mixed-integer linear programming (MILP) model to obtain a feasible solution to the fuzzy transportation cost problem. In this model, the coefficient of the transportation costs and parameters is assumed to be a pentagonal fuzzy number. Furthermore, defuzzification is performed using an accuracy function. To validate the model and technique and feasibility solution, an illustrative example of the oil and gas SC is considered, providing improved results compared with existing techniques and demonstrating its ability to benefit petroleum companies is the objective of this study.

Motor-driven advection competes with crowding to drive spatiotemporally heterogeneous transport in cytoskeleton composites.

The cytoskeleton-a composite network of biopolymers, molecular motors, and associated binding proteins-is a paradigmatic example of active matter. Particle transport through the cytoskeleton can range from anomalous and heterogeneous subdiffusion to superdiffusion and advection. Yet, recapitulating and understanding these properties-ubiquitous to the cytoskeleton and other out-of-equilibrium soft matter systems-remains challenging. Here, we combine light sheet microscopy with differential dynamic microscopy and single-particle tracking to elucidate anomalous and advective transport in actomyosin-microtubule composites. We show that particles exhibit multi-mode transport that transitions from pronounced subdiffusion to superdiffusion at tunable crossover timescales. Surprisingly, while higher actomyosin content increases the range of timescales over which transport is superdiffusive, it also markedly increases the degree of subdiffusion at short timescales and generally slows transport. Corresponding displacement distributions display unique combinations of non-Gaussianity, asymmetry, and non-zero modes, indicative of directed advection coupled with caged diffusion and hopping. At larger spatiotemporal scales, particles in active composites exhibit superdiffusive dynamics with scaling exponents that are robust to changing actomyosin fractions, in contrast to normal, yet faster, diffusion in networks without actomyosin. Our specific results shed important new light on the interplay between non-equilibrium processes, crowding and heterogeneity in active cytoskeletal systems. More generally, our approach is broadly applicable to active matter systems to elucidate transport and dynamics across scales.

Modelling Approach to Develop a Multimodal Transportation Network

Multimodal transportation (MMT) refers to a system that utilizes various means of transportation to transfer people & goods from one place to another. Transit operations are measured as the maximum number of passengers that can be carried past a fixed route, in a given period. Investing in and using multiple modes of transportation does not only bring efficiencies but also goes a long way to reduce time & delay, as well as the overall cost of transportation. This paper presents the efficient mode of transportation system at selected routes in the Bengaluru city, the route stretch selected is 12.2 km in length and it has 8 major intersections. The type of pavement surface consists of both bituminous and Reinforced cement concrete (R.C.C). The complete study stretch is a 2-way 4-lane road. This study provides walkability-index, traffic volume studies in terms of passenger car unit (PCU), time and delay study, and Cost & time analysis. Four modes of transportation are used in this study to find the effective multimodal-transportation system namely, 2-wheeler, 4-wheeler, para-transit [15], and buses/metro. The outcome of this paper is to arrive at the shortest distance for reducing delay & time, and cost-effective travel using multi-mode transport. While focusing on the present condition of the para-transit transport facilities. The time, delay & cost during MMT and to provide a safe, cost-effective & convenient way to travel or transport. The result shows the reduction in time, cost & delay of transportation by using the MMT model. This MMT system could be adopted as an efficient mode of transportation on this route. Similar rural-urban junction routes around the world could use this approach for effective transit by making a modal study.

Akıllı Ulaşım Sistemleri Mimarisi: K-AUS için Öneri

The latest advances in technology and the improvement of decision processes with learning methods based on artificial intelligence have put the word "smart" ahead of all systems that make human life easier. Based on intelligent transportation systems, it is aimed to reduce the damage to the country's economy and the environment while providing technology-based and faster, safer, more accessible, more sustainable and more efficient transportation. The main goal of creating the intelligent transportation systems architecture is to design and implement human-focused, sustainable transportation systems together with cutting-edge technologies such as industry 4.0 technologies, mobile applications, augmented reality, and the internet of things. The transition to the Cooperative Intelligent Transportation Systems (C-ITS) structure by strengthening the infrastructure of intelligent transportation systems is included in the "National Intelligent Transportation Systems Strategy Document and 2020-2023 Action Plan". Intelligent transportation systems architecture needs to be updated according to C-ITS systems that provide interoperability and data integrity. With C-ITS, the aggregate collection of intelligent systems under one roof and the integrity of data will enable sustainable mobility such as monomedical payment in multi-mode transport. Therefore, the main factor in creating the architecture of intelligent transport systems is to create system architecture by making complex systems with data integrity and numerous insignificant idle data into systems that communicate with each other and reach the level of interoperability. In this study, intelligent transportation systems policies in the world have been analyzed and systems that have reached the level of interoperability that will provide the basis of C-ITS and intelligent transportation systems architecture have been proposed.

