Multimodal Transportation System Research Articles

Integrated Door-to-Door Transport Services for Air Passengers: From Intermodality to Multimodality

Intermodal and multimodal door-to-door journeys refer to the usage of various transport modes (air, rail, bus, road or maritime) by the traveler to complete a single journey. The main difference between these two approaches is that multimodal transport is executed under a single transport contract (a single ticket) between the passenger, on the one hand, and transport operators, on the other hand. The benefits of this type of service are reflected in the potential to save time and money. Such systems would make the transport sector greener and more sustainable, promote growth and reduce carbon emissions. The purpose of this paper is to define the concept of an air passenger multimodal transport system, identify factors and challenges that determine such a system’s development within Europe and to provide recommendations and directions for future research. The research carried out so far has indicated that market segmentation and transport system characteristics, as well as economic, social and political factors, have direct impacts on system development. This paper provides the basis for introducing single ticket, timetable synchronization and data sharing services, as well as the need to update the related regulations in order to move towards air passenger multimodality in both research and practice.

To What Extent May Transit Stop Spacing Be Increased before Driving Away Riders? Referring to Evidence of the 2017 NHTS in the United States

With the emergence of ride-sourcing and ride-splitting services, more options are available to support shifts away from transit, where maintaining transit ridership increases requirements for transit service quality, so as to promote high-capacity and sustainable transport systems. In this endeavor, proper transit stop spacing is critical for both service accessibility and in-vehicle trip efficiency, as well as operation cost. This research explores acceptable stop spacing for three kinds of transit services from the perspective of travel behavior, drawing on the 2017 National Household Travel Survey in the United States. A stochastic frontier model is developed to infer passengers’ unobservable vertex of acceptable transit access times on the basis of observed walk time, which can be converted to the tolerance with respect to stop spacing with the average walking speed. Significant explanatory variables on the vertex of acceptable transit stop spacing are further identified with their quantified impacts, including household density, household income, wait time, trip distance, transfer, and maintenance purpose, while the inefficiency variance is significantly related to traveler age, wait time, secondary walk time, and trip frequency. Recommended response strategies follow. Findings from this study provide insights, guidelines, and implementation plans for different transit agencies when considering stop spacing redesign, to strengthen transit service appeal and to promote cooperative and sustainable multi-modal urban transport systems.

Impacts of the walking environment on mode and departure time shifts in response to travel time change: Case study in the multi-layered Hong Kong metropolis

Three-dimensional (3D) transportation space is one of the most important characteristics of multi-layered cities; however, fine-scale built environment factors about facilities that support the 3D walking environment were unavailable in understanding travelers’ behaviors before heading to the Big Data era. Using both small (questionnaire survey) and big (large-scale geospatial) data, we conducted a case study in Hong Kong, a well-known vertical metropolis with a multi-modal transportation system. We analyzed mode and departure time shift behaviors in response to travel time change for 2927 participants and examined the impacts of new variables derived from a 3D pedestrian network dataset and potential influencing factors identified in the literature. The results from the mode shift model indicated that having more efficient pedestrian networks, as measured by the total length of walkways and the provision of mobility aid facilities (e.g., travellators, escalators), is effective in promoting mode shift behaviors. Meanwhile, our departure time shift model revealed that having more comfortable walkways, as measured by travel attitude and the provision of mobility aid facilities, increases users’ willingness to make departure time shifts from peak hours. These findings imply that a more efficient and comfortable walking environment facilitates mode and departure time shift behaviors in daily travel. Improving the building and management of walking environments would contribute to a more integrated multi-modal transport system.

Multimodal Urban Transportation Network Capacity Model Considering Intermodal Transportation

Transportation network capacity is an important indicator from measuring the performance of a transportation system. Previous studies on the capacity of multimodal networks have not considered transfers between different transportation modes. In fact, because of the diversified development of the urban transportation system, travelers are no longer limited to a single transportation mode in daily travel. This paper thus proposes an improved network capacity model considering intermodal transportation in urban multimodal transportation systems. The proposed network capacity model is formulated as a bi-level programming problem, in which the lower-level model is a combined modal split and traffic assignment (CMSTA) model. The CMSTA model consists of a cross-nested logit (CNL) in the phase of mode split to account for intermodal transportation and a path-size logit (PSL) in the phase of traffic assignment to account for route overlapping. Also, we consider the flow interaction of different modes (e.g., car and bus) when they share the same links. The Barzilai–Borwein step size method is used to efficiently solve the lower-level CMSTA model (i.e., the CNL-PSL model) of which the objective function is complicated. The numerical results demonstrate the advantages and features of the proposed model. The model is also applied to a real network case to assess the network capacity of the multimodal transportation system.

