Priorities in urban transport research

Research should be fundamental to transportation as a phenomenon, and yet central to the problems that need to be solved. This paper looks at the history of transportation research in the U.S. with a view toward understanding the bases of past research priorities, and deriving a basis for proposing future priorities. As a result, varieties of research are proposed. They include research which is progressive by criteria of the field during past decades, research which is critical or established as needed by rejection of those criteria, and research which arises as newly required by recent mandates to the field. As the most significant conclusion, it is proposed that research models be built — models which put the understanding of urban structure dynamics ahead of accuracy in forecasting.The authors wish to acknowledge the assistance of Ray Blessing, Department of Urban Studies and Planning, and Thomas McKim, Department of Civil Engineering, M.I.T. This paper has profited from criticism by Professor Daniel Brand. The original version was prepared with support from the National Science Foundation.     

Robust models for transportation service network design

In this paper robust models are presented for the transportation service network design problem, using the ferry service network design problem as an example application. The base assumption is that only the mean and an upper bound on the passenger demand are known. In one robust model, this information is supplemented by a lower bound on the demand, whereas in a second robust model, the assumption is made that the variance of the demand is known, in addition to the mean and upper bound. The relationship between the two models is investigated and characterized analytically. A case study using the ferry service in Hong Kong is provided to illustrate the models.     

An integrated model of facility location and transportation network design

Network location models have been used extensively for siting public and private facilities. In this paper, we investigate a model that simultaneously optimizes facility locations and the design of the underlying transportation network. Motivated by the simple observation that changing the network topology is often more cost-effective than adding facilities to improve service levels, the model has a number of applications in regional planning, distribution, energy management, and other areas. The model generalizes the classical simple plant location problem. We show how the model can be solved effectively. We then use the model to analyze two potential transportation planning scenarios. The fundamental question of resource allocation between facilities and links is investigated, and a detailed sensitivity analysis provides insight into the model's usefulness for aiding budgeting and planning decisions. We conclude by identifying promising research directions.     

Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities

The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.     

The role of congestion of transportation networks in urban location and travel choices

Congestion of urban transportation systems results from an equilibrium of location and travel choices with generalized travel costs which increase with vehicle flows as well as other factors. The use of network equilibrium concepts in analyzing urban policies and evaluating alternative plans is examined. Issues arising in the use of network equilibrium models are described, and formulations of urban network prediction and design models are explored.     

Service network design with asset management: Formulations and comparative analyses

In this paper, we address the service network design with asset management problem, which integrates asset management considerations into service network design models for consolidation-based freight carriers. We propose model formulations based on arc variables for both flow and design, as well as formulations with path flow variables and new cycle design variables. Problem instances reflecting actual planning problems are used in the computational study to analyze the strengths and weaknesses of the various model formulations and the impact of asset management considerations on the transportation plan and the computational effort. Experimental results indicate that formulations based on cycle variables outperform traditional arc-based formulations, and that considering asset management issues may significantly impact the outcome of service planning models.     

Macroscopic traffic models for vehicle-follower automated transportation systems

The problem of distributing and routing vehicles in a large automated transportation network may be approached through the design of on-line control algorithms, particularly when the network contains many origin-destination pairs and alternate routes. To develop such algorithms, it is necessary to obtain models that accurately represent the dynamic behavior of vehicles on the guideway network. In this paper, models based on density, flow and average velocity variables are derived for the vehicle-follower longitudinal control scheme. Models suitable for use in analysis and simulation work are developed for links, merges, diverges, and stations. The proposed models are shown to compare favorably with simulation results that use explicit modeling of vehicle dynamic modeling of vehicle dynamic interaction.     

Network concentration indices for less-than-truckload transportation

An efficient and service-oriented transportation network is a necessary resource for successful less-than-truckload operations. The design and evaluation of transportation networks are mainly driven by quantitative particularly cost-oriented measures, such as transport and transshipment costs. This type of measurement, however, simply cannot represent the manifold performance of a transportation network. In particular, incorporating network concentration into network design decisions overcomes the shortcomings of purely cost-oriented decisions because spatial network concentration is at the root of many aspects of network performance (e.g., congestion and network vulnerability). This paper suggests modifications to the network concentration index and the hubbing concentration index from the passenger airline context for less-than-truckload road transportation. The modified indices enable information to be conveyed by network concentration into less-than-truckload network design decisions and provide a suitable perspective to include service-oriented aspects into network design.     

