Multimodal Transportation System Research Articles

Efficiency Based Evaluation of Public Transport and Paratransit Systems with a View to Integrating Transportation

Rapid urbanization, increasing population, and a booming economy have stimulated growth in Indian cites, resulting in higher levels of dependence on private vehicles. This has raised serious issues over the sustainability of transport infrastructure in cities. Public transportation (PT) systems can help achieve sustainable transportation. But they face competition from intermediate public transport (IPT) or Paratransit. The existing PT and IPT systems, therefore, need to re-plan their operations to complement each other and deliver a wider network of services. To achieve this, an evaluation of both PT and IPT systems at microscopic levels is needed to facilitate their possible integration in a coordinated multimodal transportation system. The present paper attempts to evaluate the public and paratransit systems in the city of Surat in the Indian state of Gujarat using a data envelopment analysis (DEA) technique in DEAP software at the individual and system level. The operations, route design, and cost efficiency of both systems are evaluated to understand how well the existing set-up caters to demand. The arithmetic mean of operations, route design, and cost efficiencies of 26 routes of PT system were worked out to be 0.89, 0.94, and 0.69, while that of the 13 routes of the IPT system were 0.92, 0.97, and 0.88 respectively. The system investigation shows that analytically, only 8% of IPT routes were inefficient in all the three aspects, compared with 42% of PT routes. The performance of each route was analyzed, appropriate suggestions made, and the potential of these systems for designing an integrated transport system highlighted.

A robust fuzzy optimisation for a multi-objective pharmaceutical supply chain network design problem considering reliability and delivery time

Due to the emergency role of pharmaceutical supply chains, there has been rapid development of optimisation techniques as one of efficient tools to improve pharmaceutical supply chain network design. To improve the pharmaceutical supply chain network, this study proposes a novel location-allocation-inventory model as a multi-objective, multi-echelon, multi-product, multi-period and multi-modal transportation system for pharmaceutical supply chain network design under uncertainty. The proposed model aims to optimise multiple objectives, including minimising the total costs and the delivery time while maximising the transportation system reliability simultaneously. To control the impacts of uncertain parameters including the ordering, delivery, purchase, and transportation costs and the capacity of vehicles, warehouses and of distribution centres, a robust fuzzy optimisation approach is developed. An efficient modification of a state-of-the-art evolutionary algorithm called the red deer algorithm (RDA) in its multi-objective form abbreviated as IMORDA is developed and compared with itself and well-established algorithms in the literature such as non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimisation (MOPSO). The results confirm the applicability and efficiency of the IMORDA for the proposed model and encourage further development of this new metaheuristic.

Multi-Modal Combined Route Choice Modeling in the MaaS Age Considering Generalized Path Overlapping Problem

In the MaaS (Mobility as a Service) age, the alternatives of route choice for a trip will not be the single mode paths, but the combined routes utilizing more than one travel mode in the multi-modal transportation systems. When modeling the multi-modal combined route choices, alternative routes are correlated not only because of the overlapping of physical links, but also because of the overlapping of travel modes. We define this problem as the generalized path overlapping problem. To address the generalized overlapping problem, a multi-modal logit kernel (MLK) model is proposed to explicitly consider the correlations of unobserved utilities of combined routes. In this model, the unobserved utilities of combined routes are divided to two parts, the link specific parts and the independent route specific parts. The link specific parts are further divided to two parts: physical link specific and the mode specific. The generalized path overlapping problem is captured by the sharing of these two parts of unobserved link utilities. Based on this model, the stochastic user equilibrium on multi-model transport networks is represented as a fixed-point problem. Numerical studies are designed to illustrate the effects of incorporating generalized overlapping problem on disaggregated route choice prediction and aggregated traffic flow assignment. With different settings of physical link and mode specific error terms, the variations of disaggregated route choice predictions and aggregated traffic flows are discussed. It is found that, the generalized overlapping problem can be captured by the proposed model and significantly affect both the individual route choice predictions and aggregated traffic flows at equilibrium.