Perspectives of mobility development in remote areas attractive to tourists

This paper addresses the problem of transport systems in remote areas, defined by a set of constraints deriving from a sparse population, infrequent transportation location means stops and cost-effectiveness of the system. Remote areas attractive to tourists additionally require transportation services designed with respect to changeable demand and the necessity to provide transportation solutions limiting detrimental influence on the environment. This paper aims to identify and assess the perspectives for developing innovative mobility solutions for residents and tourists in remote areas in line with sustainable development and evaluate factors supporting or hindering the development of the selected perspectives. The results of a Delphi study with 23 experts from seven EU Member States, Russia and Norway, enabled the identification of factors shaping the future of mobility in peripheral areas, including IT-supported multimodal transport systems, demand-responsive transport and transport services tailored to the specific needs of different user groups.

System dynamics model for intra-city multimodal transportation considering behavioral indicators and demand under uncertainty conditions

PurposeBy designing a system dynamics model in the form of a multimodal transportation system, this study for the first time seeks to reduce costs and time, and increase customer satisfaction by considering uncertainties in the intra city transit system, especially demand uncertainty and provide a prototype system to prove the capability of the dynamical system.Design/methodology/approachThe paper tried to model the factors affecting the intra city multimodal transportation system by defining different scenarios in the cause-and-effect model. The maps and results developed according to system dynamics modeling principles are discussed.FindingsFour scenarios were considered given the factors affecting the urban transportation system to implement the transportation information system for reducing the material and non-material costs of wrong planning of the intra city transit system. After implementing the scenarios, scenario two was selected under the following conditions: advertising for cultural development, support of authorities by efforts such as street widening to reduce traffic, optimize infrastructure, increase and optimize public transport and etc.Originality/valueThe value of this paper is considering uncertainty in traffic optimization; taking into account behavioral and demand indicators such as cultural promotion, official support, early childhood learning, traffic hours and the impact of traveler social status; investigating the factors affecting the system under investigation and the reciprocal effects of these factors and real-world simulation by considering the factors and effects between them.

Routes Choice in the International Intermodal Networks under the Soft Time Window

There are many transportation nodes in multimodal transport. It is more in line with the actual transportation situation to reasonably select the transportation mode from the perspective of the elastic constraint of arrival time. Considering the elastic constraint of arrival time, the soft time window factor is brought into the research of multimodal transport route optimization, the route optimization model is established, and the appropriate genetic algorithm is selected and designed to deal with it. So as to obtain the optimal transportation scheme of multimodal transport, multimodal transport system optimization involves many factors such as multimodal transport organization, policy, process, responsibility, coordination, and environment.

Exact solutions to a carsharing pricing and relocation problem under uncertainty

In this article we study the problem of jointly deciding carsharing prices and vehicle relocations. We consider carsharing services operating in the context of multi-modal urban transportation systems. Pricing decisions take into account the availability of alternative transport modes, and customer preferences with respect to these. In order to account for the inherent uncertainty in customer preferences, the problem is formulated as a mixed-integer two-stage stochastic program with integer decision variables at both stages. We propose an exact solution method for the problem based on the integer L-Shaped method which exploits an efficient exact algorithm for the solution of the subproblems. Tests on artificial instances based on the city of Milan illustrate that the method can solve, or find good solutions to, moderately sized instances for which a commercial solver fails. Furthermore, our results suggest that, by adjusting prices between different zones of the city, the operator can attract significantly more demand than with a fixed pricing scheme and that such a pricing scheme, coupled with a sufficiently large fleet, significantly reduces the relevance of staff-based relocations. A number of issues, that remain to be addressed in future research, are pointed out in our conclusions.