Geographic information systems for transportation in perspective

The late 1980s saw the first widespread use of Geographic Information Systems (GIS) in transportation research and management. Due to the specific requirements of transportation applications and of the rather late adoption of this information technology in transportation, research has been directed toward enhancing existing GIS approaches to enable the full range of capabilities needed in transportation research and management. This paper places the concept of transportation GIS in the broader perspective of research in GIS and Geographic Information Science. The emphasis is placed on the requirements specific of the transportation domain of application of this emerging information technology as well as on core research challenges.     

Designing computable general equilibrium models for transportation applications

This paper presents a review of Computable General Equilibrium (CGE) model applications for spatial economic and transport interaction modelling. This paper has three objectives (1) To deliver an up to date and comprehensive literature review on applications of CGE models in transportation, (2) To analyze the different methodological approaches and their theoretical and practical advantages and disadvantages, and (3) To ultimately provide guidance on designing CGE models for various transportation analyses. The content of the paper is as follows: first, a brief introduction to CGE models is provided. The history of CGE models is traced, ranging from their origins and seminal applications in economics, to their eventual adoption in transportation research. This is followed by a comprehensive review of the application of CGE models to transport projects and policies. Various applications in transportation are reviewed in terms of their intended application, as well as their treatment of space and time. Finally, these applications are contrasted with respect to their methodological approaches, with a close examination of various influential model choices. Here, the essential design choices made within these model applications are explained and debated, to clearly elaborate on the workings of the models and the design choices facing CGE model developers.     

Geographic information system design for network equilibrium-based travel demand models

Travel demand analyses are useful for transportation planning and policy development in a study area. However, travel demand modeling faces two obstacles. First, standard practice solves the four travel components (trip generation, trip distribution, modal split and network assignment) in a sequential manner. This can result in inconsistencies and non-convergence. Second, the data required are often complex and difficult to manage. Recent advances in formal methods for network equilibrium-based travel demand modeling and computational platforms for spatial data handling can overcome these obstacles. In this paper we report on the development of a prototype geographic information system (GIS) design to support network equilibrium-based travel demand models. The GIS design has several key features, including: (i) realistic representation of the multimodal transportation network, (ii) increased likelihood of database integrity after updates, (iii) effective user interfaces, and (iv) efficient implementation of network equilibrium solution algorithms.     

Joint deployment of charging stations and photovoltaic power plants for electric vehicles

The focus of this study is to jointly design charging stations and photovoltaic (PV) power plants with time-dependent charging fee, to improve the management of the coupled transportation and power systems. We first propose an efficient and extended label-setting algorithm to solve the EV joint routing and charging problem that considers recharging amount choices at different stations and loop movement cases. Then, a variational inequality problem is formulated to model the equilibrium of EV traffic on transportation networks, and an optimal power flow model is proposed to model the power network flow with PV power plants and optimally serve the EV charging requirements. Based on the above models for describing system states, we then formulate a model to simultaneously design charging stations, PV plants, and time-dependent charging fee. A surrogate-based optimization (SBO) algorithm is adopted to solve the model. Numerical examples demonstrate that the proposed SBO algorithm performs well. Additionally, important insights concerning the infrastructure design and price management of the coupled transportation and power networks are derived accordingly.     

旅游交通融合发展研究——以福建省为例

为深入落实"交通强国"战略和实现"全域旅游"目标,推动旅游与交通深度融合发展,需做好旅游交通体系发展的顶层设计。通过分析旅游交通面临的问题,提出了旅游交通融合发展的理念。将福建省作为案例,针对福建旅游交通网络面临的问题,提出了"快旅慢游"旅游交通体系的建设目标、实施方案及保障措施。依托高铁、民航、邮轮和公路等综合立体交通网络,提出了"一带三环多放射"旅游交通"快旅"通道的发展思路;通过特色旅游产品开发、旅游服务质量提升等方面,规划了"慢游"微循环旅游交通的发展方案,构建了福建省多层次、综合立体的旅游交通体系发展新格局。以期通过福建省旅游交通融合发展案例研究,为其他省市旅游交通融合发展借鉴参考。     

Comparing the impact of future airline network change on emissions in India and the United States

