A reliability‐based traffic assignment model for multi‐modal transport network under demand uncertainty

In densely populated and congested urban areas, the travel times in congested multi‐modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day‐to‐day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on‐time arrival. In view of these, this paper presents a reliability‐based user equilibrium traffic assignment model for congested multi‐modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state‐augmented multi‐modal transport network is adopted in this paper to effectively model probable transfers and non‐linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

Sequential optimization approach for the multi‐class user equilibrium problem in a continuous transportation system

We consider a city region with several facilities that are competing for customers of different classes. Within the city region, the road network is dense, and can be represented as a continuum. Customers are continuously distributed over space, and they choose a facility by considering both the transportation cost and market externalities. More importantly, the model takes into account the different transportation cost functions and market externalities to which different customer classes are subjected. A logit‐type distribution of demand is specified to model the decision‐making process of users' facility choice. We develop a sequential optimization approach to decompose the complex multi‐class and multi‐facility problem into a series of smaller single‐class and single‐facility sub‐problems. An efficient solution algorithm is then proposed to solve the resultant problem. A numerical example is given to demonstrate the effectiveness and potential applicability of the proposed methodology.     

Network equilibrium for congested multi‐mode networks with elastic demand

This paper proposes an elastic demand network equilibrium model for networks with transit and walking modes. In Hong Kong, the multi‐mode transit system services over 90% of the total journeys and the demand on it is continuously increasing. Transit and walking modes are related to each other as transit passengers have to walk to and from transit stops. In this paper, the multi‐mode elastic‐demand network equilibrium problem is formulated as a variational inequality problem where the combined mode and route choices are modeled in a hierarchical logit structures and the total travel demand for each origin‐destination pair is explicitly given by an elastic demand function. In addition, the capacity constraint for transit vehicles and the effects of bi‐directional flows on walkways are considered in the proposed model. All these congestion effects are taken into account for modeling the travel choices. A solution algorithm is developed to solve the multi‐mode elastic‐demand network equilibrium model. It is based on a Block Gauss‐Seidel decomposition approach coupled with the method of successive averages. A numerical example is used to illustrate the application of the proposed model and solution algorithm.     

Passenger route guidance system for multi‐modal transit networks

In many public transport oriented cities in the world, especially Asian cities, the public transport system has been developed extensively, to the extent that it has become increasingly difficult to navigate. Although inter‐modal transfers are common and often necessary, a complete set of the routes across transport modes is generally not presented in a form that is accessible to travelers, as each operator would only publish its own routes. Moreover, the common nonlinear fare tables together with inter‐modal fare discounts pose challenges to travelers in deciding their best routes. This study develops a multi‐modal passenger route guidance system, called eFinder, to aid travelers with their combined mode‐route choices. We discuss the architecture and features of this system in this study. This system forms a platform for disseminating public transit information and should complement further development and use of the public transport network by enabling travelers to make informed choices.     

A method for solving the multi‐objective transit frequency optimization problem

Frequency setting takes place at the strategic and tactical planning stages of public transportation systems. The problem consists in determining the time interval between subsequent vehicles for a given set of lines, taking into account interests of users and operators. The result of this stage is considered as input at the operational level. In general, the problem faced by planners is how to distribute a given fleet of buses among a set of given lines. The corresponding decisions determine the frequency of each line, which impacts directly on the waiting time of the users and operator costs. In this work, we consider frequency setting as the problem of minimizing simultaneously users' total travel time and fleet size, which represents the interest of operators. There is a trade‐off between these two measures; therefore, we face a multi‐objective problem. We extend an existing single‐objective formulation to account explicitly for this trade‐off, and propose a Tabu Search solving method to handle efficiently this multi‐objective variant of the problem. The proposed methodology is then applied to a real medium‐sized problem instance, using data of Puerto Montt, Chile. We consider two data sets corresponding to morning‐peak and off‐peak periods. The results obtained show that the proposed methodology is able to improve the current solution in terms of total travel time and fleet size. In addition, the proposed method is able to efficiently suggest (in computational terms) different trade‐off solutions regarding the conflicting objectives of users and operators. Copyright © 2017 John Wiley & Sons, Ltd.     