Unravelling individual mobility temporal patterns using longitudinal smart card data

The increasing availability of longitudinal individual human mobility traces enables the disaggregate analysis of temporal properties of mobility patterns. The objective of this study is to identify distinctive market segments in terms of habitual temporal travel patterns of public transport users. First, travel patterns are clustered using a K-means approach followed by grouping the resulting patterns into a small number of profiles using a hierarchical clustering method. Second, we construct user-week vectors that are then clustered using a Gaussian Mixture Model approach.We apply our clustering analysis to the multi-modal public transport system of Stockholm County, Sweden, using data from more than 3 million smart card-holders. Our clustering analysis resulted in 10 day-of-the-week patterns with their composition varying across the county. In addition, we identify the following hour-by-hour weekly profiles:’Weekly commuters', ‘Lower peaks',’Late travellers', ‘Early birds' and ’Flat curve’. The behavior represented by ’Weekday commuters' and ‘Lower peaks' is most persistent over weeks. We demonstrate how a better understanding of user travel patterns offers policy makers, service planners and providers with enhanced opportunities to understand and cater for diverse market segments, for example by means of tailored fare products.

Integrating public transit signal priority into max-pressure signal control: Methodology and simulation study on a downtown network

Max-pressure signal control has been analytically proven to maximize the network throughput and stabilize queue lengths whenever possible. Since there are many transit lines operating in the metropolis, the max-pressure signal control should be extended to multi-modal transportation systems to achieve more widespread usage. The standard max-pressure controller is more likely to actuate phases during high-demand approaches, which may end up ignoring the arrival of buses, especially in bus rapid transit. In this paper, we propose a novel max-pressure signal control that considers transit signal priority of bus rapid transit systems to achieve both maximum stability for private vehicles and reliable transit service. This study revises the original max-pressure control to include constraints that provide priority for buses. Furthermore, this policy is decentralized which means it only relies on it relies only on the local conditions of each intersection. We set the simulation on the real-world road network with bus rapid transit systems. Numerical results show that the max-pressure signal control which considers transit signal priority can still achieve maximum stability compared with other signal control integrated with transit signal priority. Furthermore, the max-pressure control reduces private vehicle travel time and bus travel time compared to the current signal control.

Coordinating ride-sourcing and public transport services with a reinforcement learning approach

Combining ride-sourcing and public transit services (with ride-sourcing service to address the first/last-mile issues) can bring many benefits, such as saving passengers’ trip fares, improving drivers’ earnings, reducing gas emissions, and alleviating traffic congestion. However, it still remains a challenging issue to coordinate ride-sourcing and public transit services through real-time order dispatching. In this paper, we model the order dispatching in a multi-modal transportation system as a large-scale sequential decision-making problem. A centralized algorithm is then proposed to dispatch idle drivers to arriving passenger orders and determine whether to advise passengers to use a combined mode of ride-sourcing and public transit services (if yes, the algorithm also needs to recommend an appropriate transportation hub). In particular, our proposed algorithm contains a reinforcement learning approach that estimates the long-term expected rewards, and an Integer Linear Programming (ILP) that matches idle drivers and waiting passengers in real-time based on both immediate revenue and the estimated long-term rewards. By evaluation on the real-world on-demand data and metro system in Manhattan, the proposed method shows remarkable improvement on the system’s efficiency under different density of supply and demands.

Multimodal Transport Solutions for Smart Cities

The research article has shown the multimodal transport solutions for smart cities in India. The researcher has discussed the concept of multimodal transport solution, problems and also characteristics for the solution of multimodal transport systems in the smart cities. The main findings are to show that the multimodal system has the capacity to overcome the issues of smart cities. It also has power to mitigate traffic issues which take place that take place in different cities. The system develops the product delivery times, reduces many inventory costs and also keeps the shipment costs under control. Keyword :Multimodal transport solution, Smart cities, communication technology.