Electron temperature gradient driven transport model for tokamak plasmas

A new model for electron temperature gradient (ETG) modes is developed as a component of the multi-mode anomalous transport module [Rafiq et al., Phys Plasmas 20, 032506 (2013)] to predict a time-dependent electron temperature profile in conventional and low aspect ratio tokamaks. This model is based on two-fluid equations that govern the dynamics of low-frequency short- and long-wavelength electromagnetic toroidal ETG driven drift modes. A low collisionality NSTX discharge is used to scan the plasma parameter dependence on the ETG real frequency, growth rate, and electron thermal diffusivity. Electron thermal transport is discovered in the deep core region where modes are more electromagnetic in nature. Several previously reported gyrokinetic trends are reproduced, including the dependencies of density gradients, magnetic shear, β and gradient of β (β′), collisionality, safety factor, and toroidicity, where β is the ratio of the plasma pressure to the magnetic pressure. The electron heat diffusivity associated with the ETG mode is discovered to be on a scale consistent with the experimental diffusivity determined by power balance analysis.

Transit Voronoi diagrams in multi-mode public transport networks

Network Voronoi diagrams (N-VDs) are effective geometric constructions for partitioning geographical space constrained by road networks. However, they are not applicable for urban areas with well-developed public transport systems. This study proposes new transit Voronoi diagram (T-VD) models for partitioning geographical space constrained by public transport networks. The proposed T-VD models explicitly consider the complexities of a public transport network, including transfers between different transport modes, dynamic transit schedules, changing network topologies, etc. To efficiently construct T-VDs, geo-computational algorithms are developed by modifying and integrating classical shortest-path algorithms in road networks and transit shortest-path algorithms in public transport networks. Case study results show significant differences between T-VDs and N-VDs, highlighting the need for using T-VDs in urban areas with well-developed public transport systems. The developed geo-computational algorithms efficiently constructed T-VDs in large-scale public transport networks within satisfactory computational times.

Predicted Behaviour of Helium in ITER by the Multi-Mode Transport Model

Predicted Behaviour of Helium in ITER by the Multi-Mode Transport Model

Using weighted multilayer networks to uncover scaling of public transport system

The public transport system is considered as one of the most important subsystems in metropolises for achieving sustainability objectives by mediating resources and travel demand. Representing the various urban transport networks is crucial in understanding travel behavior and the function of the transport system. However, previous studies have ignored the coupling relationships between multi-mode transport networks and travel flows. To address this problem, we constructed a multilayer network to illustrate two modes of transport (bus and metro) by assigning weights of travel flow and efficiency. We explored the scaling of the public transport system to validate the multilayer network and offered new visions for transportation improvements by considering population. The proposed methodology was demonstrated by using public transport datasets of Shanghai, China. For both the bus network and multilayer network, the scaling of node degree versus Population were explored at 1 km * 1 km urban cells. The results suggested that in the multilayer network, the scaling relations between node degree and population can provide valuable insights into quantifying the integration between the public transport system and urban land use, which will benefit sustainable improvements to cities.