A two‐leveled multi‐objective symbiotic evolutionary algorithm for the hub and spoke location problem

We consider a hub and spoke location problem (HSLP) with multiple scenarios. The HSLP consists of four subproblems: hub location, spoke location, spoke allocation, and customer allocation Under multiple scenarios, we aim to provide a set of well‐distributed solutions, close to the true Pareto optimal solutions, for decision makers. We present a novel multi‐objective symbiotic evolutionary algorithm to solve the HSLP under multiple scenarios. The algorithm is modeled as a two‐leveled structure, which we call the two‐leveled multi‐objective symbiotic evolutionary algorithm (TMSEA). In TMSEA, two main processes imitating symbiotic evolution and endosymbiotic evolution are introduced to promote the diversity and convergence of solutions. The evolutionary components suitable for each sub‐problem are defined. TMSEA is tested on a variety of test‐bed problems and compared with existing multi‐objective evolutionary algorithms. The experimental results show that TMSEA is promising in solution convergence and diversity.     

Pruning and ranking the Pareto optimal set,application for the dynamic multi‐objective network design problem

Solving the multi‐objective network design problem (MONDP) resorts to a Pareto optimal set. This set can provide additional information like trade‐offs between objectives for the decision making process, which is not available if the compensation principle would be chosen in advance. However, the Pareto optimal set of solutions can become large, especially if the objectives are mainly opposed. As a consequence, the Pareto optimal set may become difficult to analyze and to comprehend. In this case, pruning and ranking becomes attractive to reduce the Pareto optimal set and to rank the solutions to assist the decision maker. Because the method used, may influence the eventual decisions taken, it is important to choose a method that corresponds best with the underlying decision process and is in accordance with the qualities of the data used. We provided a review of some methods to prune and rank the Pareto optimal set to illustrate the advantages and disadvantages of these methods. The methods are applied using the outcome of solving the dynamic MONDP in which minimizing externalities of traffic are the objectives, and dynamic traffic management measures are the decision variables. For this, we solved the dynamic MONDP for a realistic network of the city Almelo in the Netherlands using the non‐dominated sorting genetic algorithm II. For ranking, we propose to use a fuzzy outranking method that can take uncertainties regarding the data quality and the perception of decision makers into account; and for pruning, a method that explicitly reckons with significant trade‐offs has been identified as the more suitable method to assist the decision making process. Copyright © 2012 John Wiley & Sons, Ltd.     

A dynamic shortest path algorithm using multi‐step ahead link travel time prediction

In this paper, a multi‐step ahead prediction algorithm of link travel speeds has been developed using a Kalman filtering technique in order to calculate a dynamic shortest path. The one‐step and the multi‐step ahead link travel time prediction models for the calculation of the dynamic shortest path have been applied to the directed test network that is composed of 16 nodes: 3 entrance nodes, 2 exit nodes and 11 internal nodes. Time‐varying traffic conditions such as flows and travel time data for the test network have been generated using the CORSIM model. The results show that the multi‐step ahead algorithm is compared more favorably for searching the dynamic shortest time path than the other algorithm.     

Multiple objective optimization of the fleet sizing problem for road freight transportation

A fleet sizing problem (FSP) in a road freight transportation company with heterogeneous fleet and its own technical back‐up facilities is considered in the paper. The mathematical model of the decision problem is formulated in terms of multiple objective mathematical programming based on queuing theory. Technical and economical criteria as well as interests of different stakeholders are taken into account in the problem formulation. The solution procedure is composed of two steps. In the first one a sample of Pareto‐optimal solutions is generated by an original program called MEGROS. In the second step this set is reviewed and evaluated, according to the Decision Maker's (DM's) model of preferences. The evaluation of solutions is carried out with an application of an interactive multiple criteria analysis method, called Light Beam Search (LBS). Finally, the DM selects the most desirable, compromise solution.     

Evaluating transport infrastructure decisions under uncertainty

This study uses a hybrid approach, combining cost–benefit analysis (CBA), multiple criteria decision analysis, and Dempster–Shafer Theory, to evaluate transport infrastructure decisions. This approach not only retains the advantages of CBA, but it also facilitates the incorporation of incomplete information into the evaluation process. A particular advantage of this hybrid approach is that it can synthesize evaluation results into an easily understood unit, namely utility. A case study of Taiwan's Tamsui-Taipei Riverside Highway Project is used to illustrate the evaluation method. The evaluation results show that, whereas government officials and city council members support the highway project, academic researchers oppose it. Overall, the decision group tends to positively approve this transport infrastructure investment. These results also reflect the actual situation in Taiwan as stakeholders grapple with the issues arising from the proposed Tamsui-Taipei Riverside Highway Project.     