A multi-objective robust optimization approach for green location-routing planning of multi-modal transportation systems under uncertainty

Carbon emission has been widely studied in transportation research in general, yet research on carbon emission specifically in hazardous material transportation remains surprisingly limited. This study presents a multi-objective model for locating transfer points and routing in a multi-modal network of hazardous materials, accounting for multiple different uncertainties, while minimizing carbon emission alongside risk and cost of transportation. This study models uncertainties in accident probabilities, emission factors, and costs of establishing transfer points with polyhedral uncertainty sets, and utilizes robust counterpart optimization to tackle these uncertainties. The application of the proposed approach is examined in a case study of petroleum product transportation. The results of our analyses confirm the effectiveness and robustness of the developed model. Specifically, it is found that the proposed model can reduce carbon emissions by 873 g, and individuals at risk by 0.28, for every additional dollar spent.

Simulation-Based Design of Urban Bi-modal Transport Systems

The three-dimensional passenger macroscopic fundamental diagram (pMFD) describes the relation of the network accumulation of public transport and private vehicles, and the passenger production. It allows for modeling the multi-modal traffic dynamics in urban networks and deriving innovative performance indicators. This paper integrates this concept into a multi-modal transport system design framework formulated as a simulation-based optimization problem. In doing so, we consider the competition for limited road space and the operational characteristics, such as congestion occurrences, at the strategic design level. We evaluate the proposed framework in a case study for the Sioux Falls network. Thereby, we deliver a proof of concept, and show that the proposed methodology indeed designs a transport system which benefits the overall system's performance. This paper further advances the integration of sequential model-based optimization techniques, macroscopic traffic flow concepts, and traffic simulation to design multi-modal transport systems. This supports transport planners and local authorities in composing efficient and robust transport networks.

Hybrid simulation to support interdependence modeling of a multimodal transportation network

The inland waterways in the United States (U.S.) transport approximately 20% of coal, 22% of petroleum products, and 60% of farm exports making these waterways a significant contributor to the U.S. multimodal transportation system. In this study, data of extreme natural events affecting the U.S. inland waterways are collected and used to predict possible occurrences of such events using a spatio-temporal statistical model. A simulation tool incorporating this model is developed to investigate the impact of waterway disruptions on the interconnected multimodal transportation systems. A case study on the lower Mississippi River and the McClellan–Kerr Arkansas River Navigation System along with the related highways is provided to illustrate the use of the simulation tool for operation simulation and interdependence modeling of the multimodal transportation network. This tool provides a flexible means for quickly evaluating the performance of such Interdependent Critical Infrastructures (ICIs) and assisting in decision making.

On Transport Monitoring and Forecasting During COVID-19 Pandemic in Rome

Abstract This paper presents the results of a study on the Rome mobility system aiming at estimating the impacts of the progressive lockdown, imposed by the government, due to the Covid-19 pandemic as well as to support decision makers in planning the transport system for the restart towards a post-Covid “new normal”. The analysis of data obtained by the transport monitoring system has been fundamental for both investigating effects of the lockdown and feeding transport models to predict the impacts on future actions. At first, the paper focuses on the so-called transport analytics, by describing mobility trends for the multimodal transportation system of Rome. Then, the results of the simulated scenarios to design public transport services, able to ensure passengers social distancing required in the first post-Covid months, are presented and discussed.

Development of a Model for Evaluating the Coverage Area of Transit Center Using Smart Card Data

Since metropolitan cities are broadening as a result of urban sprawl, multimodal transportation systems have been adopted to fulfill the connection between the suburban and urban areas. The transportation system is being revamped around the transit center in the urban area to facilitate access to the downtown area from the suburbs. Studies are being conducted to improve the accessibility of public transportation by using the concept of hub-and-spoke. In this study, we develop a coverage area index (CAI) to assess the impact of a transit center on access to urban areas from the suburbs quantitatively. The concept of network centrality and the kernel density function is used to evaluate the extent of the influence of a transit center. The smart card data in the Seoul metropolitan area are used to analyze the CAI. Six transit centers in the Seoul metropolitan area are investigated to compare the coverage area to the transit center. The bandwidth of the kernel density function is set as 2 km considering the size and influence of each region. We evaluate six transit centers using the CAIs in Seoul compared to the index characteristics with transit accessibility (TA) index from previous studies. The CAI is possible to identify the incompetent centers, alternative routes to solve the problems of overcrowding on the centers, and areas with insufficient supplies of regional transit.

