Standardization of capacity unit for headway-based rail capacity analysis

Determining the required capacity upgrades to accommodate future demand is a critical process in assisting public and private financing of capacity investments. Conventional railway systems usually operate multiple types of trains on the same track. These different types of trains can exert substantially different capacity impact, and can cause serious operational conflicts. In the past, rail line capacity is commonly defined as the maximum number of trains that can be operated on a section of track within a given time period. However, a specific unit (trains/hr or trains/day) does not reflect the heterogeneity of train types. According to the concept of base train equivalents (BTE) and base train unit (BTU), this study developed headway-based models to determine BTE for transforming different train types into a standard unit (i.e., BTU). An approximate method for lines with three and more types of trains was also proposed to compute BTEs for non-base trains. Results from the case studies demonstrate that this method enables the standardization of rail capacity unit, facilitates assessment of the impact from heterogeneous trains, and allows comparison and evaluation of the capacity measurements from different lines and systems.     

A hierarchical customer satisfaction framework for evaluating rail transit systems of Istanbul

This paper provides a hierarchical customer satisfaction framework to measure rail transit lines’ performances in Istanbul. The problems related to rail transit line systems are addressed via customer satisfaction surveys. Then, a framework is proposed combining statistical analysis, fuzzy analytic hierarchy process, trapezoidal fuzzy sets and Choquet integral to evaluate customer satisfaction levels. Next, the criteria need to be improved are determined and specific recommendations to enhance the operation for specific lines are suggested. The proposed framework provides directions for the future investments and it also can be used at a more macroscopic level to determine the operational deficiencies. Furthermore, it can be generalized and applied to complex decision making problems that include uncertain and subjective data or vague information.     

An analysis of rail freight operational efficiency and mode share in the British port-hinterland container market

The growth in container shipping poses considerable challenges to efforts to reduce the negative externalities associated with freight transport. There are particular concerns about the impacts of the associated port-hinterland freight flows. Through empirical research, this paper examines trends in the operational efficiency of the British port-hinterland container rail freight market and to assess the impacts of any changes on the overall sustainability of this market. Original survey work conducted in 2007 and 2015 has allowed longitudinal and cross-sectional analysis of the characteristics of this market.The survey findings reveal that rail’s mode share of port container throughput (in TEU) has increased from 14.7% in 2007 to 16.6% in 2015 and it is likely that its share of the associated hinterland activity has also risen. Rail was carrying 25% more TEU by 2015 without an increase in train service provision. Increases in mean train capacity and mean load factor were observed, leading to growth in the mean train load from 44 TEU in 2007 to 55 TEU in 2015. This considerable improvement in operational efficiency is expected to have reduced the negative externalities per unit of transport activity associated with the rail-borne hinterland container flows, though scope is identified for further improvements in sustainability.     

An analysis of internal transit systems requirements for central cities

The deficient performance of existing downtown transit distribution systems may significantly affect the overall performance of the urban transportation system in many metropolitan areas. This paper has two principal objectives. First, it describes an approach entitled Performance Requirements Analysis for developing a set of requirements or standards that a downtown transit system should satisfy and structuring these requirements so as to generate a small set of alternative generic systems for detailed evaluation. Second, it provides a preliminary assessment of performance requirements for distribution systems in 19 of the largest cities in the United States.     

An integrated framework for embedding large-scale dynamic traffic assignment models in advanced traveler information systems

In recent years, increasing attention has been drawn to the development of various applications of intelligent transportation systems (ITS), which are credited with the amelioration of traffic conditions in urban and regional environments. Advanced traveler information systems (ATIS) constitute an important element of ITS by providing potential travelers with information on the network's current performance both en-route and pre-trip. In order to tackle the complexity of such systems, derived from the difficulty of providing real-time estimations of current as well as forecasts of future traffic conditions, a series of models and algorithms have been initiated. This paper proposes the development of an integrated framework for real-time ATIS and presents its application on a large-scale network, that of Thessaloniki, Greece, concluding with a discussion on development and implementation challenges as well as on the advantages and limitations of such an effort.     