Neural network model of the multi-mode anomalous transport module for accelerated transport simulations

A neural network version of the multi-mode anomalous transport module, known as MMMnet, has been developed to calculate plasma turbulent diffusivities in DIII-D with a calculation time suitable for control applications. MMMnet uses a simple artificial neural network structure to predict the ion thermal, electron thermal, and toroidal momentum diffusivities while reproducing Multi-Mode Model (MMM) data with good accuracy and keeping the calculation time as a fraction of that associated with MMM. Model-based control techniques require models with fast calculation times, making many existing physics-oriented predictive codes unsuitable. The control-oriented predictive code Control Oriented Transport Simulator (COTSIM) calculates the most significant plasma dynamics in response to the different actuators while running at a speed useful for control design. In order to achieve this calculation speed, COTSIM often relies on scaling laws and control-level models. Replacing some of these scaling laws and control-level models with neural network versions of more complex physics-level models has the potential of increasing the range of validity and the level of accuracy of COTSIM without compromising its computational speed. In this work, MMMnet is integrated into COTSIM to improve the turbulent diffusivity predictions, which will in turn improve the prediction accuracy associated with the dynamics of many plasma properties.

Accessibility of Multimode Transport Facilities to Suburban Tourist Attractions: Analysis Based on Meso- or Microcommunity Scale in Beijing

Abstract This paper aims to evaluate the accessibility of multimode transport facilities to suburban tourist attractions, under the background of detailed needs of tour transportation planning and ...

Microtearing instabilities and electron thermal transport in low and high collisionality NSTX discharges

Microtearing mode (MTM) real frequency, growth rate, magnetic fluctuation amplitude, and resulting electron thermal transport are studied in systematic NSTX scans of relevant plasma parameters. The dependency of the MTM real frequency and growth rate on plasma parameters, suitable for low and high collision NSTX discharges, is obtained by using the reduced MTM transport model [T. Rafiq et al., Phys. Plasmas 23, 062507 (2016)]. The plasma parameter dependencies are compared and found to be consistent with the results obtained from MTM using the gyrokinetic GYRO code. The scaling trend of collision frequency and plasma beta is found to be consistent with the global energy confinement trend observed in the NSTX experiment. The strength of the magnetic fluctuation is found to be consistent with the gyrokinetic estimate. In earlier studies, it was found that the version of the multi-mode (MM) anomalous transport model, which did not contain the effect of MTMs, provided an appropriate description of the electron temperature profiles in standard tokamak discharges and not in spherical tokamaks. When the MM model, which involves transport associated with MTMs, is incorporated in the TRANSP code and is used in the study of electron thermal transport in NSTX discharges, it is observed that the agreement with the experimental electron temperature profile is substantially improved.

Evaluation of passenger satisfaction of urban multi-mode public transport.

The scientific evaluation of passenger satisfaction for public transport is helpful to enhance the attraction of public transport. To improve the accuracy of passenger satisfaction evaluation for public transport and the scientificity and objectivity of the index weighting, combining the characteristics of analytic hierarchy process (AHP), entropy weight method (EWM) and fuzzy comprehensive evaluation(FCE) method, the passenger satisfaction evaluation system for Ningbo’s urban public transportation was built. The paper analyzed 5046 questionnaires on conventional bus transit and 1682 questionnaires on rail transit in Ningbo city, Passenger satisfaction for Ningbo city’s public transport was evaluated comprehensively, and the evaluation results showed that the overall passenger satisfaction of the public transport in Ningbo was 91.2 in 2019, The case study shows that the application of the AHP-EWM-FCE model on the multi-mode public transport system can objectively quantify passengers’ feelings about urban public transport service, and thus provide a theoretical basis for the improvement of passenger satisfaction in Ningbo.

Super-Gaussian, superdiffusive transport of multimode active matter.

Living matter often exhibits multimode transport that switches between an active, self-propelled motion and a seemingly passive, random motion. Here, we investigate an exactly solvable model of multimode active matter, such as living cells and motor proteins, which alternatingly undergoes active and passive motion. Our model study shows that the reversible transition between a passive mode and an active mode causes super-Gaussian transport dynamics, observed in various experiments. We find the non-Gaussian character of the matter's displacement distribution is essentially determined by the population ratio between active and passive motion. Interestingly, under a certain population ratio of the active and passive modes, the displacement distribution changes from sub-Gaussian to super-Gaussian as time increases. The mean-square displacement of our model exhibits transient superdiffusive dynamics, yet recovers diffusive behavior at both the short- and long-time limits. We finally generalize our model to encompass complex, multimode active matter in an arbitrary spatial dimension.