PUBA: Privacy-Preserving User-Data Bookkeeping and Analytics

Abstract In this paper we propose Privacy-preserving User-data Bookkeeping & Analytics (PUBA), a building block destined to enable the implementation of business models (e.g., targeted advertising) and regulations (e.g., fraud detection) requiring user-data analysis in a privacy-preserving way. In PUBA, users keep an unlinkable but authenticated cryptographic logbook containing their historic data on their device. This logbook can only be updated by the operator while its content is not revealed. Users can take part in a privacy-preserving analytics computation, where it is ensured that their logbook is up-to-date and authentic while the potentially secret analytics function is verified to be privacy-friendly. Taking constrained devices into account, users may also outsource analytic computations (to a potentially malicious proxy not colluding with the operator).We model our novel building block in the Universal Composability framework and provide a practical protocol instantiation. To demonstrate the flexibility of PUBA, we sketch instantiations of privacy-preserving fraud detection and targeted advertising, although it could be used in many more scenarios, e.g. data analytics for multi-modal transportation systems. We implemented our bookkeeping protocols and an exemplary outsourced analytics computation based on logistic regression using the MP-SPDZ MPC framework. Performance evaluations using a smartphone as user device and more powerful hardware for operator and proxy suggest that PUBA for smaller logbooks can indeed be practical.

Optimal pricing and investment in a multi-modal city — Introducing a macroscopic network design problem based on the MFD

Improving the performance of an existing transportation system is a challenge for engineers and policy makers as many dimensions and system design variables are interacting. In this paper, we propose the three-dimensional macroscopic fundamental diagram network design problem (3D-MFD-NDP). It is a strategic macroscopic tool to identify the directions of decision making in a multimodal transportation system, where the provision of roads and public transport services are interacting with costs for cars and public transport services in the performance of the entire road surface transportation system. The 3D-MFD-NDP models their effects aggregated at the network level and does not locate all measures to the road network. The objective function of the introduced 3D-MFD-NDP is minimizing the total travel time, while the design variables of the problem are the user costs for cars and bus tickets, the bus headway, the share of dedicated bus lanes and the length of the road network. The advantage of the 3D-MFD-NDP compared to existing approaches is that it is formulated as a mathematical program with equilibrium constraints (MPEC) that allows a fast closed-form solution instead of being simulation-based, usually computing many details not required in strategic decision making. We apply the 3D-MFD-NDP to the greater area of Zurich to study two different problems. First, we investigate how the current network performance can be increased by pricing and investment measures. Despite difficulties in identifying reliable cost information for the provision of roads, we find that substantial travel time savings are possible, especially when limiting car use by restricting its space and increasing its costs. Second, we investigate the response to a 20% population growth in urban and suburban regions with car and public transport prices as well as bus frequency as the free design variables. We find that the system can accommodate the population growth, but as the system costs are shared among more users, the costs per trip are lessened, which attenuates the steering effect of prices.

Improving the technology of product supply chain management in the context of the development of multimodal transportation systems in the European union countries

The relevance of the study is caused by the growing role of multimodal transportation in Ukraine and the European Union, ensures the optimization of the goods supply chain management to the consignee, and an important element of this development is the significant role of rail transport in the multimodal transportation, which is relevant towards minimization of costs and preserving the environment. The purpose of the article is to develop measures to improve the designing processes of the multimodal route parts for grain supply chains through the using of network systems and minimizing the total transportation cost. Taking into account the specifics of the functioning and management of multimodal transportation, an approach to the integrated assessment of the effect from the transport enterprises activities in multimodal transportation based on the building of network models of each part of the multimodal route is offered. The article presents the results of the analysis and theoretical generalization of approaches to formalizing the process of functioning the multimodal transportation systems for goods supply chains with rail and road modes of transport. The materials of the article are of practical value for vocational and industrial training of logistics operators, transport companies’ staff, and scientific and pedagogical personnel in order to improve their professional competencies.