Пути решения проблем пассажирских пригородных перевозок при помощи мультимодальной транспортной системы

The article deals with the problems and solutions of suburban passenger transport as a factor of increasing demand for rail transport, reducing their cost and travel time. We are studying a multimodal transport system that is being upgraded and used on the route Krasnoufimsk–Druzhinino–Yekaterinburg. In conclusion, it is concluded that it is necessary to calculate the bandwidth of the path of the high-speed train, an analysis of traffic flow from each departure point, calculate the costs necessary for the project.

Estimating Traffic Density, Trends and the Impact of BRT Construction on Traffic Junctions of Karachi Using Geospatial Techniques

Everyone must commute on a daily basis to work, get educated, buy necessities, seek entertainment or visit friends and family. Thus, transport infrastructure has become an integral or most probably the most important aspect of urban design. Major cities of the world have a mass transit system or even multimodal transport system to cater for the transportation needs of their citizens. Karachi a mega polis city of approximately 23 million residents lacks a properly coordinated and well scheduled transportation mechanism. Therefore, its residents primarily rely on their own means to fulfill their commuting needs resulting in heavy traffics and very significant time delays on its roads. These time delays and rush hour frustrations in turn have a negative impact on the overall productivity and psychological and social well-being of the populace. The government has in recent years taken up this matter seriously and begun construction of Bus Rapid Transit systems along various major traffic corridors of Karachi. The purpose of this thesis was to study the change of traffic behavior in recent years, traffic density variations and the impact on transportation road might have along its corridors using geospatial techniques. The results of this study showed that daily average passenger commutes experienced an increase of approximately 58.4% from 2012 to 2017 and that major mode of transportation shifted from public transit vehicles to private ones specially motorcycles resulting in unfavorable occupancy to PCU ratio. This in turn has adversely affected the traffic density of the city. This congestion can only see some relief when the BRT becomes operational.

On the creation of the Intelligent multimodal transport system of Russia and the project “Intelligent container chain“

In the article, the ideas for the development of unmanned freight vehicles and the construction of high-speed railways are transformed into an innovative resource-efficient and high-tech solution — the creation of an Intelligent Multimodal Transport System of Russia, and the development of projects and structures for unmanned vehicle freight traffic — into the “Intelligent Container Chain” project. The proposals put forward are based on an analysis of the potential of the Russian railways and its implications for the spatial development of the Russian Federation. The trends in the development of unmanned vehicles are analyzed and it is concluded that its implementation in Russia will require the construction of specialized road, energy and digital infrastructure with the appropriate allocation of land allocation and supply of energy, communications and other technological communications. The need to search for new scientific, technological and organizational solutions is shown to achieve synergy between the demand for container road transport and the infrastructural and technological capabilities available in the railway transport system. As such a decision, the expediency of developing a new Intelligent Multimodal Transport System under the auspices of the Russian Railways was substantiated. Priority directions for the development of this system, as well as technical and investment solutions and scientific and technological tasks necessary for its implementation, have been determined. At the same time, questions have been formulated that require scientific study. The advantages of the proposed system for increasing the efficiency of using the transport space and developing a breakthrough competitive infrastructure business of the Russian Railways are disclosed. The prospect of the formation on this basis of unique high-tech groundwork is shown, which makes it possible to realize the potential of Russian science and the transport complex and has a high export potential.

Using data and technology to integrate mobility modes in low-income cities

ABSTRACT The utilisation of data and technology in transportation has given rise to new forms of flexible, on-demand mobility and urban freight services. Such advances have also enabled the integration of multiple transportation modes and facilitated more predictable, environmentally-friendly, high-volume trips. While many of these technologies are now commonplace in higher income cities, they are less prevalent in lower income cities. This review identifies a) recent advances in technology and data that can facilitate multimodal urban travel, and b) the existing and potential application of these advances in low- and lower middle-income (LIC and LMIC) cities, particularly in Sub-Saharan Africa and Asia. This review examines peer-reviewed and grey literature and uses a multi-method approach with expert interviews. The review identifies open transportation data and data standards, global positioning systems, cashless fare payment, and blockchain as having high potential to facilitate integrated mobility in lower income contexts, and considers potential barriers to adopting and risks of utilising these technologies in LICs and LMICs. The review finds that, enabled by technology and data advances, LICs and LMICs could leapfrog the high car use and inefficient urban freight systems typical of higher income cities to more integrated, efficient, multimodal transport systems.