Data mining using regularized adaptive B‐splines regression with penalization for multi‐regime traffic stream models

This paper presents a new data mining method that integrates adaptive B‐spline regression and traffic flow theory to develop multi‐regime traffic stream models (TSMs). Parameter estimation is implemented adaptively and optimally through a constrained bi‐level programming method. The slave programming determines positions of knots and coefficients of the B‐spline by minimizing the error of B‐spline regression. The master programming model determines the number of knots through a regularized function, which balances model accuracy and model complexity. This bi‐level programming method produces the best fitting to speed–density observations under specific order of splines and possesses great flexibility to accommodate the exhibited nonlinearity in speed–density relationships. Jam density can be estimated naturally using spline TSM, which is sometimes hardly obtainable in many other TSM. Derivative continuity up to one order lower than the highest spline degree can be preserved, a desirable property in some application. A five‐regime B‐spline model is found to exist for generalized speed–density relationships to accommodate five traffic operating conditions: free flow, transition, synchronized flow, stop and go traffic, and jam condition. A typical two‐regime B‐spline form is also explicitly given, depending only on free‐flow speed, optimal speed, optimal density, and jam density. Copyright © 2013 John Wiley & Sons, Ltd.     

Analytic hierarchy process application in selecting the mode of transport for a logistics company

As a multi‐criteria decision‐making (MCDM) method, the analytic hierarchy process (AHP) has been used considerably to solve hierarchical or network‐based decision problems in socio‐economic fields. Following an in‐depth explanation of the transport function in logistics and an overview of the MCDM methods, the AHP model is employed in the paper for a logistics company in selecting the most suitable way of transportation between two given locations in Turkey. The criteria used in the selection of transportation modes are identified as the cost, speed, safety, accessibility, reliability, environmental friendliness, and flexibility. Several cost parameters (transportation, storage, handling, bosphorus crossover) are incorporated into the decision‐making process. The application is carried out in instructional character. The results of the study indicate that the railway transportation, which is not widely used in Turkey, is also an alternative and suitable means of transportation. Copyright © 2013 John Wiley & Sons, Ltd.     

Multi‐criteria analysis procedure for sustainable mobility evaluation in urban areas

This paper proposes a procedure to evaluate sustainable mobility in urban areas. A set of indicators according to three dimensions of sustainability, i.e., environment, economics, and social aspects, are proposed to evaluate mobility in urban areas. The sustainable mobility evaluation is based on an Index calculated through a weighted multi‐criteria combination procedure. A group of specialists in Brazil was involved in the development of the Index by defining the weights for the criteria. An application of the methodology in the city of Belo Horizonte, capital of the State of Minas Gerais, with 2.24 million inhabitants, is presented to validate the methodology.     

A multi‐objective approach to the parcel express service delivery problem

Parcel express service in many countries assumes door‐to‐door delivery of parcels and small packages in the fastest possible way. Delivery companies usually organize hub delivery networks, as flows between hubs are characterized by the economy of scale effect. At hubs, parcels are exchanged across vans, trucks, and planes. To organize parcel delivery in a specific region, the parcel delivery company must make appropriate decisions about the total number of parcel delivery hubs, their locations, and the allocation of demand for facilities' services to facilities. These issues are modeled in this paper as a multi‐objective problem. The model developed is based on compromise programming and genetic algorithms. We also demonstrate in the paper an interactive manner in which a defined problem can be solved. The proposed model could be implemented in large‐scale networks. The paper also shows a case study of parcel delivery service in Serbia. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluating Locations for Intermodal Transport Terminals

Abstract

The choice of location for an intermodal transport terminal is an important component in a regional logistics system and a paramount decision for the investor as well as the community affected. The investor needs a realistic estimation of traffic potentials and incorporated cost-estimates of a location, since it serves as an important input to the investment decision process. Policy makers need instruments and tools to analyse the effect of intermodal terminals on the surrounding environment, which also enables a comparison between several possible locations in order to ensure sustainability and long-term competitiveness. The model in this paper allows a comparative evaluation of a set of possible intermodal terminal locations based on considerations by relevant actors. Furthermore, it presents a process of retrieving data and effectively communicating results. Considerations and interests of stakeholders are incorporated into the approach by means of evaluative criteria. The approach aims at facilitating the planning process of regional logistics systems in general and the evaluation process of intermodal terminal locations in particular by considering both public and private interests focusing on economic and environmental aspects.     