GIS and Gravity Model-Based Accessibility Measure for Delhi Metro

Metro is a rapid transit mode that helps in fast and efficient movement of the public. To make metro journey more convenient and attractive, from origin to destination, accessibility of metro must be good. In this study, tri-level analysis is carried out for the study area of Delhi. Traffic congestion and environmental condition of Delhi are degrading continuously, and to improve the situation, a sustainable Multi Modal Transport System (MMTS) with high accessibility must be explored. In this paper, policy to improve zone to zone metro accessibility for work purpose is discussed and the relation between multimodal transport system with accessibility is studied using GIS (ArcGIS), macrosimulation software (VISUM) and gravity model. It was observed that by the addition and extension of metro lines, transport accessibility is greatly improved. This study shows that percentage of zones in Delhi with higher accessibility level could increase from 5 to 13.88% with the implementation of phase IV of metro. In addition, the implementation of phase IV metro could reduce the average travel time between zones and metro stations. It will also reduce the travel time between metro stations substantially (for the zones covered in this study the average travel time is reduced by 23.63% and for the station covered in this study the average travel time is reduced by 17.73%). Further, it was found that ‘out vehicle travel time’ (OVTT) is having a major impact on the accessibility of metro. Lastly, it was concluded that with the higher level of metro accessibility, people will prefer the multimodal transport system with metro as the main mode. Travel time isochrones for public and private trips for the estimated MMTS model are also presented in this paper to depict the changes in accessibility for different scenarios. This will further help in improving private transport accessibility by reducing congestion on roads. Thus, planning for transport accessibility helps in developing the city in a sustainable manner in the future.

Multiagent-Based Modeling and Simulation of a Coal Multimodal Transport System

With the change in coal supply and demand, the dynamics of multiple transit nodes and the connection between different transportation modes make the Coal Multimodal Transportation System (CMTS) more complicated in the long-distance transportation of coal. Therefore, it is necessary to analyze the multimodal transportation nodes, build a coal multimodal transportation model, measure the network throughput through simulation experiments, and identify system bottlenecks. The CMTS is a complex nonlinear dynamic system with many participants with complex and uncertain links. Different transportation modes, operation links, and connection processes will affect system performance, and modeling and simulation technology effectively study complex dynamic systems. This paper takes the CMTS as the research object, uses agent-based modeling methods and Witness simulation software to analyze the composition and operation mechanism of CMTS, establishes the multiagent model of CMTS, and validates the model by a Witness simulation experiment of northern coal shipped to south. The simulation results indicate the capacity of the transport route and resource utilization of nodes in CMTS in case of different demand growth rates in the future. Based on the multiagent model andWitness simulation results, this paper provides practical support for constructing and applying the multimodal transport system model library and provides the basis for decision-making for the CMTS plan.

Decarbonizing Regional Multi-Modal Transportation System with Shared Electric Charging Hub

Decarbonizing Regional Multi-Modal Transportation System with Shared Electric Charging Hub

Bus Frequency Optimization in a Large-Scale Multi-Modal Transportation System: Integrating 3d-Mfd and Dynamic Traffic Assignment

Bus Frequency Optimization in a Large-Scale Multi-Modal Transportation System: Integrating 3d-Mfd and Dynamic Traffic Assignment

Analyzing complexities in the Brazilian soybean supply chain: a systems thinking and modeling approach

Purpose This study aims to analyze the complexities of the Brazilian soybean supply chain (SSC) and develop strategic interventions to improve the origin system’s performance. Design/methodology/approach This study used stakeholder interviews to identify the SSC bottlenecks and determine and assess drivers of competitiveness. A methodological framework based on the systems thinking approach for developing long-term structural changes was used. The problem was structured using behavior over time graph and causal loop modeling to propose three investment strategies to solve the logistics problem in SSC. Findings This study highlights the gaps in coordination between stakeholders and the public sector regarding the public policy for infrastructure investment. Three strategic interventions were developed to address the agro-industrial logistical problem, namely, investment in storage, multimodal transport systems and improvements in existing transport infrastructure. To overcome transport and storage logistics limitations, the authors suggest different forms of partnerships, including public-private partnerships. Research limitations/implications This research is limited to evaluating an agricultural commodity (soybean) and does not include its by-products. The sample of stakeholders was limited and the boundary of analysis was Brazil. Nevertheless, the study showed how strategic interventions could be developed following a holistic analysis. Practical implications The proposed integrated approach illustrates the development of three strategic initiatives. It can be implemented by stakeholders, including the public sector, which is the basis for providing assertive long-term investments in Brazilian logistics. Social implications The SSC analysis could promote the implementation of systemically determined interventions and strategies. It could significantly improve the performance of agricultural systems and help the formulation of public policies aimed at rural development. Originality/value The use of system dynamics to identify intervention points is an essential contribution to mitigating the SSC’s hindrances. Moreover, the combining methodologies resulted in comprehensive intervention strategies.