In this paper we use simulation to analyze how flight routing network structure may change in different world regions, and how this might impact future traffic growth and emissions. We compare models of the domestic Indian and US air transportation systems, representing developing and mature air transportation systems respectively. We explicitly model passenger and airline decision-making, capturing passenger demand effects and airline operational responses, including airline network change. The models are applied to simulate air transportation system growth for networks of 49 airports in each country from 2005 to 2050. In India, the percentage of connecting passengers simulated decreases significantly (from over 40% in 2005 to under 10% in 2050), indicating that a shift in network structure towards increased point-to-point routing can be expected. In contrast, very little network change is simulated for the US airport set modeled. The simulated impact of network change on system CO₂ emissions is very small, although in the case of India it could enable a large increase in demand, and therefore a significant reduction in emissions per passenger (by nearly 25%). NO_x emissions at major hub airports are also estimated, and could initially reduce relative to a case in which network change is not simulated (by nearly 25% in the case of Mumbai in 2025). This effect, however, is significantly reduced by 2050 because of frequency competition effects. We conclude that network effects are important when estimating CO₂ emissions per passenger and local air quality effects at hub airports in developing air transportation systems.     

Complex Network Topology of Transportation Systems

ABSTRACT

As a strategic factor for a country to survive in the global competition, transportation systems have attracted extensive attention from different disciplines for a long time. Since the introduction of complex network theory in the last decade, however, studies on transport systems have witnessed dramatic progress. Most roads, streets, and rails are organized as a network pattern, while link flows, travel time, or geographical distance are regarded as weights. In this article, the authors will present the current state of topological research on transportation systems under a complex network framework, as well as the efforts and challenges that have been made in the last decade. First, different kinds of transportation systems should be generalized as networks in different ways, which will be explained in the first part of this paper. We follow this by summarizing network measures that describe topological characteristics of transportation networks. Then we discuss the empirical observations from the last decade on real transportation systems at a variety of spatial scales. This paper concludes with some important challenges and open research frontiers in this field.     

Optimal competitive freight network design as hierarchical variational inequalities programming problems

Freight networks are a case of systems that multiple participants are composing interrelations along the complete supply chain. Their interrelations correspond to alternative behavior, namely, cooperation, non-cooperation and competition, while they are large-scale spatially distributed systems combining multiple means of transportation and the infrastructure and equipment typically utilized for servicing demand, results to a complex system integration. In this paper, the case of the optimal design of freight networks is investigated, aiming to highlight the particularities emerging in this case of transportation facilities strategic and/or operational planning and the multiple game-theoretic and equilibrium problems that are structured in cascade and in hierarchies. The application that is investigated here focuses in the design of a significant ‘player’ of the freight supply chain, namely container terminals, while the proposed framework will aim on analyzing investment strategies built on integrated demand–supply models and the optimal network design format. The approach will build on the multilevel Mathematical Programming with Equilibrium Constraints (MPECs) formulation, but is further extended to cope with the properties introduced by the ‘designers’ (infrastructure authorities), shippers and carriers competition in all levels of MPECs. Since container terminals are typically competing each other, the nomenclature used here for formulating appropriate MPECs problems are based on hierarchies of Variational Inequalities (VI) problems, able to capture the alternative relationships emerging in realistic freight supply chains. The proposed formulations of the competitive network design case is addressed by a novel approach of co-evolutionary agents, which can be regarded as new in equilibrium estimation. Finally, the results are compared with alternative network design cases, namely the centralized cooperative and exchanging design. Under this analysis it is able to highlight the differences among alternative design cases, but moreover an estimation of the ‘price of anarchy’ in transportation systems design is offered, an element of both theoretical as well as practical relevance.     

A toll-based bi-level programming approach to managing hazardous materials shipments over an intermodal transportation network

This research proposes a bi-level bi-objective model to regulate the usage of rail intermodal terminals for hazardous materials (hazmat) shipments, where government imposes tolls to deter carriers from using certain terminals. The complexity of the resulting mathematical program motivates the development of a hybrid speed-constrained multi-objective particle swarm optimization algorithm, which is then integrated with CPLEX, to solve the model. Through a real problem instance based on the intermodal service chain of Norfolk Southern in US, the toll-setting model is examined and further compared with a regular network design approach, in which certain terminals are closed to hazmat containers. The computational results show that the toll-setting policy is more practical and efficient, and the two models can be combined as a two-stage strategy in long-term hazmat transportation regulations. Additional managerial insights are derived for different stakeholders.     

Solutions to the optimal network design problem with shipments related to transportation cost

Two versions of an optimal network design problem with shipments proportional to transportation costs are formulated. Extensions of an algorithm developed in prior research for solving these problems are proposed and tested. The performance of the algorithms is found to improve substantially as the dependence of shipments on costs is increased. Moreover, the optimal solutions obtained are unexpectedly robust with respect to a wide range of transportation cost assumptions. These findings could have important computational and policy implications if applicable to larger networks.