An integrated assessment of alternative land-based passenger transport policies: A case study in Tenerife

Over recent decades, there have been numerous cases of land-based transport policies that have lacked clear and coherent strategies. This has not only hampered the resolution of issues like road congestion, but has also created new ones (e.g. strong social opposition to new train infrastructures). The absence of such strategies highlights the need for long-term transport policies with a wider vision of the issues, since land-based transport cannot be considered from just a technical perspective.The main objective of this article is to implement a participatory integrated approach to facilitate the understanding of land-based passenger transport governance issues on Tenerife, in the Canary Islands. Relevant policy issues and alternatives are identified by the stakeholders involved. The inclusion of stakeholders in the assessment process is crucial to frame transport governance issues appropriately and to define and assess plausible policy alternatives. This assessment process even included a final step of validation of the results by stakeholders to foster discussion among them about transport issues and policy alternatives.Finally, due to the obstructive role played by some stakeholders in influencing past transport policies, an analysis of possible coalitions among stakeholders is also discussed.     

Optimization of pedestrian phase patterns at signalized intersections: a multi‐objective approach

This paper presents a multi‐objective optimization model and its solution algorithm for optimization of pedestrian phase patterns, including the exclusive pedestrian phase (EPP) and the conventional two‐way crossing (TWC) at an intersection. The proposed model will determine the optimal pedestrian phase pattern and the corresponding signal timings at an intersection to best accommodate both vehicular traffic and pedestrian movements. The proposed model is unique with respect to the following three critical features: (1) proposing an unbiased performance index for comparison of EPP and TWC by explicitly modeling the pedestrian delay under the control of TWC and EPP; (2) developing a multi‐objective model to maximize the utilization of the available green time by vehicular traffic and pedestrian under both EPP or TWC; and (3) designing a genetic algorithm based heuristic algorithm to solve the model. Case study and sensitivity analysis results have shown the promising property of the proposed model to assist traffic practitioners, researchers, and authorities in properly selecting pedestrian phase patterns at signalized intersections. Copyright © 2013 John Wiley & Sons, Ltd.     

A multi‐class mean‐excess traffic equilibrium model with elastic demand

Recent empirical studies have revealed that travel time variability plays an important role in travelers' route choice decisions. To simultaneously account for both reliability and unreliability aspects of travel time variability, the concept of mean‐excess travel time (METT) was recently proposed as a new risk‐averse route choice criterion. In this paper, we extend the mean‐excess traffic equilibrium model to include heterogeneous risk‐aversion attitudes and elastic demand. Specifically, this model explicitly considers (1) multiple user classes with different risk‐aversions toward travel time variability when making route choice decisions under uncertainty and (2) the elasticity of travel demand as a function of METT when making travel choice decisions under uncertainty. This model is thus capable of modeling travelers' heterogeneous risk‐averse behaviors with both travel choice and route choice considerations. The proposed model is formulated as a variational inequality problem and solved via a route‐based algorithm using the modified alternating direction method. Numerical analyses are also provided to illustrate the features of the proposed model and the applicability of the solution algorithm. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessment of Cross‐Border Spillover Effects of National Transport Infrastructure Plans: An Accessibility Approach

Abstract

Traditional transport infrastructure assessment methodologies rarely include the full range of strategic benefits for the transportation system. One of these benefits is the contribution to cross‐border integration, critical for the European integration process. However, this is a key issue in strategic planning and decision‐making processes, as its inclusion may increase the probability of large‐scale transport infrastructure projects being funded. This paper presents a methodology for the measurement of the contribution of transport infrastructure plans to European integration. The methodology is based on the measurement of the improvement in network efficiency in cross‐border regions of neighbouring countries, via accessibility calculations in a Geographical Information System support. The methodology was tested by applying it to the ambitious road and rail network extensions included in the Spanish Strategic Transport and Infrastructure Plan (PEIT) 2005–2020. The results show significant and important network efficiency improvements of the PEIT outside the Spanish border. For the road mode, while the Spanish average accessibility improvement accounts for 2.6%, average improvements in cross‐border regions of France and Portugal are of 1.8%. And for the rail mode, the corresponding Spanish value is 34.5%, whereas in neighbouring regions it accounts for 20.2%. These results stress the significant importance of this strategic benefit and the consequent need for its inclusion in strategic planning processes. Finally, the paper identifies the potential of the methodology when applied at different administrative levels, such as the local or state levels.