Integrated operations planning and revenue management for rail freight transportation

In the rail industry, profit maximization relies heavily on the integration of logistics activities with an improved management of revenues. The operational policies chosen by the carrier have an important impact on the network yield and thus on global profitability. This paper bridges the gap between railroad operations planning and revenue management. We propose a new bilevel mathematical formulation which encompasses pricing decisions and network planning policies such as car blocking and routing as well as train make-up and scheduling. An exact solution approach based on a mixed integer formulation adapted to the problem structure is presented, and computational results are reported on randomly generated instances.     

Challenges raised by freight for the operations planning of a shared-use rail network. A French perspective

Operating rail infrastructures that are shared among different uses is complex. In Western Europe, the predominance of passenger traffic over freight has traditionally led to thorough scheduling of capacity use, with an increasing tendency to anticipate through the design of regular-interval timetables. The paper discusses the specific challenges posed by fitting freight into the timetabling process for a mixed-use rail network, based on current French experience. The analysis is carried out from the perspective of the infrastructure manager. It is mainly supported by the results of a series of about 30 interviews, carried out in 2012 and 2013 with the parties involved in the timetabling process. The paper provides a comprehensive understanding of the process in terms of organization, rules and practices, with an emphasis on the characteristics of freight traffic compared with passenger traffic. The author highlights three key management issues for the French infrastructure manager when dealing with freight: (1) the uncertainty surrounding the mid-long term development of the rail freight market at the national level; (2) the heterogeneity resulting from the diversity of commodities, convoys and profiles and behaviors of the capacity applicants; (3) the volatility of some freight traffic resulting in a great amount of activity in the later stages of the timetabling process. If uncertainty about the future appears to be a highly sensitive issue in the French context, heterogeneity and volatility of freight traffic can be perceived as management challenges that may be experienced, to a greater or lesser degree, on other rail networks.     

An integrated measure of accessibility and reliability of mass transit systems

The growth of a city or a metropolis requires well-functioning transit systems to accommodate the ensuing increase in travel demand. As a result, mass transit networks have to develop and expand from simple to complex topological systems over time to meet this demand. Such an evolution in the networks’ structure entails not only a change in network accessibility, but also a change in the level of network reliability on the part of stations and the entire system as well. Network accessibility and reliability are popular measures that have been widely applied to evaluate the resilience and vulnerability of a spatially networked system. However, the use of a single measure, either accessibility or reliability, provides different results, which demand an integrated measure to evaluate the network’s performance comprehensively. In this paper, we propose a set of integrated measures, named ACCREL (Integrated Accessibility and Reliability indicators) that considers both metrics in combination to evaluate a network’s performance and vulnerability. We apply the new measures for hypothetical mass transit system topologies, and a case study of the metro transit system in Seoul follows, highlighting the dynamics of network performance with four evolutionary stages. The main contribution of this study lies in the results from the experiments, which can be used to inform how transport network planning can be prepared to enhance the network functionality, thereby achieving a well-balanced, accessible, and reliable system. Insights on network vulnerability are also drawn for public transportation planners and spatial decision makers.     

GHG-emission models for assessing the eco-friendliness of road and rail freight transports

Intermodal rail/road transportation is an instrument of green logistics, which may help reducing transport related greenhouse gas (GHG) emissions. In order to assess the environmental impact of road and rail transports, researchers have formulated very detailed microscopic models, which determine vehicle emissions precisely based on a vast number of parameters. They also developed macroscopic models, which estimate emissions more roughly from few parameters that are considered most influential. One of the goals of this paper is to develop mesoscopic models that combine the preciseness of micro-models while requiring only little more information than macro-models. We propose emission models designed for transport planning purposes which are simple to calibrate by transport managers. Despite their compactness, our models are able to reflect the influence of various traffic conditions on a transport’s total emissions. Furthermore, contrasting most papers considering either the road or the rail mode, we provide models on a common basis for both modes of transportation. We validate our models using popular micro- and macroscopic models and we apply them to artificial and real world transport scenarios to identify under which circumstances intermodal transports actually effect lower emissions. We find that travel speed and country-specific energy emission factors influence the eco-friendliness of intermodal transports most severely. Hence, the particular route chosen for a transnational intermodal transport is an important but so far neglected option for eco-friendly transportation.     