Traffic-induced epidemic suppression in multiplex networks

Multiplex networks have been proposed as an effective abstract of real complex systems, ranging from multi-modal urban transportation systems to communication systems. In this paper, we investigate a traffic-driven epidemic model in multiplex networks, and derive a theoretical approach to accurately predict the epidemic threshold of each layer. Our results show that the multiplex structure can produce different effects on the epidemic threshold of layers. Interestingly, one important finding is that the epidemic can be completely suppressed in a certain layer. This phenomenon occurs only when the connectivity of layers is very different, and the traffic flow is heterogeneously distributed over the layers. Therefore, epidemic spreading becomes quite distinct among the layers with different amounts of traffic flow. By using mean-field analysis, an explicit expression is derived to detect this traffic-induced epidemic suppression phenomenon. The accuracy of theoretical prediction is assessed in Erdős–Rényi and scale-free multiplex networks.

Multi-modal transportation recommendation with unified route representation learning

Multi-modal transportation recommendation aims to provide the most appropriate travel route with various transportation modes according to certain criteria. After analyzing large-scale navigation data, we find that route representations exhibit two patterns: spatio-temporal autocorrelations within transportation networks and the semantic coherence of route sequences. However, there are few studies that consider both patterns when developing multi-modal transportation systems. To this end, in this paper, we study multi-modal transportation recommendation with unified route representation learning by exploiting both spatio-temporal dependencies in transportation networks and the semantic coherence of historical routes. Specifically, we propose to unify both dynamic graph representation learning and hierarchical multi-task learning for multi-modal transportation recommendations. Along this line, we first transform the multi-modal transportation network into time-dependent multi-view transportation graphs and propose a spatiotemporal graph neural network module to capture the spatial and temporal autocorrelation. Then, we introduce a coherent-aware attentive route representation learning module to project arbitrary-length routes into fixed-length representation vectors, with explicit modeling of route coherence from historical routes. Moreover, we develop a hierarchical multi-task learning module to differentiate route representations for different transport modes, and this is guided by the final recommendation feedback as well as multiple auxiliary tasks equipped in different network layers. Extensive experimental results on two large-scale real-world datasets demonstrate the performance of the proposed system outperforms eight baselines.

Analyzing intra-metropolitan variation in highway traffic performance in Los Angeles using archived real-time data

ABSTRACT We conduct a case study of highway system performance in Los Angeles County. We use the Los Angeles Archived Data Management System, a comprehensive archive of regional real-time multi-modal transportation system data, to analyze effects of systematic, functional, random, and land use factors on performance variation over different time periods of the day. To understand functional class effects, we use cluster analysis on geometric and demand parameters to identify functionally similar groups of highway segments. We compare performance between groups and across segments within groups. We perform regression analysis to test the influence of various factors on performance. We find that after controlling for time of day, accidents, and adjacent population density, group or peer effects have significant influence. This suggests that peer group level, as opposed to regional, performance measurement and monitoring is useful. Our research has significant implications for transportation system monitoring and planning.

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.

Multimodal transportation system protection against sea level rise

Transportation infrastructure resilience is an important component of a region’s ability to recover from natural disasters. While Sea Level Rise (SLR) is becoming inevitable with climate change, little is known of the impact of protection strategies on multiple modes of transport. The present paper proposes a framework where a range of coastal protection strategies are undertaken in the case of one meter of SLR (expected by the year 2100). The methodology incorporates high-resolution hydrodynamic simulations using the Coastal Storm Modeling System (CoSMoS) and traffic simulations using the Multi-Agent Transport Simulation (MATSim) to quantify the potential impact of SLR and protection strategies on both the highway and public transit systems in the San Francisco Bay Area.The results of the traffic simulations are analyzed at the regional and Transportation Analysis Zone (TAZ) levels. Modeling results show that coastal protection of one area will affect the transportation system (sometimes negatively) in areas beyond its vicinity. The improved spatial resolution, and the integration of highway and transit networks in a unified model, reveal transportation phenomena that were not identified in previous studies. By quantifying the impacts on commuters’ mobility in different TAZs, the methodology can be used to develop effective and inclusive strategies against SLR for a given region of interest.