Impact analysis of climate change on rail systems for adaptation planning: A UK case

Climate change poses critical challenges for rail infrastructure and operations. However, the systematic analysis of climate risks and the associated costs of tackling them, particularly from a quantitative perspective, is still at an embryonic phase due to the kaleidoscopic nature of climate change impacts and lack of precise climatic data. To cope with such challenges, an advanced Fuzzy Bayesian Reasoning (FBR) model is applied in this paper to understand climate threats of the railway system. This model ranks climate risks under high uncertainty in data and comprehensively evaluates these risks by taking account of infrastructure resilience and specific aspects of severity of consequence. Through conducting a nationwide survey on the British railway system, it dissects the status quo of primary climate risks. The survey implies that the top potential climate threats are heavy precipitation and floods. The primary risks caused by the climate threats are bridges collapsing and bridge foundation damage due to flooding and landslips. The findings can aid transport planners to prioritise climate risks and develop rational adaptation measures and strategies.     

Impacts of rail transit access on land and housing values in China: a quantitative synthesis

ABSTRACT

Rail transit investment has been viewed as a prominent policy instrument for local and regional development. However, little is known about to what extent the theorised changes in land and housing values arising from rail transit access can be substantiated by evidence in a large developing country context. This paper presents a quantitative review of empirical studies that analysed the impacts of rail transit access on land and housing values in China. We review empirical analyses in 67 studies from 1997 to 2018 for which we encode quantitative results along with a range of theoretically combinations of spatially contextual characteristics, data and methodological-design characteristics. The results show that there are significant variations in the size estimates of effects of rail transit access across studies. Such variations are associated with rail project types, data and methodological designs. Our study provides the insights on what has already been known and what needs to be known on evaluating real estate consequences of rail transit improvements in developing countries.     

Welfare maximization for bus transit systems with timed transfers and financial constraints

Conventional and flexible bus services may be combined to better serve regions with a wide range of characteristics. If demand densities and resulting service frequencies are low, the coordination of bus arrivals at transfer stations may significantly reduce passenger transfer times. A method is proposed for integrating, coordinating, and optimizing bus services while considering many‐to‐many travel patterns, demand elasticity, financial constraints, and appropriate service type for various regions. The objective is to maximize welfare, that is, the sum of producer and consumer surplus. The problem is solved with a hybrid optimization method, in which a genetic algorithm with bounded integer variables is selected for solving one of the subproblems. The service types, fares, headways, and service zone sizes are jointly optimized. Sensitivity analyses explore how the choice among conventional and flexible busses depends on the demand, subsidy, and demand elasticity parameters. The results also show that welfare can increase due to coordination, and these increases are found to be higher in cases with high demand or low subsidy. Copyright © 2015 John Wiley & Sons, Ltd.     

A multiple criteria approach for the evaluation of the rail transit networks in Istanbul

The deficiencies in the Istanbul transportation system have led the local authorities to plan several alternative transportation projects. In this paper three alternative rail transit network proposals are evaluated by using Analytic Hierarchy Process (AHP), a multiple criteria decision support system. The AHP facilitates decision-making by organizing perceptions, experiences, knowledge and judgments, the forces that influence the decision, into a hierarchical framework with a goal, scenarios, criteria and alternatives of choice. Based on this analysis, the decision makers have developed a new alternative as a combination of the most closely competing two alternative rail transit networks. This combination rail transit network is currently under construction.     

Estimation of rail passenger flow and system utilization with ticket transaction and gate data

Capturing the dynamics in passenger flow and system utilization over time and space is extremely important for railway operators. Previous studies usually estimated passenger flow using automatic fare collection data, and their applications are limited to a single stopping pattern and/or a single type of ticket. However, the conventional railway in Taiwan provides four types of ticket and five types of train service with a number of stopping patterns. This study develops a comprehensive framework and corresponding algorithms to map passenger flow and evaluate system utilization. A multinomial logit model is constructed and incorporated in the algorithms to estimate passenger train selection behavior. Results from the empirical studies demonstrate that the developed framework and algorithms can successfully match passengers with train services. With this tool, operators can efficiently examine passenger flow and service utilization, thereby quickly adjusting their service strategies accordingly to improve system performance.     

An optimization model of energy and transportation systems: Assessing the high-speed rail impacts in the United States

This paper presents a long-term investment planning model that co-optimizes infrastructure investments and operations across transportation and electric infrastructure systems for meeting the energy and transportation needs in the United States. The developed passenger transportation model is integrated within the modeling framework of a National Long-term Energy and Transportation Planning (NETPLAN) software, and the model is applied to investigate the impact of high-speed rail (HSR) investments on interstate passenger transportation portfolio, fuel and electricity consumption, and 40-year cost and carbon dioxide (CO₂) emissions. The results show that there are feasible scenarios under which significant HSR penetration can be achieved, leading to reasonable decrease in national long-term CO₂ emissions and costs. At higher HSR penetration of approximately 30% relative to no HSR in the portfolio promises a 40-year cost savings of up to $0.63 T, gasoline and jet fuel consumption reduction of up to 34% for interstate passenger trips, CO₂ emissions reduction by about 0.8 billion short tons, and increased resilience against petroleum price shocks. Additionally, sensitivity studies with respect to light-duty vehicle mode share reveal that in order to realize such long-term cost and emission benefits, a change in the passenger mode choice is essential to ensure higher ridership for HSR.     

Design and development of interactive trip planning for web-based transit information systems

This article presents a Web-based transit information system design that uses Internet Geographic Information Systems (GIS) technologies to integrate Web serving, GIS processing, network analysis and database management. A path finding algorithm for transit network is proposed to handle the special characteristics of transit networks, e.g., time-dependent services, common bus lines on the same street, and non-symmetric routing with respect to an origin/destination pair. The algorithm takes into account the overall level of services and service schedule on a route to determine the shortest path and transfer points. A framework is created to categorize the development of transit information systems on the basis of content and functionality, from simple static schedule display to more sophisticated real time transit information systems. A unique feature of the reported Web-based transit information system is the Internet-GIS based system with an interactive map interface. This enables the user to interact with information on transit routes, schedules, and trip itinerary planning. Some map rendering, querying, and network analysis functions are also provided.     

A framework for user- and system-oriented optimisation of fuel efficiency and traffic flow in Adaptive Cruise Control

Fully automated vehicles could have a significant share of the road network traffic in the near future. Several commercial vehicles with full-range Adaptive Cruise Control (ACC) systems or semi-autonomous functionalities are already available on the market. Many research studies aim at leveraging the potential of automated driving in order to improve the fuel efficiency of vehicles. However, in the vast majority of those, fuel efficiency is isolated to the driving dynamics between a single follower-leader pair, hence overlooking the complex nature of traffic. Consequently fuel efficiency and the efficient use of the roadway capacity are framed as conflicting objectives, leading to fuel-economy control models that adopt highly conservative driving styles.This formulation of the problem could be seen as a user-optimal approach, where in spite of delivering savings for individual vehicles, there is the side-effect of the deterioration of traffic flow. An important point that is overlooked is that the inefficient use of roadway capacity gives rise to congested traffic and traffic breakdowns, which in return increases energy costs within the system. The optimisation methods used in these studies entail high computational costs and, therefore, impose a strict constraint on the scope of problem.In this study, the use of car-following models and the limitation of the search space of optimal strategies to the parameter space of these is proposed. The proposed framework enables performing much more comprehensive optimisations and conducting more extensive tests on the collective impacts of fuel-economy driving strategies. The results show that, as conjectured, a “short-sighted” user-optimal approach is unable to deliver overall fuel efficiency. Conversely, a system-optimal formulation for fuel efficient driving is presented, and it is shown that the objectives of fuel efficiency and traffic flow are in fact not only non-conflicting, but also that they could be viewed as one when the global benefits to the network are considered.     