Measuring the effects of job competition and matching on employment accessibility

Accessibility has often been seen as a key indicator to assess socio-economic interactions and planning policies involving urban transportation and land use. Job competition and matching are important factors for individual job seekers as they evaluate job prospects, often including employment accessibility. However, due to inadequate data and the complex representation and interpretation of methods used, many studies have not considered job competition and matching as they attempted to assess employment accessibility. Most of the available studies do not analyze the effects of economic status, educational background, and transportation mode. In the small number of studies addressing job competition, few have considered the combination of multi-modal transportation access for commuters, though these are available in large metropolitan areas. In order to gain a better understanding of employment accessibility, this study adopts a method to assess employment accessibility by incorporating job proximity, job competition, and job matching in a multi-modal transportation system. This study focuses on the eight-county Greater Houston metropolitan region. Unemployed workers in the civilian labor force are a proxy for the number of job seekers. It is used to calculate employment accessibilities for job seekers in poverty, with different educational backgrounds, and commuting via multiple transportation modes. An interesting finding is that household auto ownership is an important determinant not only for auto drivers, but also for transit riders engaged in job seeking. In an automobile-oriented city such as Houston, driving to bus stops or rail transit stations provides job seekers significant advantages over walk-to-transit riders, especially for those living in suburban areas outside the boundary of the existing transit systems serving the central city or the core county.

Impacts of COVID-19 on the Transport Sector and Measures as Well as Recommendations of Policies and Future Research: A Report on SIG-C1 Transport Theory and Modelling

COVID-19 has critically impacted many aspects of societies worldwide, particularly on people's transportation activities. This report summarizes the influences of COVID-19 pandemic, reviews existing research results, and identifies future research needs in the scope of SIG C1 in the WCTRS. We first review models on contagion spreading through transportation networks, including aggregated spatial metapopulation models and disaggregated individual-based models. We identify that further research is needed to consider both intercity and intracity mobilities and leverage emerging multiple data resources for constructing individuals' complete trip chains. Next, we discuss transport operation needs in the aftermath of COVID-19. We find that there remains a need for operating multimodal urban transport systems to satisfy people's basic travel demands while minimizing contagion risks. Relevant research needs are identified in optimizing transport operation via modern data acquisition technologies and advanced modelling methods. Last, we discuss the impacts of COVID-19 on people's travel behaviour and overall travel demand patterns. We identify relevant research methods, including data-driven methods and stated-preference survey. Practical intervention measures are also recommended to shift travel demand towards more healthy and sustainable travel modes

Research review on improving the efficiency of multimodal transportation based on technological solutions

During the process of analyzing Russian and foreign studies in the field of multimodal cargo transportation, existing methods for improving the efficiency of the multimodal transport system are considered. Improving efficiency of multimodal transportation today is possible due to the optimization of the interaction system between the used modes of transport and transportation of goods. Cost reduction, optimization of cargo terminals, the formation and development of the transport corridors network also play an important role in improving this type of transportation. The use of the new capabilities of satellite navigation, as well as the importance of reducing the environmental load and fuel economy should not be underestimated. The minimization of risks throughout the field of multimodal transportation, the improvement of the legislative framework and document management processes are important. To solve these problems, experts propose methods for the operational management of cargo delivery and expedited transportation. Based on these methods, the place of transport logistics in the process of bringing goods to the consumer during multimodal transportation is determined. A methodology for designing a multimodal transport network has been developed, this methodology involves the formation and development of transport corridors, taking into account new conditions for the globalization of transportation. Researches on the organization of transportation using multimodal transport units and technologies (containers, contrailers, "running highway") have been conducted. Based on the theory of controlled networks and integer linear programming methods, the experts developed mathematical models for the distribution of cargo flows, the choice of the most favorable transportation routes, ideal loading of rolling stock, and transportation of goods using the best forwarding algorithm. Methods are proposed for assessing the maximum capacity of the transport network and predicting the interference of weather conditions in the process of goods transportation, based on the Ford-Fulkerson theorem on the maximum flow and minimum cross section and the use of the mathematical apparatus of Markov chains. As a result of the analysis, it was concluded that the lack of a universal methodology for managing multimodal transportation processes on the basis of a telecommunication platform requires the formulation and solution of the important scientific and practical problem - the development of popular organizational and management methods, technological solutions to ensure the effectiveness of multimodal transportation. The totality of the tasks to be solved in this case has important socio-economic significance for the Russian Federation.