Development of efficient stop planning optimization process for high‐speed rail systems

The Taiwan High Speed Rail (THSR) has recently added three additional stations to its original network. Although the three additional stations can improve accessibility to the system, these new stations can present difficulties in the transportation planning process, particularly for planning of train stops. The additional stations may benefit some passengers, but may also lengthen the travel time for the other passengers. Therefore, the main challenge faced by THSR is finding an efficient way to design appropriate stopping patterns. Past studies on stop planning usually adopted meta‐heuristics or decomposition methods to solve this complex problem. Although these solution techniques can improve solution efficiency, none of them can guarantee the optimality of the solution and capture the transfer movement of different stopping patterns. In this research, we proposed an innovative network structure to address complex stop planning problems for high‐speed rail systems. Given its special network structure, two binary integer programming models were developed to simultaneously form and determine the optimal stopping patterns for real‐world THSR stop planning problems. An optimization process was also developed to accurately estimate the station transfer time corresponding to the variation in stopping patterns and passenger flow. Results of the case studies suggest that the proposed binary integer programming models exhibit superior solution quality and efficiency over existing exact optimization models. Consequently, using this stop planning optimization process can help high‐speed rail system planners in designing optimal stopping patterns that correspond to passenger demand. Copyright © 2017 John Wiley & Sons, Ltd.     

An agent-based multimodal simulation model for capacity planning of a cross-border transit facility

Cross-border transit facilities constitute major public investment, and thus must serve the long-term needs of the communities, such as providing access to schools and businesses, contributing to a shared regional culture and lifestyle, fostering international trade, and supporting jobs for the region’s residents. Numerous studies have been conducted to evaluate the economic implications of vehicular flow delays at border crossings, however none of the studies focused on assessing cross-border flow of bus passengers and pedestrians. Since pedestrians are considered to be autonomous, intelligent, and perceptive, it is a challenging task to predict pedestrian movement and behavior in comparison to vehicular flows which follow a specific set of traffic rules. This paper presents a multiagent based multimodal simulation model to evaluate the capacity and performance of a cross-border transit facility. The significance of this research is the use of dynamic mode choice functionality in the model, which allows an individual person to make instantaneous choices between available modes of transportation. The scope of interest of the paper is limited to simulating access interface, circulation areas, ancillary and processing facilities. The developed model was calibrated to ensure realistic performance, and validated against specific performance criteria such as throughput per processing facility. In order to demonstrate the applicability of the developed simulation model, capacity and operational planning of a pedestrian transit facility was performed. The relative performance of alternative design or configuration was evaluated using the level of service criteria. Lastly, the effectiveness of each proposed capacity or operational improvement strategy was compared to the “do-nothing” scenario.     

An integrated risk assessment model: A case of sustainable freight transportation systems

The major challenge in the development of sustainable freight transportation systems (SFTSs) is due to the involvement of numerous dynamic uncertainties and intrinsic sustainability risks. Sustainability risks are potential threats that can have undesirable impacts on the sustainability of a system. The main objective of this study is to identify and evaluate the sustainability risks associated with freight transportation systems (FTSs). Accordingly, a risk analysis approach is developed by innovatively integrating the intuitionistic fuzzy set theory and D-number theory to quantitatively model the sustainability risks. Intuitionistic fuzzy numbers can examine both the membership and non-membership degrees of an element while the D-number theory increases the objectivity of assessments by fusing multiple expert judgments. The proposed risk assessment model facilitates the managers in the development of SFTSs by ensuring visibility, predictability and measurability in freight operations. Unlike the conventional perception, the findings indicate that most of the high priority sustainability risks in FTSs are socially induced rather than financially driven and consciousness in people’s conduct is must to attain the positive results. The analysis alerts the freight managers toward the high priority sustainability risks and guides in pro-active strategy formulation and optimum allocation of mitigation resources to minimize disruptions in SFTSs.